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Chapter I

INTRODUCTION

Growth and Inequalities

During the last decade a perception is growing in the

world that China and India are becoming two major economic

superpowers in the world. Consequently, business firms, especially, MNCs

running towards India and China so as to take advantage of the

prevalent and fast growing market in these two countries.

Table1.1 GDP growth Rate of Select World Economies

Source: World Development Report (2013), World Bank

The above Table 1.1 brings forth the fact that the economy of India has

experienced Mean annual growth rate of GDP of 6 per cent during the

decade 1990 to 2000 which further improved to 6.9 per cent next five years

period i.e. 2000to 2005. Accordingly, the growth rate of population, during

the time span of 2000 to 2005, dropped down to 1.5 per cent per year.

Apparently, India occupied the second rank in the ranking of top GDP

bearing economies of the world, during the period 1990-2005, as published

in the World Development Report (2013). The GDP growth rate of India has

Ranking Country Mean Annual GDP Growth Mean Annual Population Rate %

1990-2000* 2000-05 2011 1990-04* 2000-05 2011

1. USA 3.5 2.8 1.7 1.2 1 0.72

2. China 10.6 9.6 9.3 0.9 0.6 0.47

3. Japan 1.3 1.3 -0.7 0.2 0.2 0.28

4. India 6 6.9 6.85 1.7 1.5 1.36

5. Germany 1.8 0.7 3.02 0.3 0.1 -0.06

6. UK 2.7 2.3 0.76 0.3 0.2 0.66

7. France 2 1.5 1.69 0.4 0.6 0.55

8. Italy 1.6 0.7 0.43 0.1 -0.1 0.47

9. Russian Fed. -4.7 6.2 4.33 -0.2 -0.4 0.01

10. Spain 2.6 3.1 0.42 0.7 1.4 0.36

11. Korean Repb. 5.8 4.6 3.63 0.8 0.5 0.74

12. Canada 3.1 2.6 2.45 1 1 1.03

13. Mexico 3.1 1.9 3.91 1.6 1 1.2

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exhibited a rising trend and has been reckoned at 9.7 per cent I the year

2006-07, but declined sharply to 6.85 per cent level in the year 2011.

Consequently, India conferred the honor of being the second fastest

growing economy, only next to China in the world. As the growth rate of

population declining to 1.5 per cent the per capita GDP growth would also

get accelerated and the economy of India followed this momentum for

next two decades, the gap between the per capita GDP of India as

compared with world‘s developed economies would gradually narrow

down. In order to maintain its, image of second fastest emerging economy

of the world and level up with China, India has to keep up its momentum of

GDP growth rate up to 10 per cent level per year. Thus, the entire question

boils down to maintain this high GDP growth rate over the next two

decades.

India as an Economic Super Power

The irony of Indian Economy is, it has more than hundred

billionaires, but the fundamental question that stares in the face of the

country‘s polity and economy is: Do the number of billionaires‘ bears any

impact on the state of poverty, inequality, unemployment and hunger. If

the economic well being does not improve at all, then only a small section

of the county‘s population appropriates country‘s economic resources to

their favor, then any claim of being a real economic super power, will be

considered as false prided. Although, India may parade its handful of

billionaires as a symbol of being great and powerful, it would be sensible

and worthy to examine the reality of status of economic super power in

India. Some evidences which contradict the claim of being an economic

super power are discussed below in sequential manners which are as

follows;

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Table1.2 Employment Growth Rate in India

Firstly, while considering the situation of employment in India, shows a

gloomy picture as the aggregate employment in organized sector

indicates an annual average negative growth rate of 0.25 per cent from

during the period 1997-2011. While classifying it further into Public and

Private sector, the data reveals an even worse condition of rate of growth

of employment, as the rate of growth of employment in private sector

moved up from 0.44 per cent in 1983-94 to 1.97 per cent during 1994-2010.

Although the private organized sector share in employment has improved,

large proved incapable to generate expected employment opportunities

higher than the rate of increase in labor force. In this regard, therefore the

contributions of billionaires are disappointing.

Secondly if we consider the poverty Ratio, it exhibits the fact that on the

basis of uniform recall period, poverty ratio has declined from 36 per cent in

93-94 to 27.5 per cent during 2004-05. The obvious conclusion is that the

extent of decline in poverty ratio in post reform period was only 0.70 per

cent during 1994-2004, as against 0.85 per cent in the pre reform period

(1983-94). This showdown in poverty ratio could be credited to increase of

inequality during post reform period. Thus, there was an enclave type

growth during the post reform period, which boosted the rate of growth

further but failed to percolate its benefits among the poor.

Employment in Organized Sector in India (lakhs)

1994

2010

Public Sector 194.45

178.6 Private Sector 79.3

287.1

Total

273.75

287.1

Growth Rate of Employment

1993-94

1994-2010

Public Sector 1.5

-0.55 Private Sector 0.44

1.97

Total

1.2

0.25

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On the basis of methodology of Tendulkar Committee, the ratio of poverty

estimated at 37.2 percent, during the year 2004-05 that further decline to

29.8 per cent in 2009-10. However the basis for determining the poverty line

has been subject to wide criticism.

Thirdly, the facts furnished by the National Family Health Survey (2005-06)

reveals certain discouraging facts:

1. The children within age group of 6- 35 months, were found to be anemic

and this percentage was even higher for rural with 81.2 per cent. Besides

this, 56per cent married women were found to be anemic. Among married

men under the age group of 15-49 were found to be anemic.

2. Percentage of children who are stunted was 35 per cent and for those who

were wasted were 19 percent similarly, underweight children under age 3

were as high as 46 per cent.

3. A look at the availability of basic facilities reveals that only 68 per cent

households had electricity that includes 93 per cent of urban population

and merely per cent rural population. Availability of piped drinking water is

only at 46 per cent of population that includes 71 per cent of urban

population and 28 per cent of rural population. Toilet facility was available

only to 45 per cent of the total population, which includes 83 per cent

urban area and 26 per cent of rural areas.

Thus, on an overall scenario of the Indian economy is not as rosy

as always stated by government mouthpieces, as a parade of handful

brigade of billionaires, cannot make the economy of India the ‗economic

powerhouse‘, until the benefits of growth rate are not percolated to the

last deprived citizen of the nation.(Table 1.3)

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Table1.3 Percentage of Households with basic Amenities (2005-06)

Total Rural Urban

Have Electricity

67.9 93.1 55.7

Use piped drinking water

42 71 27.9

Have access to toilet facility

44.5 83.1 25.9

Live in Pucca House

41.4 74.1 25.5

Source: National Family Health Survey (2005-06)

To conclude it could be mentioned that the growth process is leading to a

rapid increase of the Indian middle class, confined more to the cities and

metros, in this sense, it does not adequately promote inclusive growth but it

leads to greater concentration of income in the urban areas vis-à-vis rural

areas.

Present Position of Income Distribution in India

National Council of Applied Economics Research (NCAER) has

conducted a study on Indian middle class titled as ―The Great Indian

Middleclass‖. As the middle class has been described in various ways,

especially in cultural terms, or in terms of education and lifestyle, which

could not be quantifiable if considered as variable. NCAER has made an

attempt to analyze the numbers declining in various income categories

and redefine the middle class in terms of annual income within a range of

Rs. 3.4 to 7 lakhs at 2009-10 level of prices. After the completion of the study

NCAER made the following findings;

1. The middle class could be defined as the households earning Rs. 3.4-17

lakhs, Rs. 2-10 lakhs annually. During 2001-02, total middle class households

increased from 4.5 million to 10.7 million-an increase of 138 per cent. In

2009-10 they are expected to grow to 28.4 million accounting for a total

population of 150 million.

2. At the bottom of the middle class is the category defined as seekers who

have just moved into the middle class bracket with an income of Rs. 3.4 to

7 lakhs, Rs. 2-7 lakhs.

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3. There is also a category referred as strivers accounting for 1.7 million

households with an annual income of Rs. 5-10 lakhs. This class is growing at

the rate of 18 per cent per annum.

4. Rich class with an annual income of over 10lakhs accounted for only 0.8

million households in 2001-02, which is expected to rise at 3.8 million by

2009-10

5. As a result of economic prosperity resulting from higher growth rate of GDP

and the distribution of income in favor of middle classes and rich

households, the demographic pattern has undergone a rapid change. The

size of the middle class which was 10.7 million in 2001-02 is expected to

reach 28.4 million household in the year 2009-10.

6. Urban households accounts for nearly two-third of the total household and

rural households are poor one third. Hence, it could be understood that

growth of middle class is more or less an urban phenomenon. (Table 1.4)

Source: NCAER (2006), The Great Indian Middle Clas

7. Table 1.5 exhibits, the distribution of households among various categories

exhibits the fact that the bottom quintile group i.e the lowest income class

is expected to fall from 72 per cent to 52 per cent – a dramatic shift of

nearly 20 per cent. As against it, the aspirers tend to0 show a rise from

about 6 per cent to 13 per cent during 2001-02 and 2009-10.

Table 1.4 Size of Different Income Classes in Rural and Urban Areas

Class Income Range Share of Rural Households %

2001-02 2009-10 2001-02 2009-10

Deprieved Below RS. 90000 18.2 15.8 81.8 84.2

Aspirers RS.90000 - Rs200000 41.5 38.8 48.5 61.2

Middle Class Rs.200000-1000000 64.8 66.6 35.2 33.4

Rich Over 10Lakhs 77.1 77.8 22.9 22.2

Total 28.4 31.2 71.6 68.8

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Table 1.5 Distribution of Household Income

Annual Households Income at 2004-05 prices 2010-11 2015-16

Deprived Below Rs.112000 134.7 113.3

Aspirers Rs.112000-250000 70.7 89.4

Middle Class Rs.250000-1250000 31.4 53.3

Rich Over Rs.1250000 3.2 6.6

Source: NCAER (2006), the Great Indian Middle Class

Inflation and Economic Growth

Economic Development since 1951 has consisted of a huge

amount of continuous and sustained investment. In order to finance such

investment, the Government had to resort to heavy, taxation, extensive

borrowing and deficit financing. The first two methods of financing

economic development consisted mainly of transferring financial resources

from general public to the government and were broadly non-inflationary

though indirect taxes definitely could push up prices through fueling cost

push factors. The last method, viz. deficit financing, i.e. financing extra

expenditure through borrowing from reserve bank- led to increase in the

supply of money with the general public and consequently increase in the

demand for goods and services. At the same time, the supply of

consumption goods did not increase proportionately with the increase in

the demand for them.

As, some inflationary pressure is inevitable, in an emerging economy like

India. It is, however, significant that it does not interrupt the steady and

rising momentum of economic growth. From the Sixth Plan (pre reform

period) onwards, the rate of economic growth rose steadily in India. By the

end of the tenth five year plan (post reform period), the rate of growth

touched 9 per cent. Such a rate of inflation with equivalent and more rises

in demand is bound to exert pressure on level of prices. At the same time,

the rate of increase in production of essential agricultural goods may not

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match the increase in demand. This gives impetus to inherent inflationary

pressure in the Indian economy. Accordingly, the control of inflation and

maintenance of relatively stable prices are crucial for a successful

implementation of plan programmes. But control of inflation needs

herculean efforts because of various internal and external conditions: a).

internally, bottlenecks in various critical sectors like power coal and rail

transport and stagnant agricultural production; and b). externally, higher

inflationary international environment and unfavorable terms of trade and

heavy adverse balance of payments.

Necessarily, therefore the control of inflation was given top priority in all five

year plans and needed all the ingenuity and imagination of the

government.

Recent Inflationary pressure in India

In the year 2008, the whole sale price index (CPI), touched the

level of 240.7 during the Ist week of August, against 213.7 on August 2007

(1993-94=100) signaling 12.63 per cent rise in CPI during the year, highest

witness during the last year ten years. It crossed the limit of 5 per cent

comfort zone as specified by RBI. However gradually inflation has shown a

declining trend as there has been a fall in the rate of inflation due to

recessionary trend such that rate of inflation has reached near zero or even

negative between September 2008 and February 2009.CPI declined from

241.5 in September 2008to 227.6 in February 2009. Subsequent months of

the year 2009, once again witnessed rapid rise in the level of prices and the

whole sale price index climbed to 246.5 in December 2009, up from 229.7 in

December 2008. Since then we find inflation rate nearing 8-10 per cent

annually. Between April 2010 and December 2012, we find rate of inflation

indicated by CPI to be above 7 per cent and in September 2011, reaching

even the magic figure of 10 per cent.

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Source: Department of Industrial Policy Promotion, Central Statistical

Organization IW: Industrial Workers, AL- Agricultural Laborers

Calculating the whole sale price index has always been a subject of

criticism. Critics routinely raise their voice regarding flawed measurement of

CPI. Considering this issue various parliamentary and other committees

were formed by the government, although several recommendations were

given by the previous committees but government has always been

Table 1.6 Different Price Indices

CPI CPI-IW CPI-AL

2010 April 10.88 13.33 14.96

May 10.48 13.91 13.68

June 10.25 13.73 13.02

July 9.98 11.25 11.02

August 8.87 9.88 9.13

September 8.98 9.82 8.43

October 9.08 9.7 7.14

November 8.2 8.33 7.99

December 9.45 9.47 8.67

January 9.47 9.3 8.55

February 9.54 8.82 9.14

March 9.68 8.82 9.11

2011 April 9.74 9.41 9.11

May 9.56 8.72 9.63

June 9.51 8.62 9.32

July 9.36 8.43 9.03

August 9.78 8.99 9.52

September 10 10.06 9.43

October 9.87 9.39 9.36

November 9.46 9.34 8.95

December 7.74 6.49 6.37

2012 January 7.23 5.32 4.92

February 7.56 7.57 6.34

March 7.69 8.65 6.84

April 7.5 10.22 7.84

May 7.55 10.16 7.77

June 7.58 10.05 8.03

July 7.52 9.84 8.61

August 8.01 10.31 9.18

September 8.07 9.14 9.43

October 7.32 9.6 9.85

November 7.24 9.55 10.31

December 7.18 11.77 11.33

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hesitant to follow these recommendations. In 2005, a taskforce has been

formed under the chair of Dr. Abhijeet Sen, member, Planning Commission

recommended updating the base year; increasing the number of

commodities and making changes in weightage given to different

commodities. Such changes would give a higher rate of inflation and thus,

the government is holding back its revision of CPI. The committee had

recommended 2004-05 as the base year. If, we have a glance at the

Table. 1.6 We find that a higher rate of inflation in terms of Consumer Price

Index, for Industrial workers (IW) and Consumer Price Index terms for

Agricultural Laborers (AL), as compared to whole sale price index (CPI).

Same is also exhibited in Figure 1.1

Figure 1.1 Different Price Indices

Obviously there has been a gap between the perception of the

government and that of common man, who is experiencing much greater

retail inflation. While the government has been staring at a lower rate of

inflation in terms of whole sale price index, the common man was

experiencing a sharp rise in the wholesale prices of the food grains,

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especially rice, wheat and pulses, and besides that of vegetables and

fruits. As the common man was experiencing double digit inflation

according to one estimate, about another 10 crore people have been

pushed below the line of poverty due to the impact of recent price

Inflation.

Objective

Keeping in view the significance of the effect of inflation and income

distribution on economic growth the following objectives of the study are

stated below;

1. To investigate the problem of inflation in the Indian economy during pre

and post reform period

2. To provide an alternative framework for the study of Inflation in India.

3. To make an appraisal of different control techniques of inflation adopted in

India to control inflation.

4. To examine the theoretical issues regarding social choice growth and

income distribution.

5. To identify the determinants of income distribution as reflected by Gini

Coefficient.

6. To examine pattern of income distribution.

7. Finally, to examine the relationship among Inflation, Income Distribution

and economic growth in India.

Methodology

The certain useful statistical and econometric technique

have been used in the present study for measuring inflation, Wholesale

Price Index (CPI) and Consumer Price Index (CPI) have been used,

whereas economic growth has been measured by Gross Domestic

Product (GDP). In order To analyze the extent of relationship between

economic growth and inflation and vice versa, the cointegration theory

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and two steps Error Correction Model (ECM) is used. Which was

proposed by Engle-Granger (1987) two-step cointegration approach is

used to check whether the dependent variable is cointegrated with the

dependent variable;

For measuring income distribution, the poverty and inequality have

been analyzed of Indian Experience, for this, data on leading 16 states of

the country have been taken into consideration. These 16 states includes:

Andhra Pradesh, Assam, Bihar, Gujarat, Haryana, J&K, Karnataka, Kerala,

Maharashtra, Madhya Pradesh, Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar

Pradesh and West Bengal. Analysis of poverty and income distribution in

these Indian States have been carried out at four selected points of viz.

1983-84, 1993-94, 2004-05 and 2009-10 . Quintiles, Gini Ratio have been

used as a measure of inequality for the period of 1983-2010. While

Headcount Ratio, has been used to measure poverty, across different

states of India. Multiple Regression analysis and Factor analysis have been

used for the analyses of the problem.

For the analysis of the relationship among Inflation, income

distribution and economic growth, unit root and error- correction model

have been used. The detailed methodology is given in the respective

chapter.

Sources of Data

The study is based on data , published by different departments of

the Government of India, Major data sources are as follows; Economic

Survey, Ministry of Finance, Government of India, New Delhi; Statistical

Abstract of India Central Statistical Organization (CSO), New Delhi;

Handbook of Statistics on Indian economy, Reserve Bank of India (RBI),

Mumbai, World Development Report, World Bank and various Reports of

the National Council of Applied Economic Research, New Delhi, besides

reports from the media both print and electronic have also been taken into

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consideration wherever deemed appropriate. The discussions/

deliberations by the eminent economists have been considered.

Organization of the Study

The whole dissertation is arranged in nine chapters, which are broadly

classified into three parts. The Part-A consists of five chapters, Part-B

constitutes the three chapters, and the last chapter constitutes the Part-C.

An outline of the study and highlighting status of Inflation, income

distribution and economic growth have been described in introductory

chapter, while second to fifth chapters are devoted to theoretical

assessment, measurement, statistical analysis, and policy measures related

to Inflation and Economic Growth. Moreover, chapter six reviews the

literature, Data and Methodology related to economic growth and

income distribution. The seventh chapter studies the pattern and

determinants of inequality and poverty across sixteen major states of India,

similarly, chapter eight discusses the policy implications on the concerned

issue. Finally, efforts have been made to reach the conclusion through

ninth chapter by statistically analyzing the relationship among inflation,

income distribution and economic growth along with the required

suggestions.

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CHAPTER – II

Inflation and Economic Growth

Inflation plays a key role in economic growth of a country. In the brief

introduction, it is revealed that Inflation became detrimental with the arrival

of Paper money. The economist around the globe propounded their

respective theories dealing with Inflation and economic growth. A

relational significance between the Inflation and Economic Growth

especially in a developing economy like India needs further deliberation.

Accordingly, this chapter is being deliberated and analyzed in three

distinct sub-heads in a manner as follows:

Inflation and Economic Growth: Literature Survey

Like many countries, industrialized and emerging economies, one of the

most fundamental objectives of macroeconomic policies in India is to

sustain high economic growth together with low inflation. Not surprisingly,

there has been considerable debate on the existence and nature of the

inflation and growth relationship. Some consensus exists, suggesting that

macroeconomic stability, specifically defined as low inflation, is positively

related to economic growth.

Macroeconomists, central bankers and policymakers have often

emphasized the costs associated with high and variable inflation. Inflation

imposes negative externalities on the economy when it interferes with an

economy‘s efficiency. Examples of these inefficiencies are not hard to find,

at least at the theoretical level.

Inflation can lead to uncertainty about the future profitability of investment

projects (especially when high inflation is also associated with increased

price variability). This leads to more conservative investment strategies

than would otherwise be the case, ultimately leading to lower levels of

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investment and economic growth. Inflation may also reduce a country‘s

international competitiveness, by making its exports relatively more

expensive, thus impacting on the balance of payments. Moreover,

inflation can interact with the tax system to distort borrowing and lending

decisions. Firms may have to devote more resources to dealing with the

effects of inflation (for example, more vigilant monitoring of their

competitors‘ prices to see if any increases are part of a general inflationary

trend in the economy or due to more industry specific causes). Having

stated the theoretical possibilities, if inflation is indeed detrimental to

economic activity and growth, then how low inflation should be. The

answer to this question, obviously depends on the nature and structure of

the economy, and will vary from country to country. Numerous studies

with several theories have been carried out, which specifically aimed at

examining the relationship between inflation and growth. These empirical

studies have attempted to examine whether the relationship between

inflation and long-run growth is linear; non-linear; casual or non-existent.

Economic theories reach a variety of conclusions about the

responsiveness of output growth to inflation. Theories are useful, as they

account for some observed phenomenon. Historically, in the absence of

what is termed ‗persistent inflation‘, the early inflation-growth theories were

built on cyclical observations. Persistent inflation is regarded as a post

World War II phenomenon. Before then, bouts of inflation were followed by

bouts of deflation. Having showed no upward or downward trend, inflation

was said to behave like a ‗lazy dog‘. It stays at a particular level unless and

until there is a disturbance. Thereafter, it moves to another level, at which it

settles. Theory, therefore sought to account for a positive correlation

between inflation and growth.

The aggregate supply-aggregate demand (AS-AD) framework also

postulated a positive relationship between inflation and growth where, as

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growth increased, so did inflation. In the 1970s, however, the concept of

stagflation gained prominence, and the validity of the positive relationship

was questioned. Widely accepted at that time, the Phillips Curve

relationship had appeared to not hold. This was evidenced by periods of

low or negative output growth, and inflation rates that were historically

high. During this period, prices rose sharply, while the economies around

the world experienced massive unemployment. There are some theories,

with their respective contribution to the inflation-growth relationship are

discussed below;

Classical Growth Theory

Classical theorists laid the foundation for a number of growth theories. The

foundation for Classical growth model was laid by Adam Smith who

posited a

supply side driven model of growth and his production function was as

follows:

Y = f (L, K, T)

Where Y is output, L is labor, K is capital and T is land, so output was related

to labour, capital and land inputs. Consequently, output growth Y was

driven by population growth (gL), investment (g K) and land growth (gT)

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Smith argued that growth was self-reinforcing as it exhibited increasing

returns to scale. Moreover, he viewed savings as a creator of investment

and hence growth, therefore, he saw income distribution as being one

of the most important determinants of how fast (or slow) a nation would

grow. He also posited that profits decline – not because of decreasing

marginal productivity, but rather because the competition of capitalists

for workers will bid wages up.

The link between the change in inflations , and its ―tax‖ effects on profit

levels and output were not specifically articulated in classical growth

theories. However, the relationship between the two variables is

implicitly suggested to be negative, as indicated by the reduction in

firms‘ profit levels through higher wage costs.

Keynesian Theory

The Traditional Keynesian model comprises of the Aggregate

Demand (AD) and Aggregate Supply (AS) curves, which aptly illustrates

the inflation – growth relationship. According to this model, in the short-

run, the (AS) curve is upward sloping rather than vertical, which is its

critical feature. If the AS curve is vertical, changes on the demand

side of the economy affect only prices. However, if it is upward sloping,

changes in AD affect both price and output, (Dornbusch, et al, 1996).

This holds with the fact that many factors drive the inflation rate and the

level of output in the short-run. These include changes in: expectations;

labor force; prices of other factors of production, fiscal and/or monetary

policy. In moving from the short-run to the hypothetical long-run, the

above-mentioned factors, and its ‗shock‘ on the ‗steady state‘ of the

relationship between output and inflation, illustrated by the movement

from point E0 to E1 in Figure 2.1, usually happens due to the ‗time-

inconsistency problem‘. According to this concept, producers feel

economy is assumed to balance out. In this ‗steady state‘ situation,

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‗nothing is changing‘, as the name suggests. The ‗dynamic adjustment‘

of the short-run AD and AS curves yields an ‗adjustment path4‘ which

exhibits an initial positive relationship between inflation and growth,

however, turns negative towards the latter part of the adjustment path.

The initial positive that only the prices of their products have increased

while the other producers are operating at the same inflation. However

in reality, overall prices have risen. Thus, the producer continues to

produce more and output continues to rise. Blanchard and Kiyotaki

(1987) also believe that the positive relationship can be due to

agreements by some firms to supply goods at a later date at an agreed

price. Therefore, even if the prices of goods in the economy have

increased, output would not decline, as the producer has to fulfil the

demand of the consumer with whom the agreement was made.

Fig. 2.1 Aggregate Demand and Aggregate Supply

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Two further features of the adjustment process are also important to

note. Firstly, there are times when the output decreases and the

inflation rate increases, for example, between E2 and E3. This negative

relationship between inflation and growth is important, as it quite often

occurs in practice, as ascertained by empirical literature. This

phenomenon is stagflation, when inflation rises as output falls or remains

stable. Secondly, the economy does not move directly to a higher

inflation rate, but follows a transitional path where inflation rises then

falls.

Under this model, there is a short-run trade-off between output and the

change in inflation, but no permanent trade-off between output and

inflation. For inflation to be held steady at any level, output must equal

the natural rate (Y*). Any level of inflation is sustainable; however, for

inflation to fall there must be a period when output is below the natural

rate.

Money & Monetarism

Monetarism has several essential features, with its focus on the long-run

supply-side properties of the economy as opposed to short-run

dynamics.1 Milton Friedman, who coined the term ―Monetarism‖,

emphasized several key long-run properties of the economy, including

the Quantity Theory of Money and the Neutrality of Money. The

Quantity Theory of Money linked inflation and economic growth by

simply equating the total amount of spending in the economy to the

total amount of money in existence. Friedman proposed that inflation

was the product of an increase in the supply or velocity of money at a

rate greater than the rate of growth in the economy.

Friedman also challenged the concept of the Phillips Curve. His

argument was based on the premise of an economy where the cost of

everything doubles. Individuals have to pay twice as much for goods

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and services, but they don't mind, because their wages are also twice

as large. Individuals anticipate the rate of future inflation and

incorporate its effects into their behavior. As such, employment and

output is not affected.

Economists call this concept the neutrality of money . Neutrality holds

if the equilibrium values of real variables -including the level of GDP - are

independent of the level of the money supply in the long-run.

Super neutrality holds when real variables - including the rate of growth

of GDP - are independent of the rate of growth in the money supply in

the long-run. If inflation worked this way, then it would be harmless. In

reality however, inflation does have real consequences for other

macroeconomic variables. Through its impact on capital accumulation,

investment and exports, inflation can adversely impact a country‘s

growth rate. In summary, Monetarism suggests that in the long-run,

prices are mainly affected by the growth rate in money, while having no

real effect on growth. If the growth in the money supply is higher than

the economic growth rate, inflation will result.

Neo-classical Theory

One of the earliest neo-classical models was postulated by Solow (1956)

and Swan (1956). The model exhibited diminishing returns to labor and

capital separately and constant returns to both factors jointly.

Technological change replaced investment (growth of K) as the primary

sector factor explaining long-term growth, and its level was assumed by

Solow and other growth theorists to be determined exogenously,

that is, independently of all other factors, including inflation (Todaro,

2000). Mundell (1963) was one of the first to articulate a mechanism

relating inflation and output growth separate from the excess demand

for commodities. According to Mundell‘s model, an increase in inflation

or inflation expectations immediately reduces people‘s wealth. This

21

works on the premise that the rate of return on individual‘s real money

balances falls. To accumulate the desired wealth, people save more by

switching to assets, increasing their price, thus driving down the real

interest rate. Greater savings means greater capital accumulation and

thus faster output growth.

The Tobin Effect

Tobin, another neoclassical economist, (1965) developed Mundell‘s

model further by following Solow (1956) and Swan (1956) in making

money a store of value in the economy. Individuals in this model,

substitute current consumption for future consumption by either holding

money or acquiring capital. Under this setup, individuals maintain

precautionary balances, in spite of capital offering a higher rate of

return.

Fig. 2.2 portfolio mechanism Curve

22

The above figure depicts the portfolio mechanism. If the inflation rate

increases from π0 to π1 (π 1 > π0), the return to money falls. According to

Tobin‘s portfolio mechanism, people will substitute away from money, with

its lower return, and move towards capital. In Figure 2, this substitution is

depicted by a shift in the Sk line to Sk‘. The portfolio mechanism results in a

higher steady state capital stock (from K0 to K 1). Tobin‘s framework shows

that a higher inflation rate permanently raises the level of output.

However, the effect on output growth is temporary, occurring during the

transition from steady state capital stock, K0, to the new steady state

capital stock, K1. The impact of inflation can be classed as having a ―lazy

dog effect‖ where it induces greater capital accumulation and higher

growth, only until the return to capital falls. Thereafter higher investment

will cease and only steady state growth will result. Indeed, growth in the

neoclassical economy is ultimately driven by exogenous technological

advancement - upward shifts in the F(k) curve - not by a one- off change

in the inflation rate.

Quite simply, the Tobin effect suggests that inflation causes individuals to

substitute out of money and into interest earning assets, which leads to

greater capital intensity and promotes economic growth. In effect,

inflation exhibits a positive relationship to economic growth. Tobin (1972)

also argued that, because of the downward rigidity of prices (including

wages), the adjustment in relative prices during economic growth could

be better achieved by the upward price movement of some individual

prices.

At this juncture, it is important to discuss the role of money in the

neoclassical economy to appropriately understand subsequent literature.

Sidrauski (1967) proposed the next major development, with his seminal

work on the context of an infinitely-lived representative agent model where

money is ‗Super neutral‘. Super neutrality, as mentioned earlier, holds when

23

real variables, including the growth rate of output, are independent of the

growth rate in the money supply in the long-run. The main result in

Sidrauski‘s economy is that an increase in the inflation rate does not affect

the steady state capital stock. As such, neither output nor economic

growth is affected.

Stockman (1981) developed a model in which an increase in the inflation

rate results in a lower steady state level of output and people‘s welfare

declines. In Stockman‘s model, money is a compliment to capital,

accounting for a negative relationship between the steady-state level of

output and the inflation rate. Stockman‘s insight is prompted by the fact

that firms put up some cash in financing their investment projects.

Sometimes the cash is directly part of the financing package, whereas

other times, banks require compensating balances. Stockman models this

cash investment as a cash-in-advance restriction on both consumption

and capital purchases. Since inflation erodes the purchasing power of

money balances, people reduce their purchases of both cash goods and

capital when the inflation rate rises. Correspondingly, the steady-state

level of output falls in response to an increase in the inflation rate.

The Stockman Effect can also operate through the effects on the labor-

leisure decision. Greenwood and Huffman (1987) develop the basic labor-

leisure mechanism, and Cooley and Hansen (1989) identify the implication

for capital accumulation. In Greenwood and Huffman‘s research, people

hold money to purchase consumption goods and derive utility both from

consumption and leisure. Fiat money6 is used because there is a cash-in-

advance constraint on consumption goods. Greenwood and Huffman

show that the return to labor falls when the inflation rate rises. As such,

people substitute away from consumption to leisure, because the return on

labor falls.

24

Cooley and Hansen (1989) extend the mechanism to consider capital

accumulation. The key assumption is that the marginal product of capital

is positively related to the quantity of labor. Thus, when the quantity of

labor declines in response to a rise in inflation, the return to capital falls and

the steady-state quantities of capital and output decline. Cooley and

Hansen show that the level of output permanently falls as the inflation rate

increases.

This theoretical review demonstrates that models in the neoclassical

framework can yield very different results with regard to inflation and

growth. An increase in inflation can result in higher output (Tobin Effect) or

lower output (Stockman Effect) or no change in output (Sidrauski).

Neo-Keynesian

Neo-Keynesians initially emerged from the ideas of the

Keynesians. One of the major developments under Neo-Keynesianism was

the concept of ‗potential output‘, which at times is referred to as natural

output. This is a level of output where the economy is at its optimal level of

production, given the institutional and natural constraints. This level of

output also corresponds to the natural rate of unemployment, or what is

also referred to as the non-accelerating inflation rate of unemployment

(NAIRU). NAIRU is the unemployment rate at which the inflation rate is

neither rising nor falling. In this particular framework, the ‗built-in inflation

rate is determined endogenously, that is by the normal workings of the

economy. According to this theory, inflation depends on the level of

actual output (GDP) and the natural rate of employment.

Firstly, if GDP exceeds its potential and unemployment is below the natural

rate of unemployment, all else equal, inflation will accelerate as suppliers

increase their prices and built-in inflation worsens. This causes the Phillips

curve to shift in the stagflationary direction; towards greater inflation and

greater unemployment.

25

Secondly, if the GDP falls below its potential level and unemployment is

above the natural rate of unemployment, holding other factors constant,

inflation will decelerate as suppliers attempt to fill excess capacity,

reducing prices and undermining built-in inflation, leading to disinflation.

This causes the Phillips curve to shift in the desired direction, towards less

inflation and less unemployment.

Finally, if GDP is equal to its potential and the unemployment rate is equal

to NAIRU, then the inflation rate will not change, as long as there are no

supply shocks. In the long-run, the Neo Keynesians believe that the Phillips

curve is vertical. That is, the unemployment rate is given and equal to the

natural rate of unemployment, while there are a large number of possible

inflation rates that can prevail at that unemployment rate.

However, one problem with this theory is that, the exact level of potential

output and natural rate of unemployment is generally unknown and tends

to change over time. Inflation also seems to act in an asymmetric way,

rising more quickly than it falls, mainly due to the downward rigidity in

prices.

Endogenous Growth Theory

Endogenous growth theories describe economic growth which is

generated by factors within the production process, for example;

economies of scale, increasing returns or induced technological change;

as opposed to outside (exogenous) factors such as the increases in

population. In endogenous growth theory, the growth rate has depended

on one variable: the rate of return on capital (Gillman, Harris and Matyas,

2002). Variables, like inflation, that decrease that rate of return, which in

turn reduces capital accumulation and decreases the growth rate.

One feature accounts for the foremost difference between the

endogenous growth models and the neo-classical economies. In the neo-

classical economies, the return on capital declines as more capital is

26

accumulated. In the simplest versions of the endogenous growth models,

per capita output continues to increase because the return on capital

does not fall below a positive lower bound. The basic intuition is that only if

the return on capital is sufficiently high, will people be induced to continue

accumulating it. Models of endogenous growth also permit increasing

returns to scale in aggregate productions, and also focus on the role of

externalities in determining the rate of return on capital.

Endogenous Models that explain growth further with human capital,

develop growth theory by implying that the growth rate also depends on

the rate of return to human capital, as well as physical capital. The rate of

return on all forms of capital must be equal in the balanced- growth

equilibrium. A tax on either form of capital induces a lower return. When

such endogenous growth models are set within a monetary exchange

framework, of Lucas (1980), Lucas and Stokey (1987), or McCallum and

Goodfriend (1987), the inflation rate (tax) lowers both the return on all

capital and the growth rate.

A tax on capital income directly reduces the growth rate, while a

tax on human capital would cause labor to leisure substitution that lowers

the rate of return on human capital and can also lower the growth rate.

Some versions of the endogenous growth economies find that the inflation

rate effects on growth are small. Gomme (1993) studied an economy

similar to the one specified by Cooley and Hansen; that is, an inflation rate

increase results in a decline in employment. According to Gomme‘s

research, efficient allocations satisfy the condition that the marginal value

of the last unit of today‘s consumption equals the marginal cost of the last

unit of work. A rise in inflation reduces the marginal value of today‘s last

unit of consumption, thus inducing people to work less. With less labour, the

marginal product of capital is permanently reduced, resulting in a slower

rate of capital accumulation. Gomme found that in this economy,

27

eliminating a moderate inflation rate (for example, 10 percent) results in

only a very small (less than 0.01 percentage point) gain in the growth of

output.

Alternative models examine how inflation might directly affect capital

accumulation and hence output growth. Marquis and Reffert (1995) and

Haslag (1995) specify economies in which capital and money are

complementary goods. Marquis and Reffert examine inflation rate effects

in a Stockman economy: there is a cash-in-advance constraint on capital.

In Haslag‘s research, banks pool small savers but are required to hold

money as deposits to satisfy a reserve requirement. Thus, an inflation rate

increase drives down the return to deposits, resulting in deposits being

accumulated at a slower rate. Since capital is a fraction of deposits,

capital accumulation and output growth are slow. In both the Marquis and

Reffert, and Haslag studies, the inflation rate effects on growth are

substantially greater than those calculated in Gomme.

I. Inflation, Growth and Central Banks: Views on Phenomenon

Traditional economic analysis takes the behavior of monetary

policymakers, as exogenous. Currently, consensus exists on the view that

inflation is a monetary phenomenon, in the sense that there would be no

inflation without sustained increases in the money supply. This leads to the

obvious policy statement that long-run price stability can be achieved by

limiting that rate of money growth to long-run real rate of growth in the

economy. However, monetary authorities across the world have allowed

monetary growth in excess of real growth rates.

The dominant trend in theory and practice of monetary policy over the last

two decades has been its dedication to price stability. Central Banks from

New Zealand to Finland have undertaken this commitment, either by

mandates from their Governments or by exercises of discretion granted to

28

them by their governments. The consequence to dedicating monetary

policy to price stability is the perceived indifference to real

macroeconomic outcomes –unemployment, real GDP and its growth rate.

These are seemingly ignored or drastically subordinated in the priorities of

most central banks. Real outcomes become a policy concern only after

the central bank is confident the objective of price stability is met.

Having stated the primary sector central bank objective, most people

interested in the conduct of monetary policy would acknowledge that

central bank actions can and do affect measures of real economic

activity, especially in the short-run. The two way economic interactions

between monetary policy and economic behavior is a process that

operates over sometime. Some consequences of central bank actions are

permanent, others only transitory. These complex and crudely understood

dynamics present particular difficulties for monetary policymakers,

especially in the face of the short-run inflation and output trade off.

General consensus exists amongst policymakers and central banks that

inflation is indeed harmful to economic growth. Many central banks

around the world are becoming more transparent in their dealings and

operations to instill confidence in the economy that the central bank is

committed to maintaining price stability. Since 1990, when the Reserve

Bank of New Zealand became the first central bank to adopt an inflation

targeting regime, the numbers have steadily increased, with at least 19

other central banks operating under the same regime. The common belief

being that price stability or low inflation would lay the foundation for higher

economic growth.

29

II. Level of Inflation Conducive to Growth

There is a pervasive belief that inflation can be reduced only at

the cost of giving growth, despite evidence to the contrary. A major

determinant of results as seen in other countries is the policy mix and

instruments used to reduce inflation and promote growth. The key to

effective solutions, with minimal negative consequences, not rote

responses. This applies to managing capital inflows, too. India needs to

devise ways to handle large capital inflows that are causing undue

currency appreciation and inflation. One aspect is the long term response

of the structural reforms, to enable efficient conversion of funding to

productive projects, i.e. increasing supply. A second is of appropriate

responses to mitigate short-term pressures, i.e. not automatically raising

interest rates or defending the exchange rate, but taking coordinated

fiscal and monetary action to contain excess liquidity (which might include

possible actions on interest and exchange rates). Nor does credit growth at

30 per cent necessarily deserves clamping down. Pattanaik and

Samataraya (2006) have stressed that the debate on the nature of

relationship between inflation and economic growth is still quite open, but

there is a convergence of views on the adverse impact high inflation on

economic growth. It is widely accepted that low inflation may be

conducive to the growth and employment; and one of the objective of

monetary policy needs to be keep the rate of inflation low. Some hold the

view that the rate of inflation may be zero, others stresses that it must be

positive or at a certain specified level, say 2 or 5 per cent, or in the 2 or 5

per cent or so Central Banks of several countries have been targeting

inflation rates varying between 0 to 4 per cent.

The arguments in favor of zero rate of inflation are stated below;

1. Inflation results in investment income being taxed at it higher nominal

value and not inflation-adjusted real value. Indexing the tax system

30

could remove this distortion, which is a difficult job. The remedy,

therefore, lies in achieving zero rate of inflation.

2. Zero rate of inflation may cause temporary increase in unemployment

or a loss of output in the short- run, but in the long run it insulates the

economy from the disruptive effects of inflation

The arguments in against, zero rate of inflation are stated below;

1. No central bank can make ―a credible commitment to pursuing a

particular monetary policy‖, as it would depend on a coordination with

the fiscal authorities in the long run. For if they do not accommodate by

maintaining the balance in the Government Budget, ―then sooner or

later Central Bank will be forced to monetize of public debt‖, and will

not be able to control inflation in the long run.

2. Zero rate of inflation may involve large real costs in the term of

continuing loss of GDP and rising unemployment rates.

3. An inflation rate of 2 to 3 per cent ―leaves open the possibility of

negative interest rates, which could help to pull an economy out of

depression. With zero inflation, real interest rate cannot be negative:

lenders would be paying borrowers to borrow.‖

4. If the inflation rate is positive, say as low as 2 to 3 per cent, it acts like a

lubricant and helps the process of adjustment of relative prices and

wages. In declining industries, the trade unions may resist a cut in

money wages, and the workers are also prone to resist the cut. The

result may be higher nominal wages and lower employment and

possibly labor unrest.

5. Statistically, the consumer price index of inflation may have an upward

bias for two reasons: it may fail to ―adjust fully for the improvement in

quality‖ ; and the weights used to add the prices of different goods and

services included are often out of the date, which may exaggerate the

rise in the cost of living due to failure to take into account the likely

31

change in the consumption pattern due to consumers switching over to

cheaper substitutes.

The question which arises is: if a zero inflation policy is neither feasible

nor desirable, what is the policy alternative? Is it that containment of

inflation needs to be given up altogether as a policy objective, is it that

inflation rate need to be kept positive but within a certain reasonable

range, say 2 to 5 per cent so as to minimize its disruptive effects and at the

same time take the benefit of its growth and the employment enhancing

effect?

The rate of inflation undoubtly affects economic decision making,

particularly savings and investment decisions which are the main

determinants of growth of GDP and employment. It is also true that high

inflation rate and volatility of inflation may cause distortions in the relative

prices and real interest rates; and also in the nature, volume and pattern of

investment and the consequent growth and distribution of GDP. In such

scenario, it may not be advisable to leave the inflation rate entirely to the

market forces. The Central Government and the Central Bank have to

monitor it and take coordinated measures to contain it with certain limits.

There is no conclusive evidence available regarding any precise

relationship between inflation and growth. During 1955-73, when inflation

was modest, Japan had both the highest average inflation rate (5.8%) and

the strongest growth rate (8.6%). Excluding Japan there is little relationship

between inflation and growth.

In the Indian context The Chakravarty committee [RBI, 1985] first

made a reference to 4 per cent level of inflation, which is regarded as the

first influential fix, on the threshold level of inflation in India.

Rangarajan(1998), introduced the concept of “threshold inflation” to

identify the level of inflation from which the adverse consequences begin

to set in. Rangarajan(1998), regarded 6 per cent of inflation to be the

32

outer tolerance limit. The threshold inflation for India found to be in the

range of 4 to 7 per cent. The appropriate measure of threshold inflation

gives greater flexibility to central bank in pursuing the objectives of growth

and price stability, simultaneously. On the other hand, if expected inflation

is above the threshold level, price stability is given greater relative

importance. It must be noted that in a developing country context, the

adverse impact of inflation on social justice has to be incorporated in any

analysis of inflation. However with structural changes in the economy and

credible anchoring of inflationary expectations at a lower level, the

threshold inflation could also move downwards [Pattanaik and

Samantaraya, 2006].

Dr. Y. V. Reddy calls for national consensus on an acceptable level of

inflation. He stresses upon inflation consensus followed by an explicit

inflation mandate. The RBI‘s annual report of 1993-94, makes a

considerable argument that ―there is need for a national consensus before

prescribing a mandate for central bank. Rapid changes in global scenario,

and rapid integration process with the world economy could be pushing

this optimum level below 6 per cent level. In the average rate of inflation of

3 to 5 per cent, there is a growing consensus of acceptance. This

approach should have, among other things, a vital impact on inflationary

expectations in India. Dr. Reddy also argues that on the need for a

systematic revamping of factors such as base year, coverage and weights

with regard to CPI and CPI. The issue relating to the base year, coverage

and weights must be resolved. A detailed survey of behavior of individual

commodity prices in both CPI segment and CPI segment would help in

analyzing the changes in their behavior in the past.

The permanent component is often called the underlying rate of inflation

or core rate inflation. It is not the current rate of inflation, comprising

transient components, but the future underlying rate of inflation, which

33

must be the concern for monetary policy. Measurement of the underlying

or more rate of inflation, however, does involve some amount of discretion.

Dr. Y. V. Reddy(1999), emphasizes that, ― The economic rationale for

considering the core rate of inflation in the framework of monetary policy

which is governed by the fact that it is this rate, being permanent in nature,

which is fully anticipated by economic agents and hence, incorporated

into their decision making process thereby making it output neutral.

Viewed from another angle, it is the existence of the permanent

component, which imparts downwards rigidity to the measured rate of

inflation in the event of positive supply shock. Therefore it would be

valuable for the economy to ensure that core rate or permanent of

inflation is reduced. The objective of reducing the core rate of inflation as

the prime objective of monetary policy should be viewed against this

perspective‖. ―With complexities in the statistical measurement of inflation,

evolving relationships between money supply and prices, uncertain time-

lags in such relationship, conduct of monetary policy is a challenging task.

On the top of normal growth cycles, our economy is moving towards wide

ranging and deep structural transformation, adjusting simultaneously to

international price pressures. When the headline measure of inflation

indicated pressures, judgments were called for in fine tuning monetary

policy‖. Inflation may cause distortions in relative prices of commodities

resulting in misallocation of resources which may adversely affect growth;

and higher the inflation, greater may be the aberrations. It is usually

expressed that in 1950s and 1960s ―there was relatively stable inverse

relationship between inflation and rate of unemployment.‖ This relationship

is also conferred as ―Phillips‘ curve‖ which proposes ―that the opportunity

cost of low inflation was higher unemployment,‖ which means, that there is

a compliance between inflation and employment- more inflation is

accompanied by less unemployment and vice versa. However such

34

relationship did not hold well in the period of 1970s and 1980s when higher

inflation and unemployment occurred simultaneously caused by supply

shocks, and the reason behind this supply shock was crude oil restraint by

OPEC. Furthermore, it has been observed that Phillips‘ curve relationship

may hold good in the short run but any endeavor to pursue a policy based

on it may result in ever-rising inflation. The inverse relationship between

inflation and unemployment rates represented by a downward sloping

Phillips‘ curve (implying that unemployment surges as the inflation rate

declines) may be valid in the short run when the ―inflationary expectations‖

could be deemed to be invariable. If the prices are rising and the

expectations is that they would increase further, a policy drafted to initiate

higher rate inflation of inflation may result in higher prices or galloping

inflation without necessarily increasing employment.

According to RBI, ―the empirical evidence produced in the second half of

the 1990s suggests that there exists a significant and negative correlation

between high inflation and growth. Inflation volatility is robustly and

negatively correlated with growth variability at high levels of inflation‖ (RBI,

2000-01)

Empirical evidence suggests that there has been a relationship between

inflation and unemployment; and during 1974-1991, countries with low

inflation had lowest job rates. Although the process of reducing inflation

pushed unemployment in some countries, for the period as a whole, low

inflation was not achieved through unemployment: if anything it favored

job creation.

Under the referred context, reference can be made to classicists and Neo-

classicists on one side and Keynes and Post-Keynesians on the other side.

For classical economists capital was considered as an immediate

determinant of growth. At the same, they assumed free competition as

self-adjusting market phenomena negating the problems like secular

35

stagnation. On the other, neo-classicists believed that growth was

harmonious process, whereas the marginalists were different as they seem

to be interested in static theory of resource allocation and pricing instead

of growth. As per the classical doctrine in case people were free to seek

their self-interest, the movement of price system would ensure mobilization

of resources automatically for society‘s satisfaction towards larger interest.

It is also their view that free trade will result in benefit of comparative

advantages. Intervention by the State would impair incentives. The

classical believed that there would be no need for the State to maintain

stable currency and the disturbances, if any, would be automatically

corrected. The learned author Dudley Seers1 speaks about the biggest

blow to the Classical liberalism when he says:

―The biggest blow to the classical liberalism was, of course, the slump of

1930‘s when it was difficult and politically impossible to deny that

government has some responsibility for avoiding large scale

unemployment. Monetary fundamentalism has, therefore, fallen out of

favour. Monetary orthodoxy in classical tradition has been abandoned.‖

It is also gathered that there has been abnormal rise in prices after

World War II all over the globe especially in under-developed countries.

The attention of the economists was drawn towards this, resulting in number

of exercise in the field of theoretical analyses and empirical research in

establishing the relationship between prices and economic growth. For

price mechanism and economic growth a study of selected literature can

be made but as the literature comprise of indefinite number, it is prudent to

adopt literature on selection as well as on random basis. Before that the

world renowned economist came in rescue of the situation and

propounded their economic models. For example Keynesian economics

1 ‗Inflation and Growth : Hearth of the Controversy‘ – In Inflation and Growth in Latin

America by Dudley Seers ,pp 93-94.

36

propounds a mixed economy – predominantly private sector, but with a

large role of government and public sector. It is this model which served

for the economies during later part of great depression, World War II and

post war economic expansion approximately from 1945 to 1973. It is also

seen that the model lost some of its influence following the stagflation of

the 1970s. The emergence of global financial crisis in 2007 has caused a

resurgence in Keynesian thought. In short Keynesian economics is a micro-

economic theory.2

It is also gathered that with the emergence of new classical macro-

economics movement in the late 1960s and early 1970s there has been

criticism of Keynesian theories with the result there emerged new-

Kenynesian economists who sought to base Keynes‘ idea on more rigorous

theoretical foundations including stress on international co-ordination of

Keynesian policies, the need for international economic institutions. In short,

it is commented upon that what the Kenynesian considered the failure of

Classical theory in 1930s, they firmly objected to its main theory –

adjustments in prices would automatically make demand tend to the full

employment level. The new-classical theory supports that the two main

costs that shift demand and supply are labour and money. Though the

distribution of the monetary policy, demand and supply can be adjusted.

Thus seen from all the angles, theories show relation to money, its supply, its

movement and economic growth or otherwise in a way making opening

for survey of literature on the Price Mechanism and Economic Growth.

2 The theory is based on 20th Century British Economist John Maynar Keynes. His theory

argues that private sector decisions sometimes lead to inefficient macroeconomic

outcomes and therefore advocates active policy responses by the public sector,

including monetary policy actions by the Central Bank and the fiscal policy actions by

the government to stabilize output over the business cycle. The former British Prime

Minister Gordon Brown, former President of United States George W.Bush, President of

the United States Barack Obama and other world leaders have used Keynesian

economics through government stimulus program to attempt to assist the economic

state of their countries.

37

Kenneth Boulding and Pritam Singh3 are of the view that the

problem of the relation of the price structure to economic development is

extremely complex. The concept of ‗price set‘ for the purpose and

defining it as ―List of prices of all commodities including factors of

production, as it exists at a moment of time. ‖ However, Ayodhya Singh4

while dealing with the issue observes ―Obviously, it is the sectional and not

the general price movements through which monetary policy influences

the economy.‖

Dr. VKRV Rao5 on the price policy comments that it, ―is equally, if not

more, concerned in movements in relative price levels of important

commodities‖ meaning thereby that the movement in relative prices are

relevant in growth prices as they are indicators of inter-sectoral movement

of economic surplus, composition of demand and supply, conditions of

production and distribution and also facilitate resources in order of priorities

in planning and economy.

Reference can also be made to an article on Price Mechanism6

wherein the author of the article while dealing with the mechanism has

made reference to Adam Smith in a manner as follows:

―Price Mechanism

The Invisible hand – the workings of the price mechanism

Adam Smith, one of the founding fathers of economic famously the

‗invisible hand of the price mechanism‘. He described invisible or hidden

hand of the market operated in a competition through the pursuit of self-

interest to allocate resources in social interest. This remains the central view

3 The Role of Price Structure in Economic Development – American Economic

Review Vol. LII, No.2 May 62, pp 28-38 by, Kenneth Boulding, & Pritam Singh. 4 Sectional Price Movements in India by Ayodhya Singh, Banaras Hindu University

1965, p1. 5 Essays in Economic Development by Dr. VKRV Rao, the then Minister of Commerce

in Smt. Indira Gandhi‘s Cabinet. Published by Asia Publishing House, Bombay, 1964,

p 142 6 http ; // tutor 2u.net/economics/revision-notes/as-markets-price-mechanism.html

38

of all free market economy those who believe in the virtues of a free

market economy without government intervention.

The price mechanism is a term used to describe the means by many

millions of decisions taken each day by consumers and they interact to

determine the allocation of scarce resources competing uses. This is the

essence of economics.

The price mechanism plays three important functions in any market

based economic system…. Firstly, prices perform a signaling

function…..Prices rise and fall to reflect scarcities and

surpluses……Conversely, a rise in the costs of production will induce

suppliers to decrease supply, while consumers to the resulting higher price

by reducing demand for the good or services.‖

In the topic titled as the Determinants of Factors of Price, Segunojoh7

mentions about the price and its importance and says:

―The importance of price in the modern economic system not be

overemphasized. However, to set the right price for any commodity or

service, some parameters or determinants come to play. Among the

determinants of factoring price are:

Tender

Sales by Auction

Haggling etc. and these are discussed below.

Interaction of the forces of Demand and Supply:

In a perfectly competitive market or what is sometimes referred to as a free

market economy, prices are determined by the interaction of the forces of

demand and supply. The determination of prices by the interaction of the

invisible forces of demand and supply is known as the ‗Price Mechanism‘ or

‗Price -system‘

7 http://www.oppapers.com

39

From the laws of demand and supply, it is known that the lower the price

the greater the quantity demanded, while at higher prices less will be

demanded. On the other hand, the higher the price the greater the

quantity supplied. But there will be a price at which the quantity

demanded equals the quantity supplied. This is known as a ‗the

equilibrium price‘ the equilibrium price is the market price for the

commodity.

Changes in demand and supply lead to price changes……‖

In the Research Paper on ‗Ipod Price Building‘8 the learned author while

dealing with Price building Mechanism observed:

―Price-building mechanism is one of the basic economic principles.

Price establishing is also a very interesting topic to explore, as we pay for

some sort of product every day, but not always realize the true cost of the

item we are buying. For any product, there is a basic rule how the price is

being determined after several vital factors are taken into consideration.

The price of the product is made up from a number of characteristics: the

component costs, the labour costs (what it takes to assemble the product),

marketing costs, shipping costs. Marketing costs include raising awareness

of the product and advertising campaigns combined with package

design. Shipping includes all the transportation of the product from the

place it is manufactured, to the company storages and to the retailers

through a complex distribution chain. Taxes are not always included as

regular expenses, as some companies pay taxes based on the volume of

sales, and other based on the revenue gained.‖

On the other, with respect to price movement and inflation in an article9

appearing in ‗India Today‘ titled as ―Inflation eats up returns of Fixed

Deposits‘ the author B.S.Srinivasalu Reddy observes:

8 http://www.oppapers.com 9 India Today Mumbai, February 16 , 2010

40

―Rising prices are not just pinching your pockets, but are also affecting your

incomes, eating into the returns on bank fixed deposits (PDS). The annual

inflation rate based on the Wholesale Price Index (CPI) for January, 2010

released on Monday, shot up to 8.56 percent , much above the interest

rate offered by banks at present. CPIO inflation was at 7.31 percent in

December, 2009.‖

In an article10 available on Inflation and how India calculates this rate it is

quoted therein:

―….India constituted the last CPI series of commodities in 1993-94, but has

not updated it till now that economists argue the index has lost relevance

and cannot be the barometer to calculate inflation.

CPI is supposed to measure impact of prices on business. But India uses it

to measure the impact on consumers. Many commodities not consumed

by consumers get calculated in the Index. And it does not factor in services

which have assumed so much importance in the economy.‖

Dr VKRV Rao 11 lays much stress by saying that price is an important

economic mechanism performing certain functions, and any price policy

should be in this functional context. The learned author also mentions:

―A rigid, stable general level of prices may be as much of a dead

weight on economic growth as a rapidly rising price level.‖

The author further elaborates:

―A rightly conceived price policy for aiding economic development

should, broadly, have both a macro and a micro aspect.‖

Regarding macro policy he comments:

10 SME Times , tradeindia . com ( http: // sometimes.tradeindia.com ) However,

researcher observe that new series has commenced with 2004-05 = 100 and is dealt

hereinafter in this research work. 11 Essays in Economic Development by Dr. VKRV Rao, the then Minister of Commerce

in

Smt. Indira Gandhi‘s Cabinet.

41

―…macro policy in regard to prices operates not through a direct

impact on individual prices but indirectly through its impact on income

creation and income utilization and, therefore, on the two variables

determine the monetary framework from all changes in prices.‖

Support to the aforesaid view can be gathered from an article wherein the

writer Swaroop Rout 12 observes:

―Constantly rising prices are like a fire feeding on itself. As they

erode the incomes of wage-earners, they give rise to labour unrest. That in

turn brings down productivity leading to further increase in prices. Thus,

they establish a vicious circle which it becomes problematic to break. As

the costs of production mount, all schemes of planned economic

development go out of the window and national economy is overtaken by

chaos and thrown out of gear.‖

In India‘s case price rise and rising profits have also been dealt though

partly connected with the present work but it is prudent to quote analysis13

wherein issue is raised whether the periods of price inflation coincided with

periods of rising profits. The author Madhavan observes data do not

conclusively support the thesis that periods of rising profits are necessarily

also periods of rising prices. The issue one side has no relevance with

respect to the price movement and economic development. On the

other his work is confined to price-inflation and rising profit and that too

with respect to economy before 1962. Much water has flowed since then.

U.Tun Wai14 in his inductive case study of underdeveloped countries

says that ―…for the most of the small number of individual countries for

which the available statistics cover periods in which the rates of price

12 An Essay on the Problem of Rising Prices‖ by Swaroop Rout available at

http://www.rajputbrotherhood.com 13 Inflation and Economic Development: A case Study in India by Madhavan

published

in the Indian Economic Journal , January 1963, pp 261-263. 14 The Relation between Inflation and Economic Development-A Statistical Inductive

Study by U.Tun Wai , IMF Staff Papers, Volume 7, 1959-69, p 302.

42

increase differ significantly, the evidence suggests, that the rate of growth

was higher when the rate of inflation was lower.‖

There are also debates regarding inflation vs. stability coupled with growth

etc. In his research work Werner Baer15 observes:

―under certain circumstances which are close to the situation of many

underdeveloped countries, inflation is inevitable and beneficial up to a

certain limit‘ and, therefore, suggested that policy makers of national

governments and international organizations should not unnecessarily talk

in terms of inflation vs. stability but rather in terms of ‗warranted vs.

unwarranted rates of inflation‖.

Regarding price system in economics including Fixed price versus free price

systems with inputs on history thereto, it is observed16:

―In economics, a price system is any economic system that effects its

distribution of goods and services with prices and employing any form of

money or debt tokens. Except for possible remote and primitive

communities, all modern societies use price systems to allocate resources.

However, price systems are not used for all resource allocation decision

today…A price system may be either a fixed price system where prices are

set by a government or it may be a free price system where prices are left

to float freely as determined b y unregulated supply and demand. Or it

may be a combination of both with a mixed price

system.……Fundamentally, price systems have been around as long as

there has been trade or money…From its beginnings, the price system has

evolved into the system of global capitalism that is present in the early 21st

century. The Soviet Union and other communist nations with a centralized

planned economy were controlled price systems. Whether the ruble or the

15 Inflation and Economic Growth: An Interpretation of Brazilian Case by Werner Baer

,

EDCC Vol. II October 1966, p 87. 16 ‗Price System‘ including Fixed price versus free price system as appearing in nttp:

/en. Wikipedia . org/wiki/price system

43

dollar is used in the economic system, the criteria of a price system is the

use of money as an arbiter and usual final arbiter of whether a thing is

done or not. In other words, few things are done without consideration for

the costs and the potential making of a profit in a price system.‖

Friedrich A.Hayek 17an Austrian economist while dealing with Price

mechanism has observed that, a free price system allowed economic

coordination via the price signals, that changing prices sent, which is

regarded as one of his most significant and influential contributions to

economies . Regarding economic development it is observed18 that the

economic development is:

―A sustained, secular improvement in material well-being which we

may consider to be reflected in an increasing flow of goods and services.‖

R.L. Meier19 while dealing with economic development defines it as

follows:

―as the process whereby the real per capital income of a country

increases over a long period of time subject to stipulations that the number

of people below an ‗absolute poverty line‘ does not increase, and that the

distribution of income does not become more unequal.‖

In the words of J.R.Hicks20 ―So long as the convexity assumptions hold the

price mechanism is something that is inherent. It does not have to be

invented or brought from outside. It belongs.‖

On the price movement and inflation in an article published in Inclusion21

references have been made to the growth and inflation rather on the

17

Friedrich A.Hayek an Austrian born winner of Nobel Memorial Prize in economics in

1974 known for his defense of classical liberalism and free-market capitalism

against socialist and collectivist thought. He spent most of his academic life at the

London School of Economics, the University of Chicago & University of Freiburg.

(en.wikipedia.org/wiki/friedrich_Hayek) 18 Studies in Economic Development by Okun and Richardson 19 Development Planning by R.L. Meier 20 Sir John Richard Hicks one of the most important and influential British economist of

the 20th century. One of the recipients of Nobel Prize in economic sciences in 1972. 21

Inclusion, July-September 2010 Vol.1 Issue 2, Pp 81-82.

44

quantum of growth with equal quantum of inflation. In its issue of July–

September 2010 it is observed:

―I would posit that zero growth with zero inflation is preferable to 10%

growth with 10% inflation. This view will no doubt be hotly contested. For

instance Dr. Majumdar, an arch critic of the entire process of Financial

liberalization, argues that he would prefer any rate of inflation so long as

employment increases. This is not a matter for debate among ivory tower

economists. In the real world, it is the inarticulate weaker section‘s which

are being devastated by inflation.‖

Goldberg and Pavcnik22 on the strength of empirical research as to how

globalization has affected income equality in developing countries

observes as follows:

―…….While trade liberalization exposes domestic consumers and producers

to the volatility of world prices, at the same time the exposure to foreign

markets mitigates the effects of potentially large domestic shocks on

prices….‖

Regarding Indian economy, Umesh Gulati while dealing with the issue

observed in his paper ‗Working of the Price Mechanism in India‘ that India‘s

economy resembles more a capital economy than a socialist economy.

According to the learned author 23:

―The existing Indian economy resembles more a typical capitalist

economy than a socialist economy. For the bulk of the productive

activity in India is carried on by private individuals and joint stock

corporations. The productive enterprises owned by the government

account for about 7 percent of the net domestic product. However, the

22 Journal of Economic Literature Vol.XLV (March 2007),pp.39-82 regarding

‗Distributional Effects of Globalization in Developing Countries‘ reference at p 71,

by Pinelopi Koujianou Golderg and Nina Pavcnik of Yale University. 23 ‗Working of the Price Mechanism in India‘ a paper by Umesh Gulati; East Carolina University

acknowledging suggestions by Professor Leland B. Yeager.

45

government of India, acting through its planning commission, sets targets

by sectors for various macro-economic variables such as national income,

investment and savings. Besides, there is an all pervasive social goal of

establishing an egalitarian society in India. One of the interesting aspects

of Indian planning is the administrative machinery which is devised for the

allocation of resources to achieve the economic and social goals.‖

The aforesaid data derived from various sources and deliberation thereto

reveals that the prices move and have a movement from time to time. The

movements of prices have a definite relation with respect to particular

economy whether under-developed, developing or developed thereto.

But what is seen is that the movement ought to be uniform and not absurd

or uneven. A gradual or slow price-rise where there are competitive

products is preferable than the abrupt jump in the prices. The price policy

should concentrate towards proper savings/investment, capital formation

besides production and distribution thereto. Any unwarranted push or jerk

in price creates innumerable problem in an economy and may be

considered as symptom of a disease or a disease itself in economic set-up

which requires policy treatment including proper address by triggering

fiscal or monetary reform. The need is for establishment of an absolute and

relative price conditions to promote economic development through rising

level of income including savings and investment thereto. At this point

after glancing on the relevant literature, and assessing the same for price

movement and economic growth, it is prudent to assess the situation in a

democratic planned economy like that of India.

46

INFLATION AND ECONOMIC GROWTH

CHAPTER - III

MEASURES OF INFLATION

Multiple Inflation Measures

The multiplicity of inflation indices available in India has often been

described as problematic and has been used as an argument for not

adopting a full fledged inflation targeting framework:

“In India, we have one wholesale price index and four consumer price

indices. There are ongoing efforts at a technical level to reduce the

number of consumer price indices, and I believe the technical issues are

not insurmountable. But that still will not give us a single representative in

Inflation rate for an emerging market economy with market imperfections,

diverse geography and 1.2 billion people.”

-Subbarao (2010)

Table3.1 shows that a multiplicity of inflation measures are also found in

other countries.

Table3.1 Indicators Used in Various Economies

Distribution Stage India US UK Italy

Importer

na Import price index PPI-imp PPI-imp

Exporter

na Export price index PPI-exp PPI-exp

Producer na PPI PPI CPI-NIC

Wholesaler

CPI na Na na

CPI-IW CPI-W RPI CPI-FOI

Retailer

CPI-AL CPI-U CPI HICP

CPI-RW C-CPI-U

Deflator PCEPI PCEPI PCEPI PCEPI

Indeed, India does not collate some of the indicators that are available in

other countries. Some careful country descriptions are useful:

47

The United States

In the US, consumer price indexes are available for two population groups:

a CPI for All Urban Consumers (CPI-U) which covers approximately 87

percent of the total population, and a CPI for Urban Wage Earners and

Clerical Workers (CPI-W) which covers 32 percent of the population. The

CPI-U includes expenditures by urban wage earners and clerical workers,

professional, managerial, and technical workers, the self-employed, short-

term workers, the unemployed, retirees and others not in the labor force.

The CPI-W includes prices of only those items that are present in the

consumption basket of workers with hourly wage earning or clerical jobs.1

In addition, there are measures of inflation within regions. While all these

measures exist, the US Federal Reserve Board focuses primarily on the CPI-U

and the Personal Consumption Expenditure deflator.

Italy

In Italy, a number of inflation measures are published monthly, with prices

surveyed at di erent stages of the production and distribution chain. Price

indices referring to different segments of the population are also collated.

There are three indices for consumer prices:

(i) the consumer price index for the whole nation (NIC), based on

population wide household consumption expenditure; (ii) consumer price

index for blue and white-collar worker households (FOI), based on

consumption of households whose reference person is an employee; it is

used for indexing rental contracts and in wage negotiations (iii)

harmonized index of consumer prices (HICP), calculated according to the

EU regulations in force, which is used for the comparison of inflation

between EU member states and as a key indicator for the monetary policy

of the European Central Bank. These three indices differ in terms of the

com-

48

position and weighting of the expenditure basket, while, for the most part,

the underlying price collection survey is the same. Finally, producer prices

(PPI) are surveyed monthly, distinguishing developments on the domestic

and the export market.

The United Kingdom

A similar situation exists in the UK, where the Consumer Price Index (CPI) is

the Government‘s preferred measure of inflation for macroeconomic

policy. The institutional arrangement in the UK involves a central bank that

targets inflation, while the Treasury specifies which index should be used

and what rate should be targeted. The UK Treasury has instructed the Bank

of England to deliver 2% inflation as measured by the CPI. In contrast, the

UK Retail Prices Index (RPI) is a general purpose indicator of inflation and its

uses include indexation of pensions, benefits and index-linked gilts. A

variant of the RPI is the RPI-X which excludes mortgage payments, but

includes other components of housing

costs (housing depreciation, council tax, dwellings insurance, ground rent,

estate agents fees, surveyors costs and conveyance fees). The Producer

Price Index (PPI) is a monthly survey that measures the price changes of

goods bought and sold by UK manufacturers. The survey collects

information to develop the output price index, sometimes referred to as

factory gate prices, which measures prices of goo ds sold by UK

manufacturers. Furthermore, it also collects information for the Input index

which measures the prices of materials and fuel purchased by

manufacturers. In addition, there are a number of export and import price

indices available. Finally, the Services Producer Price Index (SPPI) is a

quarterly survey of prices charged for services provided by UK businesses to

other UK businesses and government.2

These examples illustrate the point that in all countries, multiple price

measures exist and have a useful role. At the same time, the presence of

49

multiple measures does not undermine the conduct of macroeconomic

policy. On the issue of a large and diverse population also, India is not

unique. As an example, the US has substantial domestic heterogeneity,

with greater income inequality than is found in India. This has not

undermined the notion of an overall average measure of inflation. A more

striking counter-example is that of the European Central Bank (ECB), which

has the mandate of delivering price stability for a group of 14 countries

with a population adding up to 320million featuring substantial regional

diversity.

While these differences may be present, there is still much value in viewing

an overall average measure of inflation as one of the key summary

statistics of macroeconomic conditions. Since macroeconomic policy is

about aggregative policy instruments which influence every household, it is

appropriate that it respond to aggregative information measures which

average across all households. In a nutshell, we conclude that other

countries too have many price indices, but this does not deter them from

choosing one or the other measure of inflation for macroeconomic policy

making. This motivates a careful examination of the price indices available

in India with the aim of choosing one.

Issues in Choice of Inflation Measures

In most countries, the Consumer Price Index is the most widely understood

and recognized measure of inflation. It is available relatively frequently,

and it is typically not subject to revisions. The overall CPI is meant to

represent the cost of a representative basket of goods and services

consumed by an average urban/rural household. In most countries, a

‗Producer Price Index‘ (PPI) is also reported. While PPIs record the price

change from the perspective of the seller, CPIs measure price change from

the purchaser‘s perspective. Sellers‘ and purchasers‘ prices differ due to

government subsidies, sales and excise taxes, and distribution costs. This

50

distinction, used internationally, between the PPI and the CPI is

considerably unlike the Indian distinction between the CPI and the CPI.

Inflation Measures in India

In India, the RBI has historically focused on developments in the Wholesale

Price Index. This is visible in the much greater depth of analysis dedicated

to the CPI in the Central Bank communication. Consumer prices are

referred to when significant departures from the dynamics of the CPI

emerge, as happened since early 2009 (RBI, 2009-10).

In order to choose a measure of inflation that monetary policy will focus on,

three issues need to be addressed:

1. The choice of a reference population is the first challenge. In any

country, no one price index will measure the impact of price changes

on the entire population (be it consumers or producers). Thus a target

population needs to be chosen. Ideally the price index for this

population should not move very differently from those of others.

2. The weights in the index need to be chosen. This distribution should be

as close to the present consumption basket of the target population

as possible.

3. Prices that go into the indicator should be measured properly,

effectively reflect the consumption basket and the data should be

timely and reliable.

1. Wholesale price index

India is one of the few countries where the CPI is considered as the

headline inflation measure by the Central Bank. This preference over the

CPI is often explained in terms of three criteria: national coverage,

timeliness of release (now only limited to food pro ducts) and its availability

in very disaggregate format (Mohanty, 2010). Of these criteria only the last

one is uncontroversial:

51

CPI numbers are not released to the public in the detail available for the

CPI. This however does not appear to be an insurmountable problem to

address, as the detailed data is collected, but it is just not made public with

sufficient timeliness.

Significance of Wholesale Price Index (CPI)

In a dynamic world prices do not remain constant. Inflation rate calculated

on the basis of the movement of the Wholesale price Index (CPI) is an

important measure to monitor the dynamic movement of prices. As CPI

captures price movement in a comprehensive way it is widely used by

Government, banks, industry and business circles. Significant monetary and

fiscal policy changes are often linked to CPI movements. Similarly, CPI

movement serves as an important determinant, in formulation of trade,

fiscal and other economic policies by the Government of India. The CPI

indices are also used for the purpose of escalation clause in the supply of

raw materials, machinery and construction work. The Office of the

Economic Advisor in the Department of Industrial Policy and Promotion,

ministry of commerce & Industry is responsible for compiling CPI and

releasing it. The Office published for the first time, the index number of

wholesale prices, with ‗base week‘ ended August 19, 1939 = 100, from the

week commencing January 10, 1942. Since 1947 the index is being

published regularly.

Need for a Periodic Revision in the Base Year of CPI

Periodic Revision, in the base year of CPI was needed, firstly, Due to

Structural changes in economies over a period of time, products and their

specifications, both in terms of quality and packaging, are changing even

faster. It has, therefore, become increasingly difficult to obtain the price

information of selected products for a fixed number of quotations over

longer period of time. Also, a number of products which were very

important in terms of the market share at one point of time become

52

obsolete in the short span of time and their places get occupied by

altogether different items. Secondly, due an implicit disadvantage of

Laspeyre‘s formula the methodology used for compiling the CPI, is that the

indices with fixed weighting diagram fail to capture the dynamic changes

in the product mix and structure of the economy over time. It has,

therefore, recommendations of a working group appointed by the

Government, roughly once every decade. Ever since the introduction of

the CPI on a regular basis, Six revisions have taken place introducing the

new base years, viz., 1948-49, 1952-53, 1961-62, 1970-71, 1981-82 and 1993-

94.

Brief History of Wholesale Price Index in India

The Office of Economic Advisor to the Government of India undertook to

publish for the first time, an index number of wholesale prices, with base

week ended August 19, 1939 = 100, from week commencing January 10,

1942. The index was calculated as the geometric mean of the price

relatives of 23 commodities classified into four groups: (1) Food & tobacco;

(2) agricultural commodities; (3) raw materials and (4) manufactured

articles. Each item was assigned equal weight and for each item, there

was a single price quotation.

A new ‗food articles‘ index was prepared in 1945 having wider coverage,

with last week of August, 1939 as the base. This index was calculated as a

weighted geometric mean of price relatives, the weights being

proportional to the values of marketable surplus of the various commodities

during 1938 – 39. The base period of the index was subsequently shifted to

the year ending August, 1939. Subsequently , since 1947, this series

included as many as 78 commodities, covering 215 individual quotations,

classified into five groups: (1) Food Articles; (2) Industrial Raw Materials; (3)

Semi – manufactures; (4) Manufactures; (5) Miscellaneous. The index was

53

weighted geometric mean of the price relatives and this series lasted till

March 1956.

The pre–Independence CPI indices naturally represented undivided India

making it necessary to revise the index soon after Independence. In

accordance with the recommendations of the Standing Committee of the

Department of Statisticians, the Economic Adviser‘s Office issued a revised

series of index, with 1952 -53 as the price base and 1948 -49 as weight base,

consisting of 112 commodities, and 555 individual quotations. The

commodities were classified into five groups: (1) Food Articles; (2 Liquor &

Tobacco; (3) Fuel, Power, Light & Lubricants; (4) Industrial Raw Materials;

and (5) Manufactures.

Cereals were covered comprehensively on the basis of the markets

specified by the Agricultural Price Enquiry Committee. The weighted

arithmetic average was adopted in preference to the weighted geometric

mean usedfor the earlier series. This series was issued regularly every week

from April, 1956 to September, 1969.

While 1952- 53 series (with 1948- 49 weight base) comprehensively

covered Agricultural commodities, the coverage of non- agricultural

commodities was becoming increasingly inadequate. With a view to

removing this deficiency, the Government of India constituted a

committee for improving the coverage and mode of collection of price

quotations of non- agricultural commodities. On the basis of the

recommendations made by this committee, a new series of index

num beers of wholesale prices with base 1961- 62 = 100 was issued

from Jul y, 1969. This series Lasted till December, 1976. It covered 139

commodities and 774 quotations. In the matter of commodity

classification the Standard International Trade Classification (SITC) with

slight alterations made to fit in with the Indian conditions was follow

ed. Accordingly, commodities were classified into seven groups : (1)

54

Food Articles; (2)Liquor & Tobacco; (3) Fuel, Power , Light and

Lubricants; (4) Industrial Raw Materials; (5) Chemicals; (6) Machinery &

Transport Equipment and (7) Manufactures.

While introducing the series with base 1961- 62, it was decided to

constitute a working group t o go into the methodological aspects of

the index relating to the revised series, with a more recent year as

the base. Accordingly, a new series, with the base year as 1970- 71, w

as introduced in January, 1977 on the recommendations of the Working

Group on Revision of Index Numbers of Wholesale Prices. The

coverage of this series w as much wider as it included 360 items

and 1295 price quotations. The selection of items to be included in this

series was based on systematic criteria. As regards the non- agricultural

items, those with a total value of production of more than one crore of

rupees each according to the Annual Survey of Industries, 1965, and

also items whose indigenous outputs were small but imports were

substantial , were generally included, subject to the availability of

price data. In the case of agricultural sector, selection of commodities

was done in consultation with the Directorate of Economics &

Statistics, Ministry of Agriculture. These were significant steps in the

evolution of a scientific method of index number compilation In all the

previous series, the weighting system w as based on the value of

transactions of only those commodities which featured in the index . In

the 1970 - 71series, weights were assigned on the basis of the entire

wholesale transactions in the economy and, for this purpose, the values

of transactions of the non-selected commodities (which did not find

place in the index) were assigned to those selected commodities whose

nature and price trends were similar. This was an important modification in

arriving at a more representative sample of weights for the CPI. Another

improvement introduced was in the system of allocation of weights to the

55

individual commodities. As far as possible, all identifiable items which

were treated as quotations (without a separate weight) in the earlier

series were treated as separate commodities and weights were assigned

to all of them. The weights in this series (base 1970- 71) were based on

the value of transaction consisting of : (a) Value of marketable surplus in

the case of agricultural commodities and value of products for sale in the

case of manufactured products, (b) total value of imports, including

import duties, if any, and (c) total value of excise duty, if applicable .

In the agricultural sector, individual commodities were assigned weights in

proportion to the average value of marketable surplus during the three

year period

ending 1969- 70, worked out on the basis of available data. In the

minerals and fuel, power, light and lubricants groups also, the allocation

of weights to individual commodities was generally based on the

average value of production in the three year period ending 1969- 70.

In the case of Manufactured Products", however, the value of production

based on the ASI- 1968 data was used for deriving the weighting pattern.

In the 1970-71 series, the National Industrial Classification (NIC) was

adopted to bring about a greater uniformity with the classification

followed in some other Important indices like the Index of Agricultural

Production, Index of Industrial Production, etc. In this classification, all the

commodities whether domestically produced or imported and available

for sale in primary markets were grouped under three major groups, viz.,

A: Primary Articles.

B: Fuel, Power, Light & Lubricants, and

C: Manufactured products.

The major group Primary Articles comprised three groups, via, (I) Food

Articles, (ii) Non- Food Articles and (iii) Minerals.

56

The major group Fuel, Power, Light and Lubricants in the 1970-71 series

consisted of coal, coke, lignite, mineral oils and electricity. The major group

Manufactured Products contained eleven groups, via ., (1) Food

Products, (2) Beverages, Tobacco and Tobacco products, (3) Tex tiles,

(4)Paper and paper products, (5) Leather & Leather products, (6)

Rubber and Rubber products, (7) Chemicals and Chemical products, (8)

Non-Metallic Mineral products, (9) Basic Metals, Alloys and Metal

products (10) Machinery and Transport Equipment and (11) Miscellaneous

products.

The Wholesale Price Index Series underwent another restructuring in terms

of its base and weighting diagram from the beginning of 1989. For this

purpose, the choice of the base year was narrowed down to that

between 1978-79 and 1981-82, and the latter year was chosen as the

appropriate base. It was perceived to be so on three major counts viz .,

(a) it was a normal year in terms of price and production data; (b) it was

closer to the actual data period of the 1990s; and, (c) it was close to the

base year of other revised index series commonly in use for economic

decision making. The new series with 1981-82 as the base year continued

the conceptual tradition that has been followed by its predecessors.

However, some significant innovations were made in the attempt to

restructure the series; they also related to the breadth of coverage of

commodities and composition of groups of commodities. As against 360

items in the 1970-71 series, the 1981-82 series included 447 distinct

commodities. The commodity coverage in terms of the total number of

items thus increased by a total of 87. This was the net result of the

addition of 75 new items, the splitting of a group of 32 items of the

earlier series into 100 distinct items and the amalgamation of 4 of the then

existing items into 2 of the new series; in view of the structural changes,

54 items were deleted from the 1970-71 series for the compilation of the

57

new series. The number of price quotations increased from 1295 of the

earlier series to 2371 in the revised series. The new series represented the

underlying economic activity more accurately and adequately,

presumably in a more representative manner. For the preparation of the

weighting diagram, weights were assigned on the basis of the value of

wholesale transactions for the economy. Each selected item was

allocated a weight that is proportional to its share in the total value of

output in the economy. The value of output of the non-selected items was

distributed to those of the selected ones whose nature and price trends

were considered similar.

Within the agricultural sector, individual commodities were assigned

weights on the basis of the average value of marketed/ marketable

surplus through the triennium ending 1981- 82. The 1981-82 series utilized as

an innovation of the marketed surplus ratios pertaining to the base year

as against the marketable surplus ratios based on the surveys conducted

in 1950s and early 1960s for the series it replaced. In addition, the revised

series mostly used the marketed surplus ratios instead of marketable surplus

ratios; the weight of opinion is overwhelmingly in favor of using the first

concept in preference to the second one. For manufactured products,

the value of production as per the ASI, 1980-81 have been used in the

compilation of weights. A distinct improvement in the 1981-82 series was

the inclusion of the value of output of the unorganized/ unregistered

manufacturing sectors for assigning weights to various products. Even

though it is argued that price trends in the two segments of manufacturing

industry tend to move in tandem, the unassigned weights belonging to

the unorganized/ unregistered sector could impart a significant

downward bias to the share of manufacturing output in the total

economy. This possible source of correction has been reflected in the

58

weighting diagram that has ultimately emerged in the 1981- 82 series as

compared with its predecessor.

The manufactured products were classified by the same National Industrial

Classification (NIC) as had been done earlier. This had facilitated an

undisturbed comparison with the past while moving commodities and

groups of commodities to the appropriate class where such a move was

warranted. Overall, the complete list of 447 commodities of the 1981- 82

base was split into three major sectors of the economy: (I) Primary Articles;

(II) Fuel, Power, Light and Lubricants; and, (III) Manufactured Products. The

Primary Articles sector was further split into (i) Food Articles (ii) Non- food

Articles and (iii) Minerals. The Manufactured Products sector has been

sub-divided into 13 sectors, two more in number than in the preceding

series. These w ere (1) Food products; (2) Beverages, tobacco and

tobacco products; (3) Textiles; (4) Food and food products; (5) Paper

and paper products; (6) Leather and leather products; (7) Rubber and

rubber products; (8) Chemicals and chemical products; (9) Non- metallic

mineral products; (10) Basic metals, alloys and metal products; (11)

Machinery and machine tools; (12) Transport equipment and parts; and

(13) Other miscellaneous manufacturing industries. In all, there were 334

items in the Manufactured Products list, 20 items in the Fuel, Power, Light

and Lubricants list and 93 items in the primary articles list, altogether

adding up to 447 for the 1981- 82 base.

There was no change in the method of compilation in the 1981-82 series

from what has been followed in the past. It was calculated on the

principle of weighted arithmetic mean and using the Laspeyre's formula,

which has a fixed base-year weighting diagram operative through the

entire life span of the series.

Next revision was made with base year 1993-94 and it came into effect

from April, 2000. The basket has been kept divided into three major sectors

59

of ―primary articles", "fuel, power, light and lubricants‖ and ―manufactured

products". In case of ―manufactured products" the classification that was

used in the 1981-82 series has been retained, but the last category, "other

miscellaneous manufactures" has been dropped due to problems

encountered in representativeness of individual items in its fold, and its

weight has been distributed across other remaining categories of

manufactured products on a pro-rata basis. There are thus 12 categories

of manufactured products in the 1993- 94 series which are identical with

the first 12 categories of the 1981-82 series as listed above. There are

altogether 435 articles/items in the new series, comprising of 98 primary

articles 19 items of ―fuel, power, light and lubricants" and 318

manufactured items.

An important advance made in the 1993-94 series was with respect to the

mode of compilation of the weekly price index. It made a major break

from the traditional manual method by using desktop calculators to the

use of high speed computers with the assistance of the National

Informatics Center (NIC), which developed a comprehensive software

package custom- made for this purpose. This has allowed for considerable

advance in terms of scope, coverage, accuracy and the potential for

further analysis and research on both the price series and a wide variety of

analytical studies based on rich information contained in the time series

data.

Since October 2009, release of CPI has been changed from weekly to

monthly as per decision taken by Cabinet Committee on Economic Affairs

(CCEA). However, CPI for Primary Articles and Fuel & Power is continued to

be released on weekly basis.

60

Need for Revision of Index Numbers of Wholesale Prices in India base

2004-05=100

The series of Wholesale Prices Index with a base year of 1993-94

reflects the structure of economy nearly 15 years ago. In order that the

index adequately reflects the current structure of the economy, a Working

Group for the revision of the index numbers for wholesale prices in India

was constituted on December 26, 2003 under the Chairmanship of Prof.

Abhijit Sen, Member, and Planning Commission. In determining the base

year, the Working Group followed the well established criteria that the

base year chosen should have the desired properties of being a normal

year and a year for which reliable price and other required data available.

The Working Group also considered that the base year should be as recent

a year as possible. Keeping these criteria in view, the Working

Group proposed 2004-05 as the base year for the new series of

Wholesale Price Index. Latest revision of CPI has been done by shifting base

year from 1993-94 to 2004-05. Accordingly CPI of the new series [with

base year 2004- 05] was launched on 14th September, 2010. A

representative commodity basket comprising 676 items has been

selected and weighting diagram has been derived for the new series

consistent with the structure of the economy. The number of quotations

selected for collecting price data for the above items is 5482.A

comparative statement of weights, no of items and number of

quotations between the old series and new series is given for the major

groups in the table below:

61

Table 3.2 Comparative statement of weights, number of items and

number of Quotations (old series and new series)

The above evolution of CPI in India may be summed up in the following

table:3.3

Table 3.3 Evolution of CPI in India

Universe of Wholesale Price Index in the new series (Base 2004-05 = 100):

The concept of wholesale price has hitherto covered the general idea of

capturing all transactions carried out in the domestic market. The weights

of the CPI do not correspond to contribution of the goods concerned

either to value-added or final use. In order to give this idea a more precise

definition, it was decided to define the universe of the wholesale price

index as comprising as far as possible all transactions at first point of bulk

sale in the domestic market.

62

Treatment of export and import:

In the 1993-94 series, the traded value (used for derivation of weighting

diagram) was computed by subtracting exports from the domestic

production and adding imports to the domestic production (Production

+Import-Export). This method of computing the traded value had an

inherent bias since all exports are not necessarily direct exports without

getting traded in the economy. The Working Group on the new series,

therefore, decided that while computing the domestically traded value,

only the direct export from the factories should be excluded. Similarly,

import of goods which reach the factory directly (without being traded in

the economy) should not be added to domestic production.

Method of selection of products in the Manufactured Group:

The manufactured product basket in the 1993-94 series included all such

products with traded value of Rs 120 crore or above. This led to poor

representation of products in some of the product groups. In order to

remove the anomaly in a selection method based on a uniform cut-off

criterion and make the method of selection more representative, the

Working Group, decided to adopt a method, in which each product

group in the manufactured basket gets represented by such number of

items which together cover at least 80 per cent of the traded value at the

group level. The New Series with 2004-05 as the base has 676 items in the

commodity basket.

Treatment of crude oil:

In the 1981-82 series, crude petroleum was included as an independent

item in the mineral group of the major group Primary Articles. However, in

the 1993-94series, the crude petroleum was taken away from the mineral

group as an independent item and its value was apportioned

parametrically among the items in the mineral fuel group of the major

group Fuel and Power. The Analytical Sub-Group of the Working Group for

63

the new series observed that the prices of crude petroleum could now be

collected from the open market which is interlinked with international

market. Further, the existing practice of imputing crude oil weight to

petroleum products leads to an upward bias in ‗Fuel and Power Group

Index‘ apart from the fact that the movement of crude oil prices and the

prices of petroleum products may not be similar due to ―pass-on‘ lag.

Classificatory System and Method of Calculation

The National Industrial Classification (NIC-98) being generally followed in

the current series in respect of manufactured products has been retained

for the revised series also. This has been done with a view to maintaining

continuity and to facilitate linking of the revised series with the current one.

There is no change in the method of compilation of the index in the new

series. It should, in any case, be possible to rearrange the classificatory

system to suit one‘s requirements on the basis of the detailed individual

commodity indices and their weights.

Weighting diagram

The weighting diagram for the new CPI series has been derived on the

basis of Gross Value of Output (GVO).The output values at current prices,

wherever available at appropriate disaggregation, have been obtained

from the National Accounts Statistics (NAS), 2007 published by the Central

Statistical Organization, Ministry of Statistics & Programmed

Implementation. The same have been reallocated and aggregated to

conform to the structure of CPI basket. Specific group-wise approach for

allocation of weights has been as under:

a. Primary Articles: In the case of agricultural and related commodities, the

average value of output for the triennium ending 2005-06 (i.e., 2003-04,

2004-05 and 2005-06) has been derived by using the value of output at

current prices for the relevant years obtained from the National Accounts

Statistics 2007 (Statements -55 & 56). The Marketed Surplus Ratios (MSRs)

64

were supplied by the Sub-Group on Agricultural Commodities, which

computed the MSRs for the agricultural and related commodities for the

base year 2000-01, initially considered by the Working Group. The MSRs as

supplied by the Sub-Group on Agriculture have been used for deriving the

value of marketed output for the agricultural and related commodities for

the base year 2004-05, as it was felt that the MSRs are unlikely to undergo

any significant change within a short span of three to four years.

b. Minerals: Minerals is a group under the major group Primary Articles. The

value of output of minerals other than crude petroleum has been taken

from the National Accounts Statistics, 2007 (Statement -59). Crude

petroleum has also been now been shifted to ‗minerals‘ in the revised

series. The output value of domestically produced crude petroleum has

been taken from the

Indian Bureau of Mines (IBM) and has been added to the value of output

of minerals other than crude to arrive at the total value of output of

minerals in the new CPI basket. The value of imported crude has not been

taken into account while deriving the weighting diagram for the crude

petroleum on the ground that crude is not traded as such in the domestic

market and its derivatives are already included in the basket as

independent items in the major group Fuel and Power.

c. Fuel Minerals (coal, coke and lignite): The value of output for fuel

minerals, i.e. coal, coke and lignite, has been taken from the NAS 2007

(Statement 59). The export and import figures for fuel minerals have been

taken from the Office of the Coal Controller, Calcutta. As in case of

minerals (except crude petroleum), the imported fuel minerals are taken as

traded in the domestic market and the export of such minerals are taken

as direct exports from the mines for estimation of traded value figures for

the fuel minerals.

65

d. Mineral oils: The value of mineral oils as a group as well as item-wise

values of important mineral oils like petrol, diesel, naphtha, LPG, kerosene,

lubricants etc. are not available in NAS 2007. The Ministry of Petroleum has

made available the sales figures of the mineral oils by different oil

companies for the year 2004-05. The Ministry has also provided the import

and export figures for 2004-05 for such items. While computing the traded

value of the items in the mineral oils group, the value of imports have not

been included as the import figures are already included in the sales

figures. It has been taken that the imported mineral oils are traded in the

domestic market. The export of mineral oils has been treated as direct

export for estimation of traded value figures for mineral oils and therefore

subtracted from the sales value of the mineral oils to arrive at the traded

value for mineral oils.

e. Electricity: The quantum and value of output of electricity generated

and as used by different sectors, i.e. agriculture, industry, domestic,

commercial and railways traction in the year 2004-05 was supplied by

Central Electricity Authority (CEA) to the Office of Economic Adviser. The

value of generation of electricity has been used for derivation of weight for

the electricity group and the item level weights have been derived by

distributing parametrically the group level weight amongst different sectors

of use as per the quantum of generated electricity used by these sectors.

f. Manufactured Products: The National Accounts Statistics 2007 provides

the NIC two digit group wise output figures for 2004-05 both for the

registered (Statement 61) and unregistered (Statement 62-a)

manufacturing sector. Necessary adjustments have been done in NIC

group level output figures to arrive at the group level output figures for the

12 product groups of the Manufactured Products major group of the CPI

basket. Adjustments were required in the NAS group level output figures for

a few groups to harmonize it with the CPI manufactured product grouping.

66

The group-wise combined registered and unregistered manufacturing

figures have been adjusted for import and direct export figures to arrive at

the traded value figures in respect of each of the 12 groups. The group

level weights, derived on the basis of respective traded value figures, have

been distributed pro-rata amongst the items covered in the respective

groups, as per the output figures of such items obtained from ASI data /

Office of DCSSI. The weights have been assigned on the basis of entire

wholesale transactions in the economy.

Seasonal Items

There are a number of agricultural commodities, especially, some fruits

and vegetables, which are seasonal in their availability and whose prices

are quoted only during a particular period of the year. Such seasonal items

are handled in the index in a special manner. When a particular seasonal

item disappears from the market and its prices cease to get quoted, the

index for such an item ceases to be compiled and its weight is distributed

over the remaining items within the concerned subgroup on a pro-rata

basis. This system has been in practice in all the previous series and will be

continued in the revised series also with a clear delineation of the specific

period during

which the index of a particular seasonal item will be compiled.

Other Methodological Changes

The series of CPI with base year 1993-94 had included the PDS price

quotations for wheat and rice. The Working Group was of the opinion that

since they did not represent the first point of sale, these may not be

included. In view of this it was decided to include the procurement prices

of paddy and wheat, which in a way represent the first point of sale in the

price quotations for wheat and rice.

67

Method of Calculation

There is no change in the method of compilation of the index in the

revised series. It is calculated on the principle of weighted arithmetic

mean, according to the Lasperyre‘s formula, which has a fixed base-year

weighting diagram operative through the entire life span of the series. The

formula used is: I = S(I i x W i)/ S Wi Where, S represents the summation

operation, I= Index Number of wholesale prices of a sub-

group/group/major group/All commodities Wi= The weight assigned to the

ith item/sub-group/group/major group Ii= Index of the ith item/sub-

group/group/major group Price relatives are calculated as the

percentage ratios, which the current prices bear to those prevailing in the

base period, i.e., by dividing the current price by the base period price

and multiplying the quotient by 100. The commodity index is arrived at as

the simple arithmetic average of the price relatives of all the varieties

included under that commodity. The indices for the sub-

groups/groups/major groups/all commodities are, in turn, worked out as

the weighted arithmetic mean of the indices of the items/sub-

groups/groups/major groups falling under their respective heads.

Provisional Vs. Final Index

The weekly/monthly index of wholesale prices at the time of its initial

Compilation and release is provisional in nature because it does not take

into account some of the price quotations that are received belatedly. In

such cases, the prices of the missing quotations are either repeated or

estimated depending on the nature of the commodity. The provisional

index is made ‗final‘ after a period of eight weeks/two months by which

time almost all the required price quotations are expected to have

become available.

68

Linking Factor

In order to maintain continuity in the time series data on wholesale price

index, it is imperative to provide a linking factor so that the new series, may

be compared with the outgoing one. The Office of the Economic Adviser

have been using the arithmetic conversion method to link the various

prices index series. The linking factor for the three broad groups of

commodities CPI are as follows. However, the detailed individual

commodities indices and their weights are available from 2004-05 onwards.

2. Consumer price index

The overall CPI is meant to represent the cost of a representative basket of

goods and services consumed by an average household. However, in

India, the existing CPIs refer to specific segments of the population (Rural,

Industrial Workers, etc.). shows that all measures of consumer prices

inflation broadly moved together, especially since 2008. The most recent

weighting scheme, as we saw earlier in, is of the CPI Industrial Workers,

based on an NSSO survey. The index is collected from 78 centers. In this

nomenclature, the category ‗Industrial Worker‘ is actually a misnomer and

should perhaps be called manual workers as it includes workers in factories,

mines, plantations, railways, public motor transport undertakings, electricity

generation and distribution establishments as well as ports and docks. It

includes imputed rents, as is done by some CPI measures internationally,

e.g. in the US. Roughly 10% of the index is services, in addition to the rent

component (Labour Bureau, 2009). Furthermore, from the point of view of

monetary policy, one important property of the CPI-IW is that is used as a

reference index for the wage indexation for civil servants. To gauge the

extent of the information delays in the CPI-IW basket, we compare it with

what probably is the most up to date information on Indian households‘

expenditure patterns. This is taken from the CMIE Consumer Pyramids, a

69

dataset drawn from a panel dataset where over 100,000 households are

surveyed each quarter, for a detailed level breakdown. The weight of food

in the Consumer Pyramids dataset is 45%, compared to 46% in the CPI-IW.

The difference between the two baskets is, however, much larger (almost

10 percentage points) when accounting for the fact that imputed rents are

included in the expenditure weights by the CPI-IW, but not in CMIE‘s

measurement of the consumption basket. However, within the food

categories, we find that the distribution of expenditure is not too dissimilar

across the two sets of weights. This improves our confidence in the

weighting scheme of the CPI-IW. The CSO plans to release a new all India

Consumer Price index by early 2011.The weights will be based on the

2004/05 NSSO expenditure survey. These are expected to be closer to the

weights visible in the CMIE household survey. The new index will also

account for imputed rents, as in the current CPI-IW.

Food prices

The biggest contribution to the high CPI inflation of recent years has come

from food prices. This has been a major topic of discussion among policy

makers and the media. In order to explore the accuracy of food price

data, we juxtapose data for food prices from four sources:

1. Ministry of Agriculture (MoA): retail and wholesale prices.

2. CMIE: commodity spot price data produced at a daily

frequency

for the National Commodity Derivatives Exchange (NCDEX).

3. Labour Bureau: price level data underlying the CPI-IW.

4. FCI: Minimum Support Prices (MSP).

The CMIE/NCDEX data is available daily. It provides more timely

information on primary food commodities markets, compared with that

recorded by the CPI data. The use of these prices in the clearing and

settlement processes of the commodity futures market (at NCDEX) gives

70

confidence in data quality. We find serious problems of non-response and

outliers in the MoA data. This data feeds into the CPI for agricultural

products. Similar problems are also found in the Labour Bureau data

(underlying the CPI-IW).

We also find substantial geographical heterogeneity in price levels and

trends. Some discrepancies in price levels are also visible across sources,

but may relate to issues of product variety. Both the MoA wholesale data,

and the Labour Bureau retail data co-moves with the NCDEX data after we

delete outliers and non-responding locations. This suggests that the quality

of the food price data which is one of the largest components of the CPI is

acceptable. As an aside, it is interesting to note the limited extent to which

other price data co-moves with Minimum Support Prices.

Base year

Among the consumer price indices in India, the most recent weights are

from CPI-IW, based on an ad-hoc NSSO survey on expenditure patterns in

2001.The other indices, as seen in Table 6, are fairly outdated. Until August

2010, the CPI which was often used to discuss inflation, had 1993-94 as its

base period. Only in August 2010, a new CPI was released with 2004-05 as

its base period.

Price of services

While services account for half of Indian GDP, and a large share of house-

hold consumption expenditure, there is no price index for output prices in

this sector, neither at the consumer nor at the producer level. The only

price series available for some services prices are those that have always

been routinely collected in the CPI surveys (in particular for the CPI-IW). This

series is not published or easily accessible and the data for various services

prices has not been collated into a single index.

71

The New CPI

The CSO released the new CPI with base year 2010 (Jan-Dec=100) revised

with next round of NSSO consumption expenditure survey on 18 February

this year. Some features of the new CPI series are the following:

(1) The new CPI is disaggregated at the rural and urban level. The all

India CPI is a weighted average of the two. This is in Contrast with the

earlier CPIs that represented specific classes of population (industrial

workers, agricultural laborers‘, rural laborers, etc).

(2) The new series has a better geographical as well as commodity CPI-IW

inflation.

(3) The weights have been derived from the 61st round of the India as the

headline inflation rate. The arguments made in this NSS consumer

expenditure survey (2004-05).

(4) Data for the urban CPI numbers will be collected from 310 towns

(compared to 78 in the current CPI-IW, for all India)

3. GDP Deflator

The GDP deflator is another indicator of inflation, which is often considered

to be broader than the CPI and the CPI. The GDP deflator in most countries

is obtained by using a variety of primary price indices. These are used to

deflate individual components of GDP valued at current prices (either from

the production or the demand side estimates) to obtain volume estimates.

The GDP deflatoris then defined implicitly as the ratio of the estimate at

current prices to the one at constant prices. When this process is followed,

the GDP deflatoris legitimately recognized as a high quality measure of

inflation. Nonetheless, given the delay in publication of national accounts it

is seldom used as a headline indicator of inflation in a real time setting. In

India, some observers have argued in favor of using the GDP deflator as

the reference measure of inflation. While appealing in theory, these

suggestions do not take into account the actual procedures used to

72

estimate this deflator in India. For quarterly accounts, the production

approach GDP estimates are first obtained using proxy indicators of

quantity (e.g. industrial production) and then inflated to current price

estimates. This operation, especially for the most recent quarters, is

performed using the overall CPI series.8 It should not, therefore, come as a

surprise that the dynamics in the deflator closely resembles the ones of CPI,

especially so in the last available quarters, as mentioned in Nadhanael and

Pattnaik (2010). Thus, by construction, the most recent figures on the

quarterly GDP deflator contain little information beyond already visible CPI

and CPI.

4. Secondary (derived) measures of inflation

A representative measure of inflation for the country as a whole and

availability of information on inflation at high frequency with limited time

lag are important for the conduct of monetary policy. A number of

empirical works based on the long-run equilibrium analysis have found that

money supply (M3) and CPI series are cointegrated to a fair extent, thus

providing evidence on the CPI being more amenable to monetary policy

changes (Reddy, 1999). The Report of the Working Group on Money Supply

(1998) also used CPI as inflation measure and found that the nominal

money demand equation showed long-run price elasticity close to unity.

Even though conventionally CPI inflation has been used as the headline

inflation, several limitations have emerged in the recent past that

complicate a realistic assessment of inflation based essentially on CPI. This

underscores the need for a representative measure of inflation for better

articulation of monetary policy with the objective to anchor inflationary

expectations. Since inflation objective has to be pursued by the Reserve

Bank, to avoid any conflict of interest, the primary statistics on inflation

should be generated by another statistical agency.

73

Deseasonalised trend inflation

Apart from the headline inflation, for policy purposes, central banks look at

various secondary (derived) measures of inflation to gauge the underlying

inflationary pressures. One such indicator of inflationary momentum is

annualized month-over-month seasonally adjusted inflation. However, the

use of such indicator for emerging market economies like India has its

limitations because it could be quite volatile (Fig3.1).

Fig3.1.Annualised M-o-M CPI (seasonally adjusted)

Inflation

Core inflation

Another way to analyze inflation data is by looking at ―core inflation,‖

which is generally a chosen measure of inflation that excludes the more

volatile categories like food and energy prices. The main argument here is

that the central bank should effectively be responding to the movements

in permanent component of the price level rather than temporary

74

deviations. There are many variants of core inflation which try to remove

the volatility of price changes by statistical means. These include truncation

of commodities based on standard deviation of price changes, trimmed

mean, median and other filter based smoothing techniques. Various

measures of CPI-based core inflation for the years 2008–09 and 2009–10 are

presented in Table 3.4. It can be seen that the core measures show

significant month to month variations, though the volatility has been lower

compared to the headline measure. Since core inflation is derived from the

headline, it reflects the weaknesses in the primary measure of inflation. A

prerequisite of a good inflation measure is that it is broader in coverage

and the base period is updated frequently reflecting structural changes in

the economy. In Indian context, the derivation of core inflation by

exclusion of food and energy from CPI/CPI discards a substantial portion of

the commodity basket. So the price movement of the remaining

commodities may not be representative of the underlying inflationary

trend. Although these prices have substantial effects on the overall index,

they often are quickly reversed. But the reversal of volatile prices

sometimes is not short-lived. Therefore, determining when to use a core

inflation measure versus an overall inflation measure remains a complex

issue.

75

Table 3.4

Various CPI-based Core Inflation Measures4

(Per

cent)

4 1.5 SD method: This method excludes all those commodities in which percentage price change is more than

mean plus/minus 1.5 standard deviation over mean price change. Trimmed mean: The trimmed mean procedure estimate price change of each

commodities, arrange them inincreasing order, calculate cumulative weight of the series and cut the commodities for which cumulative weightis less

than 8 per cent or greater than 92 per cent.Median: This procedure computes price change for all the commodities, arrange them in ascending order,

calculate cumulative weight of the new series and take the inflation of the first commodity for which cumulativeweight is greater than or equal to 50

per cent.Reweighting: In this method, we compute price change, calculate standard deviation of price change for CPI-All

Commodities as well as each commodities over a period of time, calculate historical standard deviation for each

commodity as the difference between CPI-All Commodities standard deviation and standard deviation of that

commodity. Then, we calculate final weight as the reciprocal of historical standard deviation, multiplied by initial

weight.5 * and ** indicate that the core inflation standard deviation is lower and significantly different from the standard

deviation of headline inflation at 1% and 5% level of significance, respectively.

76

Comparison of common items of CPI and CPI (IW)

Questions have been raised regarding the usefulness and

reliability of CPI for policy making, particularly the monetary policy. A

strong argument against using CPI as the headline inflation in the

country is its non coverage of Service Sector which accounts for more

than 55% of GDP. Though this criticism is valid, by assigning weights on

the basis of output (or turnover) rather than the value addition, to a

significant extent the services implicit in delivery of products are in a

way taken note of. The wholesale prices, implicitly take the mark up

on account of storage, transportation, banking and insurance. The Office

of the Economic Adviser (OEA), Department of Industrial Policy &

Promotion (DIPP) is, however, at an advanced stage of releasing an

index for service sector, namely, ‗Business Service Price Index‘, which

would address the issue of non coverage of service sector in CPI,

once it is incorporated into the CPI framework. Further, since CPI

covers tradable commodities, it is considered to follow the global

commodity prices, which monetary policy could hardly influence,

except through the exchange rate route. Conceptually, CPI and CPI (IW)

can differ on many counts. While CPI does not cover services, the

commodity basket of CPI (IW) includes certain personal services such

as medical care, education, recreation and amusement, transport and

communication and personal care and effects. They can also differ due

to difference in the weighting diagram and also due to the existence

of commodities/items exclusive to one series. Inflation based on CPI

and CPI (IW) began to show a divergence from the beginning of

2008 and questions have been raised on the measurement of inflation

in the country. At aggregate level, CPI-IW and CPI have differed in the

movement of index and inflation.

77

The part of the Chapter makes a generalized attempt to compare

common items of CPI (IW) and CPI. CPI (IW) compiled and released by

Labor Bureau is available only at Group and sub Group levels whereas

CPI, complied and released by the Office of the Economic Adviser

(OEA), Ministry of Commerce & Industry is available at Group, Sub

Group and item levels. For the purpose of this analysis, item level

indices of CPI (IW) were obtained from Labor Bureau.

Common Groups/ sub Groups

1. Cereals & Products, 2. Pulses & Product, 3. Oil & Fats

4. Meat, Fish & Eggs, 5. Milk & Products, 6. Condiments & Spices

7. Vegetables & Fruits, 8. Other Foods,9. Pan, Supari, Tobacco &

Intoxicants

10. Fuel & Light, 11. Clothing, Bedding & Footwear, 12. Transport &

Communication, 13. Personal care & Effects,14. Other Miscellaneous

items

Variation in both the series may arise due to one or more of the following

reasons:

(a) Difference in price

(b) Difference in weights

(c) Difference in methodology for compilation.

(d) Difference in base year.

In order to nullify the effect of difference in the weighting diagram of

the two series, the CPI weights are assigned to the item level indexes of

both series. The methodology y followed for compiling item level index

for CPI (IW) and CPI are different. In CPI (IW), average price of the

quotations for the item is calculated first and price relative of this average

price with the base price is taken which is the index for that item. In

CPI, instead of going for the average price of various quotations of the

item, price relative of each quotation with its base price is calculated first

78

and then, the average of the price relative is calculated, which is the index

for that item. In short, while in CPI average of the price relative is taken

as the index for the item, in CPI, price relative of the average price

of various quotations is taken as the index for the item. Notwithstanding

the differences in

the methodology, there seems to be no significant variation in the index

at item/commodity level. CPI (IW) is available with base year 2001

whereas the base year of CPI is 2004-05. Therefore, normalization of the

series to a common base year (2006=100) was made in order to make the

two series comparable. The Sub Group and Group indexes are

compiled as the weighted average of the items/sub -group following the

standard practice. Monthly index from January, 2006 to December,

2010 is being used for the comparison. Here, aggregated CPI and CPI

(IW) with base year 2006 has been used. Aggregated index for CPI

and CPI (IW) were compiled from the 14 Groups/ Sub Groups listed

above. The graph below gives the movement of CPI (IW) and CPI.

Both series move identically,

Fig.3.2 Movement of CPI (IW) and CPI

79

Conclusion

On a group basis, average monthly build up of prices in CPI-IW has

been higher than CPI, but that difference is just 10 basis points, or

annualized 1.2 percentage points. The CPI-IW build up of inflation has

been higher for all commodity groups except ‗condiments & spices‘. In

case of ‗milk & milk products‘, ‗transport & communication‘, ‗fuel & light‘

and ‗personal care products‘ the CPI and CPI-IW build up of inflation

during the analysis period has remained virtually same.

The comparison of the average inflation during the analysis period

indicate that the mean inflation has been higher for CPI in respect of

‗milk & milk products‘ , ‗condiments & spices‘ and ‗fuel & light‘.

Inflation in both series follows a common pattern across commodity

groups. Pulses, edible oils, other foods and transport groups exhibit greater

relative volatility. The common items between CPI and CPI (IW) carry

approximately 29% weights (in terms of CPI weight) and about 70% (in

terms of CPI (IW) weights). On this basis we may conclude that RBI should

focus on CPI for monetary policy purpose. Major chunk of tradable

goods are covered in the present analysis and RBI‘s monetary policy has

a direct bearing on these goods only (services are less likely to be

affected by rate changes). This study concludes that use of CPI for

monetary policy purpose would bring the desired effects in the long

run. Any deviation between CPI and CPI (IW) are of short term nature

which would get corrected in the long run. Moreover, CPI can be

considered as a precursor for CPI (IW). Considering the frequency of

release, coverage of commodities and the base period not far from the

present, CPI can be considered as giving the most valuable

information for assessing inflationary pressures in the country and the most

effective tool for policy making in India, at present.

80

Chapter IV

Inflation and Economic Growth Trade off in India:

During Pre Reform and Post Reform Period

Detailed Overview

Inflation in the context of India has a historical background and its

movement displays a checkered past. For the purpose of measurement

of Inflation, the prime requirement is existence of Wholesale Price Index.

Especially in India‘s case, such Index is traced back to 1950-1951 as the

base year. But the irony remains that the Government has changed this

base year several times initially from 1950-51 to 1960-61, thereafter from

1970-71 to 1981-82 and again to 1993-94 and lastly to 2004-05. Thus, there is

no permanency with respect to base year for whole sale price index on

one side and on the other the commodities to be taken into consideration

for determining the whole sale index also stand added or subtracted from

time to time. However, two methods are of importance. One adopted

on the basis of wholesale price Index and second made on the strength

of Consumer Price Index. India since 1902 used its wholesale price Index to

calculate and decide inflation rate in the country‘s economy. Though this

being India‘s position for adopting a particular method when most of the

developed and developing countries use ‗Consumer Price Index‘ since

1970 to calculate the form of inflation. The Consumer Price Index is the

official barometer of countries like United States, United Kingdom, Japan,

France, Canada, China and other developing countries.

The periodicity for measuring the inflation is also of essence. In India,

Inflation is calculated on weekly basis on the strength of Whole-sale price

Index which measures the change in the average price level of goods and

81

services in whole-sale market. As it is difficult to find out average change in

prices of all the goods and services traded in the market so for practical

purpose such commodities were identified and fixed at 435 items. But by

now, a new CPI series with 2004-05 base was released on 14th September

201024. A representative Commodity basket comprising 676 items has been

selected. The total number of price quotations has also increased from

1918 in the old series to 5484 in the new series, indicating better

representation of the prices in the wholesale markets. Some of the

important items included in the new series basket are flowers, lemons, and

crude petroleum in primary articles and ice cream, canned meat, palm oil,

readymade / instant food powder, mineral water, computer stationary,

leather products, scooter / motor tyres, polymers, petrochemical

intermediates, granite, marble, gold and silver, construction machinery,

refrigerators, computers, dish antenna, transformers, microwave ovens,

communication equipment (telephone instruments), TV sets, VCD‘s,

washing machines, and auto parts in manufactured products. A

comparison of the weighting diagram and number of commodities

between the old and new series for the major groups is drawn in Table 4.1

hereunder.

TABLE 4.1 Major Changes in the Weights and Commodities in the Revised CPI Series Items Weights No. of Commodities

New

Series(

base:20

04-05)

Old

Series(ba

se: 1993-

94)

New

Series(base:

2004-05)

Old Series(base:

1993-94)

Items

Added/

Revised

All Commodities 100.00 100.00 676 535 417

Primary Articles 20.12 22.03 102 98 11

Food Articles 14.34 15.45 55 54 1

Non-food & Minerals 5.78 6.63 47 44 10

Fuel and Power 14.91 14.23 19 19 0

Manufactured

Products

64.97 63.75 555 318 406

Food products 9.97 11.54 57 41 25

Non-food products 55.00 52.21 498 277 381

Source: The office of the Economic Adviser, Ministry of Commerce and Industry.

24 Economic Survey 2010 -11 page 69/70

82

The graphic presentation regarding major changes in weights on the

strength of 1993-94 and 2004-05 series is presented in Graph 4.1 while major

changes in number of commodities on the basis of referred series is shown

in the figure hereunder marked as Graph 4.2

GRAPH:4.1

0

10

20

30

40

50

60

70

weig

hts

items

Major Changes in Weights

2004-05

1993-94

GRAPH: 4.2

Major Changes in No. of Commodities

0

100

200

300

400

500

600

Prim

ary

Art

icle

s

Food A

rtic

les

Non-f

ood &

Min

era

ls

Fuel a

nd

Pow

er

Manufa

ctu

red

Pro

ducts

Food

pro

ducts

Non-f

ood

pro

ducts

items

Co

mm

od

itie

s

2004-05

1993-94

83

Accordingly, this basket of goods and services is used to get an

indicative figure of the Inflation and change in the prices. Now to avoid

generalization, India‘s economy can be studied in two distinct periods like

Period prior to 1992 (Pre-reform) and the Period after 1992 (Post-Reform).

The Period prior to 1992 can be seen predominant with economic reforms

inspired by socialistic pattern of economy. The economy during this period

faced various challenges including mushroom growth of regulations,

protectionism, public ownership, pervasive corruption, slow growth and like

other measures.

The price index during this period so adopted and determined for a

particular year or a decade, can be inter-alia discussed with various Five

Year Plans. The present chapter considers sixth plan period as pre-reform

period hence all the prior plan periods before sixth plan have ignored or

mentioned only on the light note.

During the 6th and 7th Five Year Plans, one sees that the wholesale

price Index rose by 38 points. On one side, it is seen that there has been a

constant Inflationary pressure generally seen in upward direction except

during 1977-1978 and 1978-1979 when the Inflation was in downward

direction and for some of the commodities it attained the stability. When

compared with the economic development decade after decade from

1950 to 1990, it is seen that there has been overall development in

agriculture, industry, infrastructure, GDP etc.

While the period after 1990 witnessed economic liberalization

coupled with globalization, which moved India‘s economy towards market

based system. The revival of economic reforms and economic policies

from time to time during the referred period accelerated India‘s growth

rate. But position of the Inflation when seen in the beginning of 1990 was

high especially on the subject of food grains and reached between 10 and

14 per cent till the year 1994-95. The inflation touched a double digit in

84

comparison to previous year and years to follow. The Five year average

inflation 25 for the period 1991-92 to 1995-96 is reflected as 10.6 but on point

to point by March end the annual average of five years is arrived at 9.3.

Thereafter, for another five years comprising of period 1996-97 to 2000-01

the five year average inflation rate on the basis of 52 week annual

average is shown as 5.0 but on the strength of point to point by March end

the inflation rate reflected is 5.3, keeping the Inflation rate in view, it

prudent to study the position on yearly basis from 2000-2001. Accordingly,

a tabular position is provided here under:

Table 4.2 Annual Average Inflation Rate based on CPI since 2000-01

(Per cent)

Year Primary

Articles

Fuel &

Power

Manufactured

Products

All Commodities

Weights (%) 20.12 14.91 64.97 100

2000-01 2.8 28.5 3.3 7.2

2001-02 3.6 8.9 1.8 3.6

2002-03 3.3 5.5 2.6 3.4

2003-04 4.3 6.4 5.7 5.5

2004-05 3.7 10.1 6.3 6.5

1st 5 years average 3.5 11.9 3.9 5.2

2005-06 4.3 13.5 2.3 4.3

2006-07 9.6 6.5 5.6 6.5

2007-08 8.3 0.0 4.9 4.8

2008-09 11.0 11.6 6.2 8.0

2009-10 12.7 -2.1 1.8 3.6

2nd 5 year average 9.2 5.9 4.1 5.5

Decadal Average 6.4 8.9 4.0 5.3

2009-10 (Apr-Dec.) 9.8 -5.8 0.7 1.7

2010-11 (Apr-Dec.) P 18.0 12.3 5.3 9.4

Source : The Office of the Economic Adviser, Ministry of Commerce and Industry.

Note: P – Provisional

The referred data as to weights % in the First vertical column of the

table regarding Inflation Rate on the basis of CPI since 2000-01 can be

demonstrated as provided in Graph 4.3 hereunder

25 Economic Survey 2001-2002, p 111, Box 5.1

85

Graph 4.3

20%

15%65%

Annual Average Inflation Rate based on WPI since 2000-01

Primary Articles

Fuel & Power

Manufactured Products

As per economic survey 2010-11 the ten year average of headline

CPI inflation was around 5.3 percent from 2000-01 to 2009-10; in this

decade 2000-01, 2003-04, 2004-05, 2006-07 and 2008-09 had higher inflation

relative to the decadal average. In the current financial year 2010-11,

overall average inflation from April-December 2010 at 9.4 percent is the

highest recorded in the last ten years.

This apart, India‘s economy is reported as 11th largest economy in the

world by nominal GDP and 4th largest by purchasing power parity 26. The

pace of liberalization and globalization opened India‘s doors to world at

large. It is seen that by 2008 India has attained the status as world‘s

second fastest growing major economy but the fact remains that the year

2009 saw slowdown of official GDP growth rate to 6.1% while return of a

large projected fiscal deficit of 6.8 % of GDP which being highest.

India is ranked at 139 in the world on the basis of its per capita

income while it is ranked at 128 on the strength of Purchasing Power Parity.

India currently accounts for US $7.03 trillion World trade as far as first half of

2010 is concerned with a value growth of 24 per cent. According to World

26 Mahendra K. Patidar in his article dated 29th October 2010 on ‗Fundamental Analysis‘

(www.Scribd.com)

86

Trade Organization India accounted for 1.5% in 2007. India‘s total

merchandise trade including Exports and Imports in 2006 stood valued at

$294 billion and its Services trade inclusive of export and import was $143

billion. In comparison to 2004 India‘s global economic engagement on

both merchandise and service trade stood at $253 million which shows an

increase by 72% in comparison to 2006.

On the Industrial front, India‘s large service industry accounts for

62.5% of India‘s GDP when Industrial and Agriculture sector contribute 20%

and 17.5 % respectively. It is also seen that Industrial sector accounts for

14% of the employment while service sector contributes 34% and remaining

52 % is predominated by Agriculture. India‘s large labour force of around

half a billion workers is engaged in various activities. While India‘s major

industries include textile, telecommunications, steel, chemicals, food

processing, transportation, equipment, mining, cement, petroleum,

machinery, information technology etc., India‘s main Agricultural products

include, wheat, rice, cotton, oilseed, tea, jute, sugarcane, potatoes, cattle,

buffalo, sheep, goats, poultry and fish etc.

On the basis of data 27, India‘s position with respect to economic

indicators reveal that in 2000 its Gross Domestic Product in million constant

1995 US $ was 46,682 in comparison to 34,109,900 0f the World and

8,913,075 of Asia (excluding middle East). With respect to its Gross National

Income (ppp, in million current International dollars) , 2ooo same stood at

2,375,398 in comparison to 44,458,520 of the world and 14,332,825 that of

Asia (excluding middle East) with further details thereto are provided in

Appendix A-I. On the issue including inflation at 10.16% in May, 2010 are

also provided in exhaustive table Appendix A–II at last of this Research

work along with summarized statistical figures of the economic growth in a

democratic planned economy like India .

27 Earth Trends 2003, a data base (earthtrends wri.Org/updates/node)

87

In addition, it is also desirable to find out the observations /

projections appearing in print media with respect to price regime and

movement of the prices. The Time of India 28 came out with deliberations

during press conference of IRDA Chairman and is quoted hereunder:

‗A ministered price regime a thing of the past‘ - IRDA chairman Hari

Narayan during press conference expressed :

―We have long moved away from the administered price regime

and it is for the market forces to determine the price of their product.”

India‘s economic position in some sectors at the time of Independence

and now is projected in print media 29. The movement of prices on one

side and growth on other with respect to corresponding years of 1947 and

2010 is appended for the sake of clarity

Table 4.4 India then and Now

Sr.No. Sector 1947 2010

1 Average Life Expectancy 31.4 years 68.0 years

2 Literacy Rate 14 % 68%

3. Gold Price Rs. 88 per 10 gram

(per tola)

Rs.18, 000 per 10

gram

4. Starting salary of I.A.S. Rs.350.00 p.m Rs.25K-26K

5. Defense Budget Rs.93 crores Rs.1,80,000 crores

6. Population 300 million 1,1777 million

7. Water output 5.5 million tones 80.3 million tones

8. Per capital Power

consumption

15.5 Kwh 733 kwh

9. Telephones 1.1 million 672 million

10. Infant mortality rate 145.6 (per 1000 live

births)

53(per 1000 live

births)

11. Doctors 0.5 (per 1,00,000

population)

64 (per 1,00,000

population)

12. National Highways 19,634 KMs 70548 KMs

13. Exports 403.4 crores 8,40,000 crores

14. Imports 408.7 crores 13,70,000 crores

15. Average cost of highest selling

car model

Rs. 350 Rs.2.6 – 4.1 Lac

28 The Time of India Thursday dated 12.8.2010. 29 The Times of India Saturday dated 14.8.2010 :

88

The aforesaid profile at a glance gets support from an Article appearing in

AII India Reporter 30where the Ld. Author quotes a portion of report submitted

before the Supreme Court to the extent that taking base in 1940 at 100/- the

value of rupee in 1996 was only Rs.1.5 in 1996. In 1940 the wholesale price index

was 13.2. This has risen to 876 by 1996 (66 times). Value of one rupee silver coin of

1940 as on 5th December 1992 was Rs.44/- . Price of silver on 30.12.1939 was Rs.52/-

per Kg. It rose to Rs.6, 945/- per Kg on 31.12.1966 that is by 133 times. All the

figures referred clearly show movement in prices.

As per CMIE 31, it is projected that in fiscal year 2010-2011, the real

GDP will grow by 9.2% while Private final consumption expenditure growth

is projected at robust 8.6%. As per the study of the Centre:

―The factor that will contribute to the higher consumption demand include:

1. A rise in the wages and salaries in the organized sector.

2. A change in income tax slabs, which has provided additional

purchasing power to the salaried class.

3. Continuation of employment generation schemes in rural areas.

4. Good rabi crop production in 2009-10.

5. Robust investment activities, and

6. Impressive growth in the service sector.

The ongoing CapEx boom in the country is likely to create fresh

employment and strengthen the growth in construction projects valued at

Rs.6.5 lakh crore are scheduled to get commissioned in 2010-11, the highest

annual capacity addition in Indian industry. More importantly, projects

worth Rs.4 lakh crore are expected to have got commissioned in 2009-10.‖

The Centre expected Industrial production to rise by 9.6 % in 2009-10

and by 9.4 % in 2010-11.The output of this sector which accounts for 79.4 %

of total production, is projected to grow by a smart 9.6 % in 2010-11. The

30

K.J.Dighe, ( June , 2011) ―The value of One Hundred Rupees or Upwards…….‖

AII India Reporter, journal Section, pp 109-112.

31 Centre for Monitoring Indian Economy (CMIE) – India‘s leading business and economic

database and research company http://WWW.cmie.com

89

growth momentum in the demand for goods and services is expected to

continue up till 2010-11. The consumption demand is expected to rise by

8.6% in tendem with the rising purchasing power of the urban, semi-urban

and rural areas or population as a whole. The GDP growth is projected to

accelerate in 2010 and agriculture is expected to contribute in measure to

this growth.

The Inflation as shown hereinbefore coupled with economic

planning and policy of the country has direct bearing on India‘s economic

growth. The upward and downward trend in the Inflation affects the

purchasing power of consumers and has its consequences on other

economic sectors especially industry and agriculture. The constant priority

of economic growth on national agenda has made the economist predict

that India will be among the leading economies of the world by 2020 32.

Recent print media 33 while referring to latest National Security Index (NSI)

designed by country‘s foremost security and economic experts expressed

that India is the 5th most powerful country of the world. In economic

strength, India ranks 7th Out of five criteria maximum weightage was given

to the defence capabilities at 30%. Economic strength, technology and

effective population add weightage of 20% each. Energy, Security had

the remaining 10%. The report also apprehends likelihood of people raising

eyebrows over India‘s extremely high rank. The NSI report says that the

Strategic community in India will still take time to get used to India being

such a powerful country.

II. Inflation and Economic Growth: A Descriptive Analysis

After the end of first year of the Sixth Plan of 1980-81; this

experienced the initial phase of modernization of Indian Economy. The

32 www.thaiscorp.in /contenido_Indian.php? (Economy-Documento sin titulo) 33 The Times of India, Lucknow Wednesday April 13, 2011, p 7 column 1 to 5

90

shares of GDP (at factor cost 1999-2000 prices) which are Primary sector

(Agricultural), Secondary (Manufacturing) and Tertiary (Service) were 41%,

22% and 37% respectively. After Thirty years (1980-2010) of significant efforts

towards reformation, these shares of GDP stood at 21%, 23% and 56% in

2009-10. Therefore, the primary sector sector has reduced to almost halved

since first five year plan, on the other a service sector augmented more

than 50 per cent of GDP share and Secondary has gained marginally.

Which reflects the character of Indian economy as Service sector

dominated economy; as the share of Service sector is almost equal to the

sum of other two sectors.( Table 4.5)

Table 4.5: GDP-Key Drivers & Variances

Primary

Sector

Secondary

Sector

Tertiary

Sector

GDP Growth

Rate

Pre-Reform Average

1981-1992

3.2 5.3 6.3 5.0

Post-Reform

Average 1992-2010

3.4 7.3 8.5 6.8

Combined Average

of Pre & Post Reform

Period1981-2010

3.3 6.3 7.4 6.2

S.D 1981-1992 5.19 3.01 1.29 2.38

S.D 1992-2010 4.02 3.01 1.79 1.88

S.D 1981-2010 4.39 3.10 1.79 2.19

Source: RBI, S.D: Standard Deviation.

Table 4.5 suggests that the real annual GDP growth is 1.79 percentage

points higher in the post-reform period. There is also half a percentage

point reduction in variability of GDP growth. Assuming 1992-93 as post-

reform as well as initial structural reform period, in the immediately

preceding ten years (1981-82 to 1991-92) of reforms and in the post reform

period the growth rates of Primary sector sector were almost unchanged;

3.2 & 3.4 respectively.

91

Whereas, secondary sector, growth rates were; 5.3 &7.3 respectively.

Tertiary sector also witnessed the marginal increase; 6.3 & 8.5 respectively.

The standard deviation represents a distinct scenario. In the pre-reform

period of 1981-92, the standard deviation of annual growth rates in the

primary sector, secondary and tertiary sector were 5.19, 3.01 and 1.29

respectively. But during post-reform period the growth rates of all the three

sectors were 4.02, 3.01 and 1.79 respectively. Which suggests, that there is

substantial reduction, in the growth rate of primary sector sector, during the

post-reform period, although, it was still ahead of remaining two sectors.

The variance depicts that, despite of all reforms processes, there is no

encouraging change in the secondary sector as it was lowest, although in

the latter years it has increased considerably by half a percentage points.

Post-Reform Primary Sector Scenario

The role of the primary sector remains critical to the Indian economy as it

accounts for about 53% of employment in the country (as per 2001

census). Moreover, this sector is a supplier of food, fodder and raw

materials for a vast segment of industry. In fact, India is a strong rural

demand led economy which boosts its growth. However, its share in India‘s

GDP has not been very encouraging. The sector accounted for about 20%

of India‘s GDP in FY05, declining to 16.8% in FY08. Primary Sector in India

met with a major turning point in the 1960s, post the implementation of

what is popularly known as the ‗Green Revolution‘. High agricultural

production and productivity achieved in subsequent years had aided

India in attaining food security to a large extent. However, the country

has not witnessed any big technological breakthrough in primary sector

since then. This is explained by the fact that whereas overall GDP has

grown by an average of 7.3% during the 2000s while primary sector has

posted a modest growth of only 2.4% during the 2000s. However, the

agricultural sector emerged as the key growth driver during FY2010 with a

92

robust year on-year growth of 6.6%. As per the 4th advance estimates,

there was a record food grain production of 218mn tonnes in FY2010,

surpassing the earlier record of 234mn tonnes achieved in FY2009.

Agricultural yield stagnates

The agricultural yield in India has been stagnating and is raising concerns.

The yields of the main food grains as well as commercial crops are seen to

be almost stagnant since FY2000s, and are actually falling FY2008

onwards, much behind the yields of countries throughout the World. The

yield of food grains in India stand at 1798 kg/hectare as on FY10 declining

from 1860 kg/ hectare in FY08 and 1909 kg/ hectare in FY0

Agricultural yield of food-grains and cash-crops

A major reason behind the stagnating yield is the small size of land

holdings in India. More than 80% of agricultural holdings in India are of less

than 2 hectares and more than 60% of farmers operate on less than 1

hectare each. As employment opportunities in the non-farm sectors are

growing very slowly, there is very little shift of labour force from agriculture.

However, improving the viability of smaller holdings by providing access to

technology, inputs and credit has been effectively tackled by the

Government in recent years.

Saving and Investment

Savings has always been one of India‘s strength, with its growth driven by its

three major components namely (i) Household savings, (ii) Private

corporate savings, and (iii) Public sector savings. The gross domestic

savings have exhibited a robust growth path, growing steadily over the

past many years. It has maintained the increasing trend over the past

years, barring FY 2009, following the financial crisis where savings across all

sectors declined. The share of gross domestic savings to GDP has always

been sizable hovering around 35%. Household savings, which has

contributed to about 70% of the total gross domestic savings and about

93

23% of India‘s GDP, has kept the high savings growth momentum going.

Private corporate savings and public sector savings have also shown a

healthy growth over the years and have recovered sharply post the crisis in

FY09. The growth in investments has also been robust over the past many

years. Gross capital formation is contributed by three sources, namely, (I)

Private corporate sector, (ii) Public sector and (iii) Household sector.

The share of gross capital formation in GDP has been robust (barring some

bad years), throughout and has followed the similar trend as that of Gross

Domestic Savings. This is a positive sign as it implies that the savings

generated in the economy are largely being channelized into

productive investments.

Gross capital formation

The share of gross capital formation in the agriculture sector in the total

gross capital formation has varied between 7-9% in the last few years.

However, it may be mentioned that, considering the huge population

dependency on agriculture and its importance as a major supply side

indicator, the share has remained way below the comfortable level. This is

an area which needs to be addressed.

CPI Behavior

In the post-reform period the (monthly) average CPI inflation (2004-05=100)

was almost 1.5 per cent lesser in comparison to pre-reform period. The

trend in the CPI inflation has shown a downward movement since mid of

1990. The variation in the standard deviation of inflation rate nevertheless

stayed almost steady during the pre & post-reform period.

94

Table 4.6 CPI Movement

ALL

COMMODITIES

PRIMARY

SECTOR

ARTICLES

FOOD

ARTICLES

NON-FOOD

ARTICLES

FUEL,POWER

& LIGHT

MANUFACTURED

GOODS

AVERAGE OF

PRE-REFORM

PERIOD

1982-1992

7.6 7.4 8.5 8.5 6.5 6.6

AVERAGE OF

POST-REFORM

PERIOD

1992-2010

6.2 7.0 7.5 7.5 6.1 5.1

OVERALL

AVERAGE

1982-2010

6.6 7.2 7.7 6.8 8.2 5.7

S.D. OF PRE-

REFORM PERIOD

1982-1992

2.7 5.6 6.1 8.7 4.0 3.4

S.D. OF POST-

REFORM PERIOD

1992-2010

2.5 4.1 4.5 7.1 6.7 3.7

OVERALL S.D.

1982-2010

2.8 4.6 5.1 7.6 5.9 3.6

The average of Primary sector Articles of CPI in the pre-reform period was

considerably on the higher side (7.6%) in comparison to the post-reform

(6.2%) period, both the food and non food articles recording much lower

average during the post-reform period. In case of Manufactured goods

too, the average was lower in the post reform period. Whereas, the

variations in the standard deviation of all the sub-groups except fuel,

power & light shown a remarkable increase of more than 2.5 percentage

points which represents the discouraging signs.

95

Table 4.7 CPI Behavior

The average of Rate of change in CPI –IW had been much lower(7.15%) in

the post-reform in comparison to pre-reform(9.04%) per cent. It is hardly

surprising that the cost-of-living of the workers, both in urban and rural areas,

went up so sharply, and that the cost-of-living of agricultural laborers, for

whom food is an even more important item in the consumption basket than

for industrial workers, went up more steeply than for the latter.

Of course, there has been a slackening in the pace of inflation, though this is in

itself in the process of getting reversed. This however is no credit to reform, rather the

contrary. Two factors have been particularly responsible, among others, for the

slackening of the pace of inflation. The first relates to the fact that after February

1994 there was a long pause in raising the administered price of food grains which

indicated that the earlier sharp squeeze on the living standard of the people had

reduced the scope for any further immediate increase in the squeeze.

The rise in prices during the 1990s has been a direct result of this. Since there

has been a curtailment in the growth of public investment and a

CPI-IW CPI- IW(FOOD) UNME CPI-AL

AVERAGE OF PRE-

REFORM PERIOD

1982-1992 9.04 8.93 9.23 8.50

AVERAGE OF POST-

REFORM PERIOD

1992-2010 7.15 7.30 7.20 6.68

COMBINED AVERAGE

1982-2010 7.86 7.92 7.96 7.37

S.D. OF PRE-REFORM

PERIOD 1982-1992 5.52 3.87 2.25 5.20

STDEV OF POST-

REFORM PERIOD 1992-

2010 3.16 4.68 2.87 4.30

S.D. 1982-2010 4.21 4.40 2.80 4.66

96

corresponding curtailment in the pace of growth of demand in the

economy, inflationary pressures should have abated in this period. Instead

we find that inflation actually accelerated in the post-reform period This

acceleration of inflation in a period of `slack' demand was essentially due to

hikes in administered prices which were ordered by the government in order

to curtail its subsidy bill, and thereby the fiscal deficit. The commodity whose

price was most severely affected in this manner was food grains. There were

steep hikes in the central issue prices of rice and wheat in December 1991,

January 1993 and February 1994. As a consequence of these hikes, by

February 1994 the issue price of the common variety of rice had increased by

86 percent compared to the immediate pre-`structural adjustment' level and

of wheat by 72 percent. It is hardly surprising that the cost-of-living of the

workers, both in urban and rural areas, went up so sharply, and that the cost-

of-living of agricultural labourers, for whom food is an even more important

item in the consumption basket than for industrial workers, went up more

steeply than for the latter.

III. Non-economic Factors of Economic Growth & their Impact on

Inflations.

Economic Growth as a process is based on two distinct factors

namely ‗economic‘ and ‗Non-economic‘. Economic growth of a country is

dependent upon its geography as a whole including natural resources,

human resources, capital formation, technology, enterprises so and so

forth. All these can be classified under ‗Economic‘ factors. While ‗non-

economic‘ factors also become of prime consideration, when economic

growth in totality is measured. For this under the title ‗Non-economic

factors‘ one can divide them into two groups namely ‗Environmental‘ and

‗Non-Environmental‘ factors. Both these groups can be deliberated upon

as follows:

97

(i) Non-economic Environmental Factors

Non-economic Environmental factors usually involve environment as a

whole and can be again sub-grouped as under:

(a) Rainfall and draught

(b) Natural disasters, earthquake, tsunami, etc

(a) Rainfall (draught/flood)

It is seen that the world economies based on Forest and Agriculture are

mostly dependent on moderate rainfall for carrying on Agriculture activities

and/or survival of the forest. The Monsoon has assumed importance for

rainfall and absence of Monsoon results in draught with consequence of

famine, disease etc. Excess of monsoon results in flood and is also not

considered conducive for agriculture and food products including forest.

Otherwise also, the rainfall is must for maintenance of ground water level

and for carrying on various other activities. India‘s leading business and

economic database and research company 34 in its publication has

observed:

―The poor progress of south-west monsoon till the first week of July 2009 is

expected to adversely affect growth in agriculture, industry and the Gross

Domestic Product of the country as a whole. ……The impact of the lower

agricultural output and slower industrial recovery will be felt on GDP

growth. With GDP to grow by 5.8 per cent in 2009-10 compared to 6.6 per

cent expected earlier. While the Union Budget is expansionary and

conducive to growth, the failure of the monsoon and its significantly

adverse impact on agriculture will shave off 0.8 percentage points from the

34 CMIE (Centre for Monitoring Indian Economy ) Poor Progress of Monsoon to affect

Growth by Chintamani Athalye asamir@ cmie. com

98

GDP growth rate. With GDP growing at 5.8 percent, India will still become

few countries with a respectable growth rate.‖

b ) Natural disasters, earthquake, tsunami, etc:

Natural disasters can be considered not as a positive sign of

economic growth but as a factor affecting economy. Some of the

countries prone to natural disasters give importance to disaster

management and even have Ministry and departments readily dealing

with disaster management whether earthquake, tsunami, forest fire,

volcanic eruptions etc.

If one refers to the past, 1815 AD is witness to Tambora Volcanic

Eruption in Indonesia which was rated at 7 recter scale and was

considered to be 52,000 times more powerful than Hiroshima Bomb. In 1908

in Russian Siberian area became victim of The Tunguska Explosion due to

fall of asteroid or comet with power of 10-15 megaton which toppled 80

million trees over 772 Sq Km of Siberia. On the contrary Central China

Nanjing city the then China‘s capital suffered because of great flood in

1931 converting the entire capital into an Island surrounded by 100,000 Sq

Km of water. In March 1993 the worse snow storm of the century engulfed

North Carolina, Virginia and other West Virginia making about 380 people

to freeze beside others to suffer from snow bites, frost bites etc and

devastated the economy of the area. In 1999 Bridge Creek Estorondo

(Oklahoma city) much damage was caused resulting in more than 8000

homes destroyed and large scale overall devastation. In 2003 due to heat

wave 75% of Ukraine wheat crop was parched to destruction. Innumerous

reference can be made like melting of Alpine glaciers resulting in flash

flood in Switzerland, forest fires in France causing death to 14802 people,

Chile Earthquake in 1960 and Haiti‘s terrifying natural disaster. In short and

brief in year 2010 up to March 14 approx. 2,20,000 people are reported

99

dead in the natural disasters. Japan‘ quake can be cited as current

example which caused a 400 Km long and 160 Km wide rupture in the

Earths crust as one tectonic plate dove under another off the coast of

northern Japan causing tsunami with the result death and destruction

crippling the economy35.

All the natural disasters not only have concern of particular country

but they are being seen by the world at large. The United Nations itself

steps in for aid and assistance. Besides, the countries contribute for

remedial measures. All these disasters drain out the economy at national

and international level which otherwise could have been used for

developmental purposes.

But this apart, in the field of economy, natural disaster does not gather

much momentum as there are other definite and prominent factors for

economic growth. But seen from the context of disasters it is seen that

progressive countries/place of the past have been lost and only do find

mention in the history and literature. The country like India does have a

budgetary allocation towards unforeseen natural disasters including flood

etc. This amount is definitely shelved from the overall consolidated fund of

India. Economists like Hardin36 stresses on regulation / control to prevent

economic degradation while Ostrom 37 speaks about self governing rules in

society for preventing environmental degradation . On the other,

American Author Stephen M. Mayor38 observes that the environmental

35 Sunday Times , The Times of India, Lucknow Edition, March 13 , 2011. 36 Garrett James Hardin a leading ecologist from Dallas, Texas in his paper ‗The

Tragedy of the Commons‘ (1968). Also known for Hardin‘s First Law of Ecology

which states ‗You cannot do only one thing‘ and used the familiar phrase ‗Nice

guys finish last‘ to sum up the ‗selfish gene‘ concept of life and evolution. 37 Elinor Ostrom an American political economist awarded Nobel Memorial Prize in

Economic Sciences in 2009 for her analysis of economic governance, especially the commons. University of Chicago Law Review 53 (1986): 711–781 (en.wikipedia.

org/wiki/ Elinor _Ostrom). 38 Stephen M. Meyer - ‗Environmentalism & Economic Property : Testing the

Environmental impact hypothesis‘ Massachusetts Institute of Technology, Project

on Environmental Politics and Policy, October 5, 1992.

100

impact on economy is theoretically plausible but not on empirical

foundations but still he agrees some influence of environment on

economic development. In India, the environmental protection has been

taken as related to human capital formation and for economic growth

and development. A definite relation exists between Environment,

Economic Growth and prices thereto.

(ii) Non-economic & Non- Environmental Factors

For economic development both economic and non-economic

factors are responsible. Both factors are supplementary and

complementary to one another and can be discussed under

different sub-headings as under:

(a) Political factors

(b) Administrative factors

(c) Judicial factors

(d) Social factors

(e) Religious factors

(f) Human factors

(g) Others

(a) Political factors

Political factors can be considered of prime importance among the ‗Non-

economic factors‘ of economic growth. In India, it is the practice of

political parties to contest the elections on set manifestoes which contains

attention towards economic development and /or economic plan/policies

which the political party professes to adopt in case elected to power.

Though the manifestoes remain manifestoes on paper but still they

become guiding principles for the particular political party with respect to

101

the promises made to the party. All these factors compel R.Nurkse39 while

studying capital formation in underdeveloped countries to say:

―Economic development has much to do with human endowments, social

attitudes, political conditions and historical accidents.‖

Jim Peach40 while delivering lecture on ‗Galbraith and the Problem of

Uneven Development‘ observes:

―…….He approached the economic development problem with a

keen understanding of both the economic and political forces shaping the

development debate….‖

The influence of political factors on the price rise can be gauged from time

to time government policies. There are also instances when it is alleged

that the government has maneuvered the price rise. Going back to

beginning of 1979 when everything on the economic front was considered

satisfactory, but introduction of the budget by the then Finance Minister

Choudhry Charan Singh caused inflation with a heavy dose of indirect

taxation. The budget introduced was deficit by Rs.1365 crores with its

consequences on Inflation resulting in their rise. The wholesale price index

which stood at 185 with 1970-71 as base year of 100 but it is astonishing to

note that in January 1980 the whole sale price index shot up to 224.

The government policies from time to time on price rise have been

criticized in and outside the parliament. Cut motions have been moved by

parliamentarians/opposition in the parliament preventing parliamentary

business for days together. The Inflation and/or unwarranted price rise on

numerous occasions have become subject of politics. It is astonishing to

note that a respectable Cabinet Minister and parliamentarian while giving

press briefing expressed that ―there is no anger on streets over rise in prices‖

39 Problems of Capital Formation in Underdeveloped Countries by R.Nurkse,

Blackwell, Oxford, 1953. 40 Journal of Economic Issues Vol. XLII No.1 March 2008, p 25. The author Jim Peach is Regents

Professor of Economics at New Mexico State University in Las Curcs, New Mexico.

102

when the fact remains that price rise has become reality and of grave

concern for the common man and consumer in India as visualized in the

circumstances appearing during first quarter of financial year 2010-1141.

For a sustained and systematic price mechanism, political stability of a

country is of prime concern. The systematic Inflation results in progress and

economic development. On the contrary, an unsystematic Inflation in

planned economy has adverse consequences. The political stability in

most of the developed countries including United States, Britain and France

has contributed towards their economic growth and stability despite the

fact that United States, Britain were involved in the World Wars. Unan

(Greece), Misr (Syria) and Rome(Italy) were considered great economies

at one time but today they are lagging behind. For Greece and Syria,

because of their unstable governments, wars, unplanned economy etc.

while for Italy the political stability coupled with corruption and weak

administration retarded its economic development in comparison to

developed countries. Soviet Russia at one time considered to be a world

power in then bi-polar world, has lost its supremacy because of political

immaturity, instability, resulting in disintegration of the country into 16

fragments including Russia itself.

(b) Administrative factors

With political set up, a country needs a strong and vibrant administrative

system as a whole. India‘s administrative system is a legacy of British when

they left in 1947. With modification in the administrative set-up for making it

working under Indian condition various steps were taken by the

government. The administration in India is usually nick-named as

bureaucracy which is referred to create various bureaucratic hurdles in

implementing government policies. The fact remains that government

41 The Financial Express, Lucknow edition, Aug. 3, 2010 column 4,5,6

103

policies and programs are usually implemented by the administrative set-

up. Weak and corrupt administrative set-up not only hinders economic

development but also causes disaster for the country. It is for the

administration to enforce Essential Commodities Act42 to prevent hoarding,

black-marketing etc. So as to usher free flow of commodities and

consumer goods to the public at large in the country. Again, it is the

administration who has to take care of wages, working hours, health,

sanitation and like other welfare measures43 of the wage earners but

inefficient, lethargic and corrupt administration fails/neglects to address

such issues with the result the policies framed fail to be implemented.

For economic development of a country and for implementation of

policies from time to time a vibrant system is required which can address to

issues facing the countries including the policies and rules framed towards

that.

With respect to India‘s position and the Inflation there are writers who

have laid much stress on stable governments and efficient administration.

Bhabatosh Datta 44 observes:

―The origin of inflation is often to be found in the panicky nervousness

of unstable governments in politically unsettled communities. Given

political stability there is no reason why India should not be able to carry

out her future plans without generating serious inflationary pressure on the

price level.‖

42 The Essential Commodities Act , 1955 ( 10 of 1955 ) . An Act to provide, in the interests of

general public, for the control of production, supply and distribution of, and trade and

commerce in, certain commodities. 43 Reference can be made to Part IV of the Constitution of India dealing with Directive

Principles of State Policy and various Labour Legislations including the Payment of Wages

Act, 1936, Minimum Wages Act, 1948, Contract Labour (Regulation and Abolition) Act, 1970

and like Laws. 44 Bhababatosh Datta is Emeritus Professor of Economics, Presidency College, Calcutta and

recipient of Padma Vibhushan. His writings spread over a period of fifty years, show that he

never deviated from a vision of an economy (www.jstor.org/stable/4405331)

104

(c) Judicial/Legal factors

Among the non economic factors of economic growth the Judicial

cum Legal factors also have their own role in the context of Indian

economy. Though, this factor is not being given due importance but

seeing the country‘s political system based on the Constitution whose

preamble itself speaks inter-alia about Socialistic pattern of Republic with

justice on the basis of social, economic and political parameters.45

The constitution in its directive principles, clearly formulates

constitutional obligation which the government has to discharge regarding

welfare of the people, minimizing the equality in income, operation of

economic system which does not result in concentration of wealth and

means of production to the common detriment. The directives also

provides for living wages, Participation of workers in management of

industries, Promotion of educational and economic interests of SC/ST and

other weaker sections. Organization of animal husbandry, besides

safeguarding forests etc.46. There are like other provisions in the Constitution

and other Laws which can be considered as guiding factors for economic

planning and development of the economy leaving way for a planned

economy for the country. During the period immediately after coming into

being of the Constitution of India, country witnessed large scale Agrarian

reforms and reforms related to poverty eradication etc. Many of the

government reforms were challenged before the judiciary and till 1970

there have been divergent judgments; sometimes supporting the

government reforms and on others declaring the reforms as un-

constitutional. 47

45 Preamble to the Constitution of India with words like ‗Socialist‘ and ‗Secular‘

incorporated by 42nd Amendment of 1976 46 Reference made to Articles 43, 43-A, 46, 48 & 48-A of the Constitution of India. 47 Among innumerous cases reference can be made to Golak Nath Vs. State of

Punjab AIR 1967 Supreme Court 1643 (Land Reforms), Keshavanand Bharati Vs.

105

The Nobel laureate Amritya Sen in 2003 while delivering lecture on ―Law

economics and Social Change‖ at West Bengal National University of

Judicial Sciences Kolkata observed that economies need firm legal support

for their development. His view on the issue is appended:

―Market economies tend to rely on firm support from appropriate

legal rules, and these rules can, often enough, greatly aid market-based

economic development.‖

Learned author and advocate Gobind Das48 specifically provides the role

of the court and the economic activity during the period upto 1970 and

the relevant extract from the referred book is appended :

―The history of the Court shows that during lts first decade, in the

opening years from 1950-1960, finding itself in a Nehruvian era of economic

progress, political stability and nascent optimism in the country…..The Court

moved forwards and backwards, and ultimately drew a line. The Court

blended the orthodox judicial function with policy making. It tried to

protect the rights to property, particularly of the rural land owning class

from the clutches of intruding legislations.‖

The learned author further describes the position of the economy and also

the position of the Supreme Court in entering into the areas of policy

making of the government. The relevant passage is quoted as under:

―During the succeeding period from 1961-70, finding a crippled

economy, instability of political authority, immorality in public life, unbridled

exercise of the parliamentary power of constitutional amendment, the

Court led by Chief Justice Subba Rao , Hidayatullah and Shah, went into

policy making on a grand scale. It curbed the power of the Parliament,

struck down major economic decisions of the executive and overruled

public policies of the Government. It acquired judicial sovereignty. It

State of Kerala AIR 1973 Supreme Court 1461 and Cooper Vs. Union of India AIR

1970 Supreme Court 564 (Bank Nationalization Case). 48 ‗Supreme Court in Quest of Identity‘ by Gobind Das, p 2 and 3, 2nd edition 2000.

106

appeared as though in India there existed Government by judiciary. In this

decade it leaned in favour of urban commercial middle classes protecting

their economic and political interest.‖

This trend of the Court diverted towards general welfare of the public

resulting in public interest litigation especially in the areas of non-

implementation of government schemes by government itself and/or non-

following of rules and regulation concerning human resources besides

environment and other economic activities. In short judicial / legal factors

cannot be ignored as and when India‘s economic conditions are

concerned and/or policy/plans are framed by the government.

(d) Social factors

Social factors are also seen having some bearing on the economy of

a country. Society as a whole is influenced by social institutions and a set

pattern of behavior is developed. Therefore, any economic program and

planning for its true implementation requires change of mind-set, more so,

when such a change is opposite to any established social behavior.

G. Myrdal49 speaks about modernization as a factor responsible for

rapid economic development as per him modernization connotes:

―the social, cultural and psychological framework which facilitates the

application of tested knowledge to all phases and branches of

production.‖

The learned author has referred to social, cultural and psychological

framework, which in totality falls within a parameter of social factor

influencing economic growth.

49 An International Economy : Problems and Prospects by G.Myrdal , Harper New York 1956.

107

A.K.Cairncross50 while specifically dealing with factors for economic

development in his book titled as ‗Factors in Economic Development‘

observes :

― No country can count itself developed, in which education in the

way of industrial civilization has not taken place. Peasants have to be

brought within the monetary economy and not left to pursue subsistence

farming; workers have to become used to working fixed hours in factories

for wage payments; towns have to grow, and so banks and business

enterprises; the fruits of science have to be applied throughout the

economy; above all, there must emerge as a continuing element in the

life of the country, a group of business, administrative and political leaders

who can be depended upon to maintain the momentum of development

by constant innovation.‖

Regarding innovation Schumpeter 51 stated that innovation is the structure

of economy and source of economic fluctuations. ……….. in short he

substantiates to the view of Circular Flow which breaks when innovation

takes place in an economy. Thus, among non-economic factors social

factor cannot be ignored.

(e) Religious factors

The Religion as non-economic factor of economic growth cannot be

brushed aside in a Secular State like India, predominated by various

religious faiths. The religion cements the human behavior, ethos and inter-

community interactions. For development of a country among others

quality of population and human capital is must. The policy regarding a

planned family propounded by the government is not effective and one of

50 Factors in Economic Development by A.K.Cairncross , Allen & Unwin, London , 1964 51 J.A. Schumpeter‘s Theory of Innovation. Reference may also be made to ―The

analysis of Economic Change‖ 1954 in Readings in Business Cycle Theories in

Austrian perspective.

108

the reasons being opposition on religious grounds resulting in poor quality

of human resource adding to the country‘s poverty. Religious factors also

affect in raising the scientific and educational standard of some of the

communities who oppose women‘s education/liberty and

entrepreneurship. In country like India, which is not only dominated by

different religious denominations but each religion is sub-divided into

various sects/classes/castes with conflicting interests among themselves.

Any policy toward economic development either ought to cover entire

spectrum of the population irrespective of religion, race , caste, sex, place

of birth or otherwise as the case may be. The inter-se conflict among

various religious and/or among some sub-sects, disturbs the national peace

and security which indirectly affects a conducive economic growth.

History has number of references when there have been religious

wars/conflicts, which drained the economy of the country. The Taliban in

Afghanistan, Extermination of Jews from Germany, Arabs in Ghaza resulting

in constant conflicts with Israel. Most of the under-developed countries are

predominately influenced by religious dogmas not inclined to adjust to

modernity of the life with science and technology. This conservative mind-

set disallows any change towards economic growth and as such in most

cases becomes a barrier for economies to expand.

(f) Human factors :

Among the other Non-economic factor of economic growth, human

factor also assumes importance and cannot be ignored in modern

economic growth. The human factor responsible for human growth of a

country can be termed as human capital formation. The social behavior

of population especially Labour force is essential in the process of

economic development, meaning thereby, that mere population growth is

not an indicator to comment upon the resultant economic growth. For

109

example a comparison with China reveals that China‘s population

estimated at 12778 million in 2000 is now growing at about 0.95 per cent

annually i.e. addition of about 12million people every year compared to

the addition of 17 million people in the case of India. Thus India is now

adding every year about 5 million people more than China. At this rate

there is a possibility that India may overtake China in population size by the

middle of the current century. This being the position as far as population

predictions are concerned. But there are rumors about China‘s progress

on economic front as reflected in newspaper columns52 wherein it is

referred:

―Beijing: China has overtaken Japan to become the world‘s second

largest economy, the fruit of three decades of rapid growth that has lifted

hundreds of millions of people out of poverty.

Depending on how fast its exchange rate rises, China is on course to

overtake the US and vault into the No.1 spot sometime around 2025,

according to projections by the World Bank, Goldman Sachs and others.

China came close to surpassing Japan in 2009 and the disclosure by a

senior official that it had now done so comes as no surprise. Indeed, Yi

Gang, China‘s Chief Currency Regulator, mentioned the milestone in

passing in remark s published on Friday, ‗China in fact is already the world‘s

second largest economy‖.

In short the human factor or human resources or human capital formation

depends upon government‘s concern on health, education and other

related social services to produce quality of human capital formation.

Most of the developed countries incur substantial expenditure on referred

factors in comparison to under-developed and developing countries; with

an expectation to have better human capital formation with increased

knowledge and skills. Once this objective of trained and skilled labour force

52 Times of India in its Times Business dated July 31st 2010.

110

with education, background and healthy atmosphere is attained, there

can be high productive efficiency which is expected to lead to

appropriate levels of economic development.

(g) Others

In the words of Bert F.Hoselitz53, with respect to ‗Non-Economic

Factors in Economic Development‘ assertions are made about opening of

new areas about structural change for widening the domestic market and

creating a foreign market. While making such emphasis the learned

author says:

―Apart from the build-up of economic overhead capital, such as a

communications and transport system and investment in harbour facilities,

some warehouses and similar installation favoring especially foreign trade,

most of the innovations introduced during the preparatory period are

based upon changes in the institutional arrangements in the legal,

educational, familial, or motivational orders. Once these new institutions

have been created, they operate as ‗gifts from the past‘, contributing

freely to the vigorous spurt of economic activity in the period of take-off.

What is perhaps most important about the structural changes taking place

during the take off period is the adaptation of previously existing institutions

for new ends, especially for capital formation.‖ (Emphasis ours)

Renowned economist Caircross54 while dealing with the issue has taken

overall factors into consideration including Social behavior etc. and

observes :

―Development is not just a matter of having plenty of money nor is it purely

an economic phenomenon. It embraces all aspects of social behavior;

the establishment of law and order, scrupulousness in business dealings,

53 Bert F.Hoselitz, ‗Theories of Economic Growth‘ 1965.

54 A.K.Cairncross - Factors in Economic Development , Allen & Unwin, London, 1964.

111

including dealings with the revenue authorities; relationships between the

family, literacy, familiarity with mechanical gadgets and so on.‖

Economists have no hesitation in deliberating upon economic crisis /

recession and development of new Economies. Niriman Behravesh,55 while

Predicting for 2010 writes:

―The U.S. and world economies have emerged from recession, and the

recovery process has begun. Unfortunately, for most developed

economies, this recovery will not feel like one in its early states. Strong

tailwinds (policy stimulus, improved financial conditions, and pent-up

demand) are being partially neutralized by equally strong headwinds

(rising unemployment rates, lingering hangovers from housing bubbles and

the financial crisis, and the likely winding down of fiscal stimulus).

Consequently, global GDP will grow only 2.8% in 2010 – much better than

the 2.0% drop in 2009, but well below the 3.5 – 4.0% trend rate of growth for

the world economy. Most emerging markets, particularly Asia, will

outpace the developed economies next year. The U.S. economic

recovery will begin the year slowly, but Europe and Japan will rebound

even more slowly.‖

Marky Wrenn, James Ronald Stanfield, and Michael Carroll56 on ‗Galbraith

and Robinson‘s Second Crisis of Economic Theory‘ analyzing the issue and

taking into consideration Keynesian and neo-Keynesian observe:

―…The Keynesian revolution dealt with one aspect of the crisis of

economic theory, the inadequacy of aggregate demand, but neo-

Keynesian economics left a vacuum by not addressing the state‘s role in

the structure of output. Hence, issues in regard to distribution and uneven

development and militarism, consumerism and ecological sustainability

were neglected and persists with great force today…‖

55

Niriman Behravesh, IHS Chief Economist on commenting Economic Predictions for 2010. 56 Journal of Economic Issues Vol. XLII No.1 March 2008, page 5.

112

In the past, there have been conquers, warriors but the end of 20th and the

beginning of 21st century is looming large under extremism/terrorism which

cannot be considered conducive for stability of any geographical region.

Once stability becomes doubtful, the expenditure for infrastructure and

development gets relegated affecting the economic development. In

country like India references can be made to Mao‘s, People‘s war group

and like others in the areas of Chhattishgarh, Jharkhand, parts of Andhra

and Maharashtra. Even there are measures by the government for

development of the area but such measures does not reach the common

masses nor the government is capable of implementing its programs and

plans in those underdeveloped areas though rich in natural resources.

Likewise, the North East suffers from terror and disturbance from the groups

like Ulfa, infiltrators and others. Kashmir is the example to quote as far as

terrorism is concerned. Substantial state budget and central allocation are

granted to curb the terrorist activities and for economic development.

Therefore, in nutshell the factors referred hereinbefore cannot be

ignored while computing parameters for the economic growth of a given

geography. The conversion of terrorist to human beings and from human

beings to human capital is must for growth and development of country.

An Emperical Analysis of Growth and Inflation Trade-off

(1980-2010)

In order To analyze the extent of relationship between economic

growth and inflation and vice versa, the cointegration theory and two

steps Error Correction Model (ECM) is used. Which was proposed by Engle-

Granger (1987) two-step cointegration approach is used to check whether

the dependent variable is cointegrated with the independent variable;

If both time series are integrated of the same order then it is possible to

113

proceed with the estimation of the following cointegration regression:

Gt = α1 + β1 It + μt ………………………………… (1)

It = α2 + β2 Gt + et ………………………………… (2)

Where Gt = economic growth rate, It = inflation rate at time t, and μt is

standard residual term that measure the extent to which Gt and It are out

of equilibrium. If μt and et are integration of order zero, I (0), then it can be

said that both Gt and It are cointegrated no expectation of they would

stay apart in the long term. Existence of cointegration suggests any

available information on one variable could be used to predict the other.

According to the cointegration theory, there could be an existence

of long-term relationship between two steps in a bivariate association only

if they the variables are stationary or if each step equation is at least

integrated of the same order (Campbell and Perron, 1991). That is, if two

series are integrated of the same order, I (D) for D = 0, 1, 2… then the

two steps are termed as; the two variables is meaningful and not

spurious and on long-run information is lost. Thus, the first step is to test for

the existence of stationarity between the variables; growth rate (G) and

inflation rate (I).

First, the Dickey and Fuller (1979) test is run then the Augmented

Dickey and Fuller (1981) test with and without a time trend. The latter allows

for higher autocorrelation in residuals.

Xt = 1 +βπ1 Xt-1 + ρ1 Xt-i + e1t …………………………... (3) i 1

These tests are carried out for both variables by replacing Xt with Gt

and It in equations (2) (for the DF-ADF tests)

Results of unit root tests are reported in tables 4.8 and 4.9. This suggests that

114

both GDP (G) and inflation (I) bears zero order integration for India.

Table 4.8 Average inflation and growth rates

CPI Based Inflation Rate Growth Rate

Mean 7.53 6.2

Standard

Deviation 3.93 2.88

Time Duration: 1983-2010

Table 4.9. DF & ADF UNIT ROOT TEST

DF & ADF UNIT ROOT TEST RESULTS

TESTING VARIABLES VARIABLES DF

ADF

I 6.22

-1.9

G

-4.47

-3.91

The variables are significant at 1%, 5% and 10% levels of significance comparing

critical t statistics as computed by MacKinnon (1991).

Next, we examine the cointegrating relationship between economic

growth and inflation. First, cointegrating equations (1) and (2) are

estimated.

Results of cointegration tests and estimates of the cointegrating

parameters are reported in tables 4.10 and 4.11. They show that growth

rates and inflation rates are cointegrated. The empirical evidence also

implies that there is a long-run relationship between growth rates and

inflation rates and the interesting finding, is that the relationship between

inflation and growth rate is negative.

These variables are significant at 1%, 5% and 10% levels of

significance comparing critical t statistics as computed by MacKinnon

(1991).

115

These findings have important policy implications –inflation is harmful rather

than helpful to growth. Caution is needed since higher inflation may trigger

inflationary spirals beyond a safe level as implied by larger inflation

elasticities.

Table 4.10 Error correction model GDP on CPI

Regression Results (1983-2010)

DEPENDENT VARIABLE: d(GDP)

VARIABLE COEFF. STD. ERROR T-STATISTIC PROBABILITY

d(GDP(-1) -0.01577 0.197284 -0.059641 0.9101

d(CPI) -0.51363 0.123933 -4.003681 0.005

d(CPI(-2) -0.10265 0.09094 -1.297009 0.2323

d(CPI(-1) 0.21675 0.106145 1.945067 0.211

d(CPI(-3) 0.112759 0.092051 1.106721 0.2851

Res(-1) -0.89886 0.242332 -3.119042 0.0039

C 0.193668 0.497071 0.401472 0.5911

R-Sq.0 0.696959 F-STATISTIC 14.21709

SE REGRESSION 1.996799

SS RESID. 139.2616

D-W 2.21037

Table 4.11. Error correction model for CPI on GDP

Regression Results (1983-2010)

DEPENDENT VARIABLE: d(CPI)

VARIABLE COEFF. STD. ERROR T-STATISTIC PROBABILITY

d(GDP) -0.39297 0.139883 -1.997861 0.0191

d(CPI(-1) 0.188429 0.135672 1.531655 0.1236

d(GDP(-2) 0.159971 0.185809 1.009931 0.2729

d(GDP(-3) 0.039561 0.179234 0.330096 0.66101

ResCPI(-1) -0.82456 0.201235 4.1718 0.0003

C -0.22487 0.5719 0.414761 0.5987

R-Sq. 0.677213

F-STATITIC 5.56601

SE REGRESSION 2.26786

SS RESID. 221.336

D-W 1.563541

116

Tables 4.10 and 4.11 presents the estimated coefficients of the error

correction model (long-term effects) and the lagged values of the two

equations (short-term effects). The estimated coefficients of the error

correction term ρ1, and ρ2 are at 5 % level of significance from growth rates

to inflation and vice versa with required (negative) signs. This exhibits the

fact that if the two equations are stayed away from equilibrium, as

exhibited in the cointegrating analysis (1) and (2), growth rates will adjust to

reduce the equilibrium error and vice versa.

CONCLUSION

The present chapter has been influenced by the recent

developments in the economic theory on the linkages between inflation

and economic growth and the contemporary contradictory evidence put

forth on the basis of the analysis on developed and developing

economies. For this purpose cointegration and error correction models

have been performed to empirically examine long-run and short-run

phenomenon of the growth-inflation linkages in India using annual data.

With an objective to examine whether any such relationship exist between

the two. The analysis result brings forth the fact that the inflation and

economic growth are negatively related. Second, inflation causes greater

changes in growth rates than the effect of GDP growth rate on Inflation.

These findings have important policy implications.

Moreover the present chapter, on the inflation-growth linkages

concludes that that any rise in inflation with reference to the previous

period adversely affects GDP growth rate. , hence the policy makers have

to opt for the measures which always maintains downward pressure on

inflation, without taking care of threshold level. Furthermore, the

government should always remember that the common man and the

decision makers do not welcome inflation that carries enormous effects on

117

the consumption pattern, which subsequently affects the output

demanded.

Macroeconomic stability and the necessary infrastructure are

among the preconditions for sustained growth. Among the ways inflation

can affect growth, an important avenue is the effect of inflation on

investment. Low or moderate inflation is an indicator of macroeconomic

stability and creates an environment conducive for investment. A review of

the existing cross-country international evidence, as well as evidence from

Asia, indicates a negative relationship between inflation and long-term

growth. Countries with low or moderate rates of inflation have higher

growth rates over the long-term compared with countries with high inflation

rates. However, low inflation does not constitute a sufficient condition for

growth. The Indian experience appears to support the above view. In India

inflation has generally been kept under control. There have been two

episodes of high inflation since 1980 but price rise has been controlled by

various fiscal, monetary and administrative measures. Also, evidence from

investment behaviour in private manufacturing suggests that an increase in

the rate of inflation has a negative impact on private investment in

manufacturing. The regression for private investment in agriculture points

towards complementarities between public and private investment. Taking

economy-wide linkages into account, the analysis suggests that higher

growth can be achieved by controlling inflation and raising public

investment. To promote growth and keep inflation low, the government

needs to control budget deficits. While simulations indicate that this can be

achieved by switching public expenditure from consumption to

investment, this may be a difficult policy to pursue, especially in a

developing

economies with a multiparty democracy. It may be more realistic to

choose tolerable rate and achieve the maximum possible growth given

118

that rate, by deficit-financed public investment.

The model allows the policy maker to see the various trade-offs involved.

The overall message is clear—the government should curtail unproductive

expenditure, which is bad for both growth and inflation, in favour of

investment. Providing stability and the necessary infrastructure can set the

stage for the use of other more direct policy measures aimed at promoting

growth.

119

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121

CHAPTER – V

Anti-Inflationary Policies

1. Planning Policies

2. Fiscal policies

3. Monetary policies

4. Other policies

------------------------------------

India is considered as a planned economy, the planning whereof is

based on five year plans, annual budgets, etc. Under Indian socio-

economic and political conditions, the five year plans referred become

policies of the government for economic development of the country. In

addition to this, each year government has to pass budget but while doing

so they need to address policies and programs as recommended in five-

year plans. Side by side the fiscal policy and monetary policies are evolved

which in totality act as an aid to the policies framed under the plan. Thus in

this way for policy implications it is primarily the plans framed from time to

time, objective and targets made therein, achievement thereof which

become relevant for studying the policy implication with respect to

economic growth of a developing country like India. Accordingly, the

policy implication is dealt in a manner hereunder from plan to plan and

conjointly, besides, conversely wherever required for critical appreciation

of the subject. The policy implications for the purpose of study and as

deduced from various sources, analysis thereto and dealt in chapters

hereinbefore can be deliberated upon in four distinct heads referred

above.

122

1. The Pre- Reform Planning Policies:

The sixth Plan (1980-1985):

The sixth plan initially started for five year i.e. from 1978 to 83 but in 1980

after defeat of the Janata government and coming in power by the

Congress government the ‗Rolling Plan‘ was abandoned and a new sixth

five year plan was introduced with effect from 1st April 1980 to 31st March

1985. This Plan has thrust and objectives for ensuring sufficient growth in rate

of economic development, improvement in efficiency related to utilization

of resources and increase in production. The Plan also stressed for

encouraging modernization for self-sufficiency towards economic and

technological goals. Incidence of poverty and unemployment was to be

reduced. Development on domestic source of energy and utilization of the

same. Improvement in the living standard of the people. Minimizing the

disparities in income and wealth. Minimizing regional disparities in

extending the benefits of growth including technological progress,

controlling population explosion. The Plan also stressed for coordination

between short and long term targets of developments and for providing

protection and improvement in ecological and environmental assets,

besides, it was ensured that all categories of people ought to participate in

development process by adopting educational, communication and

institutional strategies. The 6th Five year Plan targeted the growth rate at 5.2

percent per annum. But it is noted that actual growth rate stood at 5.3

percent per annum at 1983-84 prices.

On the other side, the food-grain production the target of nearly 154

million tons was achieved but on the Industrial Production growth same

was reported as 5.5 percent against the target of 7 percent, a shortfall of

1.5 percent in this sector. The increase in the per capital income was

arrived at 3.1percent per annum. The programs for eradication of poverty

123

and unemployment57 were adopted. The position since 1980 can thus be

perceived from the analysis and observations made by Gobind Das58 in a

manner as follows:

‖Since 1980 India made a mini-leap forward. The economy was

comfortable. – Satisfactory progress in agricultural front, in production of oil

and in industrial growth.

The early 1980‘s saw India‘s mini-leap forward. The popular perception

of a bumbling economy with ‗red-tape infested comedy of errors‘ gave

way to an optimistic forecast of stability and reasonable progress. India

escaped from its traditional constraint of 3.5 % growth rate and reached a

new level of 5 %. And the growth rate during last quarter reached a heady

7 % and agricultural growth rate was between 10 and 12 %. The

enhancement of production of food grains by 19 million tons higher than in

1982-83, indicated the growing resilience of Indian agriculture. India

recorded a dramatic increase in the production of crude oil, it more than

doubled the production of 10.5 million tons in 1980-81 to 26.2 million tons in

1983-84. The share of oil imports in total oil consumption declined from 60%

in 1980-81 to a mere 27% in 1983-84, the single most important factor in the

turnaround in the balance of payment situation. There was an

accompanying windfall in remittances from non-resident Indians in Indian

Banks from an average of 200 crores to a ‗whopping‘ Rupees 800 crores in

1983-84.‖

The aforesaid factors and the deliberation in the research work in its

different chapters reveals economic development and the movement of

57 Advances to Priority Sector and Credit Guarantee Schemes were remodeled and

new Twenty Point Programme was propounded on 14th January 1982.

58

Supreme Court in quest of Identity by Gobind Das 2nd Edition page 138.

124

the prices. The sixth five year plan of 1980-85 shows GNP at factor cost at its

current price at 15.4 while NNP at factor cost at current price as 15.2 while

per capita NNP at the current prices as 12.8. When compared to fisrt year

plan the respective figures percentage wise were 1.8, 2.0 and 0.2. For

details with respect to plan wise average growth rate of GNP and NNP

reference can be made to table 2-3 in chapter 2. Thus it can be said that

the post 1980 has witnessed burst of economic growth with leaped

headlong into the industrial age duly recommended by the financial

pundits who then gathered at Paris.

The Seventh Plan:

The seventh plan started from 1st April 1985 and ended by 31st March 1990.

The emphasis in the plan was towards the policies and programs aimed at

rapid growth in food grain production, increased employment

opportunities and productivity within the framework of basic tenants of

planning meaning thereby the plan laid stress on growth, modernization,

self-reliance and social justice. For brief it can be said that objective of the

seventh plan were towards establishing an independent and self-sufficient

economy, social system based on equality and justice, for reducing social

and economic disparities, preparing firm foundation for national

technological development, to create productive employment. The plan

also laid emphasis for sufficient increase in agriculture production,

especially food grains and to establish self-reliance for export promotion

and import substitution as mentioned in the earlier plan. This plan in specific

terms gave priorities to energy protection and development and

development of non-traditional energy source, besides, the plan also

mentions about ecological and environmental protection. The Plan

projected for attaining an annual growth rate of 5 percent.

It is seen that the Plan targeted the growth rate at 5 percent per

annum but during the plan period the actual growth rate of national

income stood at estimated at 5.9 percent on the prices of 1993-94. On the

125

growth rate front same was calculated as 3.7 percent per capita income.

It is also seen that in some of the growth rate areas were lower than the

targeted rates. Despite this, in the main areas the absolute growth rate was

satisfactory.

2. The Post Reform Planning Policies

Eighth Five year Plan:

Before formulating the eighth Plan, country witnessed significant

political changes, policy shifts and overall change keeping in view the

global economic climate. The Plan began from 1st April 1992 for a period of

five years ending with 31st March 1997. The fundamental objective of the

Plan was human development in its various aspects and towards that

priorities in brief were to create sufficient employment opportunities to

achieve the target of employment by the end of 20th century, seeking

people‘s cooperation by adopting measures for restricting population

explosion in India. The Plan also did take care of primary health facilities,

drinking water, vaccination in all villages in India and for elimination of

scavenging. On the agriculture front the plan laid emphasis on growth and

diversification of agriculture for achieving self-sufficiency in food and also

generating exportable surplus. All these projections in the plan were

considered to be achieved on the strength of basis infra-structure like

energy, transport, communication and irrigation etc, accordingly, the plan

laid its priorities in strengthening the infra-structure.

The analysis of the eighth five year plan in its end and beginning of

Ninth Plan shows that average annual growth rate in agriculture and allied

sector has been estimated at 3.9 percent against the target of 3.5 percent.

On the other, the annual growth rate for this sector in seventh Plan was only

3.5 percent per annum. On the industrial sector the growth rate has been

estimated at more than 7 percent per annum (excluding manufacturing,

mineral and mining). However, in industrial sector as a whole, the estimated

126

growth rate was 8 percent, higher then the targeted growth rate. The

annual growth rate of the Service sector was estimated at 7.9 percent GDP

at factor cost which shows 1.8 percent higher than the target though 0.5

percent lower than the rate achieved in the seventh plan. The services like

trading, communication, hotel, transport etc made a high progress and

growth rate. The rate of inflation based on whole sale price index was at

apex level of 16.3 percent in September 1991 which came down to level of

3.8 percent in November 1997. The growth rate of good grain production in

totality during 1991 to 1996-97 was 1.7 percent while the population growth

rate during the same period was 1.9 percent. As far as the projections of

eighth plan is concerned with respect to population, the average growth

rate whereof was calculated at 2.6 percent to 2.8 percent per annum. It

was also visualized that in first phase of plan itself, about 80-90 lakh

additional employment will be generated while in its second phase the

employment generation was considered to be 90-100 lakhs. But on the

contrary, unemployment rate among male workers increased in 1993-94 in

comparison to 1987-88. The rise in unemployment rate from the referred

year was from 5.54 percent to 4.91 percent. All these aspects with respect

to unemployment and population has been a major problem for the

economic planners of the country.

The Ninth Five year Plan:

The ninth plan started from 1st April 1997 and ended by 31st March

2002. A total outlay for ninth plan was kept at Rs.859200 crores though

earlier proposed outlay for the plan was Rs.875000 crores, the respective

outlay in various items is given in table hereinafter. The plan was formulated

at a time when overall world scenario was changed. The socialism was

rejected as a solution for governance and economy and market economy

was well taken by the world. The heavy investment in public sector alone

was not found sufficient and the role of private investment became explicit

127

and very much notable. A tabular statement is given for actual growth

rate of 9th Plan with economic indicators of 9th plan in a manner as follows:

Table – 5.1 9th Plan 1997-02 Actual Growth Rate (Sector-wise)

SECTOR Annual Growth Rate

during 9th Plan

I Agriculture and Allied 2.1

II Industry

1. mining and quarrying

2. Manufacturing

3. Electricity Gas and Water supply

4. Construction

4.5

3.8

3.7

6.5

6.8

III Services

5. Trade, Hotel, Transport &

Communication

6. Financial Real Estate & Business Services

7. Community Social and Personal Services

7.8

6.9

8.0

9.1

Iv Total GDP (at factor cost) 5.4

Table – 5.2Economic Indicators of Ninth Plan (1997-2002)

8th Plan 1992-97 9th Plan 1997-02

Target Actual Revised Target

1 Domestic Saving Rate* 21.6 23.8 26.1

2 Investment Rate* 23.2 24.9 28.2

3 ICOR 4.1 3.7 4.3

4 Expert Growth Rate** 13.6 11.9 11.8

5 Import Growth Rate** 8.4 11.7 10.8

6 BOP** deficit in current account 1.6 1.1 2.1

BOP** deficit in current account *GDP % at Factor Cost ** Annual Growth Rate in %

Earlier to this plan, especially in 90‘s it was emphasized that for

accelerating the pace of economic growth the problem of unemployment

is to be addressed coupled with removing the regional imbalances and for

acquiring self reliance in domestic and external sector of economy. The

objectives of the ninth plan were to give priority to development of

agriculture and villages, besides, for eradicating poverty. On the positive

side, the plan emphasized for creating sufficient productive employment.

There was stress for keeping prices stable and under control for the

128

economic development. The plan has drawn attention towards weaker

sections by ensuring provision of food and nourishment especially to such

segments of the society. On the service front the plan provided for clean

drinking water, primary health care facility, universal primary education,

housing with availability thereto. The emphasis of the plan was also on

population growth rate, maintaining environmental balance with people‘s

participation and also for encouraging and developing Panchayatraj

institutions, Cooperative and voluntary sections of the society. In very clear

terms the plan provided provisions for woman and socially weaker sections

including Scheduled Castes, Scheduled Tribes and other backward classes

and minorities so as to activate all these categories for economic

development and social change.

In short, the focus of the plan was growth with equity and distributive

justice for which different areas were identified for government attention

especially for raising the quality of life, employment promotion, eradication

of regional imbalances and for making the country as self-dependent for

ascertaining balance of payment, curtailing the foreign debt burden, for

self sufficiency in food grains. The self dependence also had an objective

for utilization and protection of national resources including herbs and

medicinal plants, besides, for attaining self sufficiency in technological

areas.

Tenth Five Year Plan:

The tenth plan commenced from 1st April 2002 and ended by 31st march

2007. The plan laid its focus on growth in per capita income (per capita

GDP). The approach paper to the plan suggested some of the issues to be

given consideration. For example, Swarn Jayanti Gram Swarozgar Yojana

and other allied programs like IRDP should be transformed into Micro

Finance Program to be run by banks with no subsidy on the similar lines as in

case of Rashtriya Mahila Kosh, people‘s participation with respect to

contribution in funds to gram sabhas by 25 percent in normal block areas

129

and 15 percent tribal/poor blocks, Food for work programs in areas of

distress, focus on productive work and their maintenance such as rural

roads, watershed development, rejuvenation of tanks, aforestation and

irrigation. Rural development funds should be used for enhancing

budgetary allocation of successful rural development schemes that are

being run by State governments, or for meeting the State contribution for

donor assisted programs for poverty alleviation, Special efforts for

strengthening the economy of the marginal and small farmers, forest

produce gathers, artisans and unskilled workers also the poor should not

merely benefit from growth generated elsewhere, they should contribute to

growth. The approach paper also suggests use of rural development funds

for enhancing the budgetary allocation and successful rural development

schemes. From the past experiences the growth ratio of GDP has been

such as to double the per capita income over approximately twenty years.

There have been suggestions, for doubling the per capita income in 10

years. This was considered to be possible only if the growth rate be around

8.7 percent in 10th and 11th plans keeping in view the population growth at

about 1.6 percent per annum. The tenth five year plan projected an

annual growth of 8 percent. It was also considered that growth projected

in the national plan get influenced by some other factors so it was desired

to set up monitor table targets for few indicators. The monitor Table targets

were identified as follows:

130

Table – 5.3 Monitorable Targets

Key Indicators By 2007 By 2012

1. Reduction of poverty By 5 percent By 15 percent

2. All Children in schools by 2003 to complete 5 years of

schooling

3. Reduction in gender gap in

literacy and wage rates

50 percent

4. Reduction in rate of population

growth decade wise

16.2 percent Between 2001-11

5. Increase in literacy rates 75 percent

6. Reduction in infant mortality rate 45 per 1000 28 per 1000 by 2012

7. Reduction in maternal mortality

rate

2 per thousand live births 1 per thousand live births

8. Increase in forest and tree cover 25 percent 33 percent

9. Sustained access to portable

drinking water in villages

Within the plan period for

all villages

10.Cleaning of major polluted rivers. By the end of plan period Other rivers

11.Gainful and high quality

employment

Addition at least to the

labour force over the 10th

plan period

Though the plan projected 8 percent growth but for doubling the per

capita income in 10 years instead of 20 years there was deficiency by 0.7

percent if all the parameters would have gone well to the expected

targets. Accordingly, the few key indicators as placed in the table were

considered of relevance and importance for attainment of objectives of

the tenth plan. The strategy adopted in the 10th plan can be summarized

as follows:

(i) The role of government in view of emergence of vibrant private

sector.

(ii) Provision and development of infrastructure for overall economic

growth.

(iii) Adopting flexibility in fiscal and monetary policy.

(iv) Balanced development of all states of Indian Union and for

recognizing state-wise break-up of broad development of targets.

131

(v) To ensure equity and social justice. This aspect consist of making

agriculture development as a core element of the plan in order to

ensure rapid growth in those sectors which likely create gainful

employment opportunities and supplement impact of growth with

special programs aimed at target groups.

(vi) The plan laid emphasis on completion of ongoing projects,

privatization of public enterprises especially those working below

capacity besides legal / procedural changes for quick transfer of

assets etc.

The outlay envisaged for the tenth plan was Rs.1968815 cores at

2001-02 prices comprising of an outlay of Rs.706000 crore for central plan,

Rs.588325 crore for state plans. However, for public sector enterprise the

outlay envisaged was Rs.674490 crore.

The targets fixed for the tenth plan lay their dependence on expected

reduction in Incremental Capital Output Ratio (ICOR) from 8.53 during the

9th plan to 3.50 in the tenth plan. For investment a target of 28.4 percent of

GDP while for domestic savings the same was expected by about 6

percentage points of GDP. A tabular picture for Macro Economic

Indicators and Macro-parameters for the tenth plan is given hereunder in

two different tables:

Table – 5.4 Tenth Plan: Macro Economic Indicators

Target 2002-07 Actuals 2002-07

GDP Growth 8.00 7.80

Growth in Agriculture 4.00 3.42

Growth in Industry 8.90 8.74

Growth in Service Sector 9.40 9.30

Investment Rate (%of GDP) 28.41 28.10

Domestic Savings (%of GDP) 23.31 26.62

Average Inflation based on CPI 5.00 5.02

132

The 10th Plan Macro Economic Indicators when given a graphic shape

reflect their respective position as provided in Graph 5.1 below:

GRAPH: 5.1

Tenth Plan Macro Economic Indicators

0

5

10

15

20

25

30

GDP Growth Growth in

Agriculture

Growth in

Industry

Growth in

Service

Sector

Investment

Rate (%of

GDP)

Domestic

Savings (%of

GDP)

Average

Inf lat ion

based on

WPI

Traget 2002-07

Actuals 2002-07

Table – 5.5 Macro-parameters for the Tenth Plan

Items Ninth Plan Tenth Plan

Domestic Saving rate (Percent of GDP mp) 23.31 26.84

Current account deficit (Per cent of GDP mp) 0.91 1.57

Investment rate (Per cent of GDP mp) 24.23 28.41

ICOR 4.53 3.58

GDP Growth(Per cent per annum) 5.35 7.93

GDP mp : Gross Domestic Product at market prices

ICOR : Incremental Capital Output Ratio

Source : Tenth Five Year Plan Document

133

Eleventh Five year Plan:

The eleventh five year plan from 2007 to 2012 laid its emphasis for

setting up economic growth rate at 9 percent in comparison to 7.6 percent

recorded during the Tenth Plan. For this objective in view, the total plan

outlay has been placed at Rs. 3644718 crore. The contribution of the

Central Government for the plan outlay will be Rs.2156571 crore while that

of the State Governments the same will be Rs.1488147 crore respectively.

The outlay includes the public sector enterprises of the Centre and State

Government also. The eleventh plan proposes growth increase in

agriculture to 4 percent from 2.13 percent of the 10th plan. For industry

growth target has been kept at 9 percent against 8.74 percent in the tenth

plan. While for Service sector it is kept at 11 percent against 9.28 percent

of growth rate achieved in tenth plan. The aforesaid figures are apparent

to suggest that proposed outlay of the eleventh plan is larger than the

projected outlay as well as the actual targets achieved in the tenth plan.

The plan outlay for the current eleventh plan is 120 percent higher than the

tenth plan realization. In comparison to GDR the projected outlay for the

public sector in eleventh plan is an average of 13.54 percent in comparison

to the average of 9.46 percent achieved in the tenth plan. It is also clear

that plan expenditure is not deemed to be the same as public investment

as it includes revenue expenditure on items like salaries, etc which in fact is

in rise because of the focus of the plan having shifted its support to social

sectors especially health and education. The objectives and features of the

draft plan are as follows:

(i) The tenth plan recorded 30.8 percent savings rate while it is envisaged

at 34.8 percent.

(ii) The investment rate in the tenth plan being 30.8 percent is expected

to be raised to 36.7 percent in the present plan.

134

(iii) Attention towards reducing the poverty and generating employment

for which purpose a 10 percent reduction in poverty and generating

7 crore new employment opportunity has been agreed.

(iv) Attention toward villages‘ rural electrification of all villages in India is

targeted.

(v) The thrust of the plan will be on social sector including agriculture and

rural development.

(vi) The stress on education by increasing allocation to 19.36 percent of

GDS from 7.68 percent in the tenth plan. To be precise the Central

Government is spending Rs.275000 crore on education during the

eleventh plan when in the tenth plan such expenditure was only

Rs.62238 crores.

(vii) The eleventh plan makes much focus on infrastructure including

irrigation, drinking water and sewage. And the investment towards

the referred sector has been raised to 9 percent by 2011-12 in

comparison to 5 percent of gross domestic product.

The analysis of the eleventh plan reveals that the plan makers are

trying to strengthen the development process which can ensure overall

improvement in quality of life of the people especially the poor, SCs /STs,

other backward castes including minorities and women. A target of 9

percent GDP growth is visualized in this plan knowing well that the current

economy is much more integrated with the global economy with all

benefits and drawbacks. It is professed that if the nine percent growth in

the GDP is achieved then the targets fixed earlier to double India‘s

economic growth within ten years could be achieved. The growth so

envisaged is broad based and ensures equal opportunity for all being inter-

related with expectations for reducing poverty, creating employment

opportunities, access to health and education particularly for the poor,

education and skilled development, opportunities under National Rural

135

Employment Guarantee, sustained environment, recognition of woman

power and good governance.

The plan has also laid emphasis on agriculture, industrial growth and

special focus on service sector. The observation in the eleventh plan clearly

mentions that Export growth in the 9% growth scenario would have to be

nearly 26% per year instead of the 16.4% necessary if agriculture grows at

4%. Such very high export growth requirements may not be easily

attainable, despite the recent performance. Therefore, a strategy aiming

at acceleration in the growth rate should provide for acceleration in

agricultural growth not only because it is more consistent with reducing

poverty and generating income in rural areas, but also because it is more

consistent with the likely constraints on export performance. Keeping in

view this requirement, 11th plan sets a target of 4% growth rate in

agricultural sector.

The eleventh plan has taken into consideration the hindrances for

growth in the field of industry especially in manufacturing sector but has the

growth target of 10 percent for the industrial sector while for its

manufacturing same has been kept at 12 percent per annum. It has been

perceived that absence of infrastructure especially power, dearth in skilled

manpower, Inspector Raj, and lack of labour flexibility are the hurdles in this

sector. Accordingly, the plan lays emphasis on infrastructure and skilled

formation of human resources, besides attention towards other areas for

the purpose. The plan also ensures that women must participate as equals

and the plan suggests for providing the facilities /amenities like crèches,

toilets, hostels and maternity benefits as the case may be. As already said,

that the eleventh plan has led special focus for service sector as same

accounts for 54 percent of GDP. This sector is faster growing sector of

Indian economy. Its growth rate is calculated at 9 percent per annum since

1990. The growth reflected is due to labour cost at the lowest coupled with

rising share of working age population. In short, the plan lays its focus on this

136

sector to create more employment opportunities towards the individual

economic growth and growth of the country in totality, once the targets

fixed by the plan are achieved which in fact being towards Income and

poverty, Education, Health, Women and Children, Infrastructure,

Environment, etc. including Agriculture, Industry and Service Sector.

To sum up, a brief of the economic growth in percentage with

respect to 5-year plans from time to time since first five year plan can be

given in tabular form as under:

Table – 5.6 Growth Performance in the Five year Plans in % per annum

Plan Period Target Realization

8. Sixth Plan (1980-85) 5.2 5.5

9. Seventh Plan (1985-90) 5.0 5.6

10. Annual Plan (1990-92) - 3.4

11. Eighth Plan (1992-97) 5.6 6.5

12. Ninth Plan (1997-02) 6.5 5.5

13. Tenth Plan (2002-07) 7.9 7.7

14. Eleventh Plan (2007-12) 9.0 -

The Growth Performance in Five Year Plans with respect to Targets and

Realization from 1st to 10th Plan are graphically demonstrated in a manner

as provided in Graph 5.2

GRAPH: 5.2

0

1

2

3

4

5

6

7

8

9

First Plan

(1951-56)

Second

Plan (1956-61)

Third Plan

(1961-66)

Fourth

Plan (1969-74)

Fifth Plan

(1974-79)

Sixth Plan

(1980-85)

Seventh

Plan (1985-90)

Eighth

Plan (1992-97)

Ninth Plan

(1997-02)

Tenth Plan

(2002-07)

Growth Performance in Five yr Plans

Target

Realization

137

The implication of planning from first plan propounded in 1950-51 to

9th Plan (1997-2002) reflects that the national income has increased from

Rs.132367 crores to Rs.1115157 crores. The figure arrived is at 1993-94 prices.

All this indicates a compound growth rate of 4.3 percent per annum. The

per capita income can be assessed to have increased 2.9 times from

Rs.3687 to Rs.10754 again at 1993-94 prices. Thus, indicating a compound

growth rate of 2.1 percent at the aggregate measured at factor cost at

1993-94 prices.

Proceeding further, the implication of the plans can also be seen in

sectoral growth as deliberated upon, however, for summation purposes

same can be presented sector-wise in tabular form after globalization and

since the 8th plan1992-97. The perusals of the data derived are reflected

hereunder:

Table – 5.7 Sector-wise Growth from 8th Plan onwards in % per annum

Sector

Eighth Plan

(1992-07)

Ninth Plan

(1997-2002)

Tenth Plan

(2002-07)

Eleventh Plan

Targets (2007-12)

1.Agriculture

2. Industry

3. Services

4. Total

4.72

7.29

7.28

6.54

2.44

4.29

7.87

5.52

2.30

9.17

9.30

7.74

4.0

10-11

9-11

9.00

The research work has also dealt with the aspect of growth in its

national income, savings, investment, capital formation, prices and

production etc., however, it is thought prudent to ascertain the macro-

economic parameters of 10th and 11th plan at its 2006-2007 prices as an

instance instead of repeating what has already been dealt at different

places in this work. Accordingly, a tabular presentation for macro

economic parameters for the referred plans at referred prices is provided

hereunder:

138

Table – 5.8 Macro-economic Parameters

(at 2006-07 prices)

Tenth

Plan

Eleventh

Plan

1 Investment Rate (%of GDP mp) 32.4 36.7

2 Domestic Savings Rate (% of GDP

mp)

30.9 34.8

3 Current Account Deficit (% of

GDP mp)

1.5 1.9

4 ICOR 4.3 4.1

5 GDP Growth Rae (% per annum) 7.5 9.0

Note : GDP mp = GDP at market prices

The implication of planning and policies in India has resulted in

growth with price movement thereto. Though the growth reflected in the

data and deliberation made in this research work do not reveal

consistency, because of economic and non-economic factors including

global scenario of present two decades in which India is placed in the

open market. The second five year plan followed by three annual plans

and beginning of the fourth five year plan have mostly got influenced and

derailed by unforeseen factors mostly attributed to non-economic issues

like draught, flood, war etc. with myopic considerations while framing the

referred plans. The movement of the prices from plan to plan and the

inflation thereto with GDP etc, have been deliberated in this research work

and reference towards that can be made to chapter first itself. All the

deliberations in this work especially in the chapter under discussion leaves

no scope to express contrary with respect to policy implication which brings

forth the price movement and in consequences economic growth in

developing economy like India. But however it still convinces one to express

that the pace of growth has not been as desired in the plans and /or

policies made there under though the government by now since the 10th

plan adopted ‗Monitorable Targets‘ for few key indicators of the economy

139

which in fact reflect government perception and concern towards

economic development and price movement. Everything is left to the

future as to its unfolding of events concerning country‘s economy,

development and the price movement thereto, a co-relation of all

warranted for successful operation of plans and policies.

2. Fiscal policies:

Though the policies are framed under five year plans and

implemented from time to time, the fiscal and monetary policy also assume

importance for carrying out the objectives of the polices in plans in a way

showing direct relation with the prices and their movement. It is true that in

India‘s planned economy, the fiscal policy pertains to use of government

expenditure and revenue collection to influence the economy. The fiscal

policy has two broader perceptions of government expenditure and

taxation. The government expenditure and taxation has a bearing on

aggregate demand and economic activity, the trend of resource

allocation besides distribution of income. Accordingly, it is the government

budget which refers to the fiscal policy to influence the referred economic

activity. The fiscal policy has its three stances namely Neutral, Expansionary

and Contractionary. All the referred stances have bearing on the economy

including that of price movement. The taxation as an integral part of fiscal

policy has from time to time provided savings with tax incentives by

exemption/deductions etc59. The savings in turn add to general national

savings in a way generating income and other allied activities including

capital formation etc. The price movement is a fact and its economic

development a consequence. The movement of prices on a sample basis

can be deduced also from the guidelines of Central Government

59 Reference can be made to the Income Tax Act, 1961 with Rule thereto and

Notification issued from time to time regarding ‗National Saving Schemes‘ etc.

under Section 80CCA, 80CCB and various other provisions thereto.

140

contained in its Notification60 regarding cost Inflation Index. The

Notification covers Cost Inflation Index from the financial year 1981-82 to

2007-08 with cost inflation index at 100 in the base year of 1981-82. For

details a tabulation presentation is provided hereunder:

Table – 5.9 NOTIFICATION OF CENTRAL GOVERNMENT REGARDING COST

INFLATION INDEX FOR THE PURPOSE OF LONG TERM CAPITAL GAIN

Financial

year

Cost

inflation

index

Financial

year

Cost

inflation

index

Financial

year

Cost

inflation

index

1981-82 100 1990-91 182 1999-00 389

1982-83 109 1991-92 188 2000-01 406

1983-84 116 1992-93 223 2001-02 424

1984-85 125 1993-94 244 2002-03 447

1985-86 133 1994-95 259 2003-04 463

1986-87 140 1995-96 281 2004-05 480

1987-88 150 1996-97 305 2005-06 497

1988-89 161 1997-98 331 2006-07 519

1989-90 172 1998-99 351 2007-08 551

GRAPH 5.3

60

Notification of Central Government regarding cost inflation index for the purpose of long term

capital gain appearing in Taxmans “Direct Taxes Ready Reckoner” by Dr. Vinod K. Singhania Edition

31ist

2008-09 & 2009-10.

0

100

200

300

400

500

600

Years

Cost inflation index

Cost inflation index

141

From the aforesaid Table price movement and policy implication

becomes explicit. Implication so deduced reveal that the price movement

with respect to immovable property have gone up from 100 in 1981-82 to

551 in 2007-08 an increase approximately by 5.5 times. The taxation on the

capital gains on one hand has shown ascending price movement and on

the other an indicator towards assesses position with respect to his capital

appreciation for tax purposes and in totality indicating the price movement

though with respect to a particular sector in the economy.

On further probe in areas of taxation61 it is seen that during the initial

years of planned economy Taxation was considered one of the revenues

to the Government. Taxation with variable slabs has been in vogue

especially with respect to Income Tax as direct Tax. For assessment year

1965-66 the lower minimum income exempted for tax purpose was

increased to 3000 thereafter for four consecutive years, the exemption was

raised to 3,500/-. However, for assessment year 1970-71 exemption was

increased to 5000/- and remained so for four years upto 1973-74. For

subsequent two years exemption of income for taxation was increased to

6000/- but for assessment year 1976-77 the exemption was again increased

to 8000/- . The assessment year 1977-78 to 1979-80 witnessed the increase in

exemption of income upto to Rs.10,000/-. In 1980-81 exemption increased

to Rs.12,000/- thereafter for succeeding four years it increased to

Rs.15,000/=. The assessment year 1985-86 to 1989-90 saw the increase upto

Rs.18,000/-. The year 1990-91 and 1991-92 the exemption slab for income

tax purposes increased to Rs.22,000/- while for assessment year 1992-93 it

was increased to Rs.28,000/- and for assessment year 1993-94 the

exemption increased to Rs.30,000/-. The assessment year 1994-95 witnessed

61 Based on data derived from various sources including websites of Ministry of

Finance (finmin.nic.in/kelkar/chp4dt.pdt).

142

the exemption of income for tax purposed upto Rs.35,000/-. It is also seen

that the assessment year from 1995-96 to 1997-98 the exemption of income

for taxation purpose reached Rs.40,000/- thereafter it increased to

Rs.50000/- since the assessment year 1998-99 and continued so. The

assessment year 2009-10 and 2010-11 the exemption for tax purposes

increased to Rs.1,60,000/= for male and Rs.1,90,000/= for female, besides for

Senior Citizens it was increased to Rs.2,40,000/-.

On further assessment and analysis, tax payers in 1965-66 were

21,26,398 while in 1970-71 the number of tax payers increased to 32,30,000.

But for 1975-76 the number of taxpayers increased to 36,37,434. In 1980-81

the number of tax payers increased to 41,75,615. The year 1985-86 the

number of taxpayers increased to 49,37,657. The 1990-91 has touched the

figure of tax payers at 89,34,442. While in 1995-96 the number of taxpayers

increased to crores actually being 1,32,08,781. The year 2000-01 has given

the tax payers figures as 2,50,52,380. For year 2009-10 the gross tax revenue

has been 626916 Crores and the budgeted estimates for 2010-11 has been

746651 Crores62 .

It is also derived that contribution of tax deducted at source

introduced in year 1990-91 added revenue to the government from time to

time. From the cursory perusal of the records gross collection of tax in crores

only on this aspect in 1990-91 has been to the tune of Rs.6188.37 crores

while after five years for assessment year 1995-96 same increased to

Rs.22949.61 crores. After another five years in assessment year 2000-01 the

gross collection in crores is reflected as Rs.35162.61. The year 2003-04 as far

as availability of data reveals the gross collection merely from TDS as

Rs.48454 cores.63

62 Economic Survey 2010-11, p 47. 63 Report of the Comptroller and Auditor General (Direct Taxes), Government of India,

2005.

143

From all this, it is clear that fiscal policy yields revenue to the

government and in turn helps government in undertaking various

expenditures including those required for plan expenditure and for

implementing the plans. The policy has a relation with government

functioning, economic development and price movement. The tax policy

itself is evidence with respect to movement of prices or in short what can

be termed as incomes attributed to individuals. The exemption slabs from

the minimum of Rs.3,000/- in 1965-66 when compared to current exemption

of Rs.1.50 lakh or 1.90 lakh for females or 2.40 for Senior Citizens as the case

may be requires no proof to establish the prices in general and the

movement thereto including the segment of earnings of individuals,

companies, firms etc. In short, the fiscal policy has its own implication and

has an impact on the price movement and economic development,

especially when seen in conjunction with five year plans and other macro-

economic policies like monetary policy and the money policy.

It cannot be forgotten that the country faced macro-economic

problem in 1991 when the expenditures have gone beyond conventional

government budget deficits adding to off-budget liabilities in the nature of

actual and contingent liabilities. The situation has arisen because of lack of

attention in keeping the fiscal balance. It was perceived that a fiscal deficit

of around 9.5 % of GDP mainly contributed to the situation. However, due

to policy implications the fiscal deficit has been kept at 6.4 % of GDP and

the growth accelerated to 7.5 % in 1996-97. Proceeding further, the

subsequent years have shown widened deficit, again drawing India‘s

attention towards its fiscal policy. The fiscal policy has played hide and

seek from time to time but what is of essence, is the relevance of fiscal

policy in achieving economic targets coupled with growth. The fiscal

policies with monetary policy are the wheels for sustaining economic

stability and achieving the goals propounded in five year plans. Three

policies together are supplementary and complementary to one other with

144

the result yielding to the results/ implications depending upon

sufficiency/deficiencies of the policies.

The fiscal policy as drawn from year to year has substantial reference

to the particular year vis a vis to economic development, expenditure,

taxation and price movements including inflation, deflation through which

country may be passing. If on one hand, price movement is said to be an

economic development but excess of the movement can be said to be

obscenity affecting the body polity. A balance has to be drawn between

the movement of the prices and permissible pocket links of the general

masses in India. The heavy dose of accelerated price movement can

prove fatal and disastrous so balanced fiscal policy is the solution negating

expansionist and contractionists approach in the fiscal matters. India need

to be very cautious while entering into global economy for becoming a

global player. The report made in Mackinsey Quarterly 64cannot be

ignored, wherein it is observed:

―Future Financial crisis could accelerate the rebalancing of global

economic activity from developed to emerging markets. The strategic

implications – which touch on everything from company‘s manufacturing

footprints to the customers they target to how they structure their balance

sheet – are profound.‖

In an article addressed to Reserve bank of India 65 the attention of the

Bank was drawn towards the fiscal deficit and the link between various

economic parameters thereto including inflation and price movement. It

was expressed:

―The link between fiscal deficit and growth, saving and investment

rates, inflation and current account deficits has also been examined in

64

―Globalization‘s critical Imbalances‖ by Lowell Bryan, published in Mckinsey

Quarterly 2010 November 3, Mckinsey & Company 55 East 52nd Street, New York

2011. 65 Fiscal Deficits and Government Debt in India: Implications for Growth and

Stablisation dated January 12, 2004 addressed to Reserve Bank of India.

145

many studies. The relationship between fiscal deficit and interest rate and

the existence of crowding out are importance considerations in

determining the advisability of deficit financed expansionary fiscal policies.

Authors like Sunderarajan and Thakur (1980); Pradhan etc (1990); and

Parker (1995) had earlier examined the issue of crowding out in the Indian

context. More recently, Chakraborty (2002) finds that fiscal deficit does

not put upward pressure on the interest rate while Goyal (2004) using

monthly data argues that there is a two-way causality fiscal deficit and

interest rates. In his view, interest rate did not rise in recent years in spite of

high fiscal deficits because of larger liquidity available to the system….‖

In the context, the fiscal policy ought to be read in conjunction with

five year plans deliberated upon hereinbefore and with monetary policy

and its implication on development and price movement which is being

dealt hereinafter.

3. Monetary policies:

Monetary Policy also assumes importance among others with respect to

price movement in an economic set-up of a country. The monetary policy

has its origin in nineteenth century particularly for maintaining the gold

standard then, however, the monetary policy has been formulated

separate and distinct from fiscal policy since 1970. It is through monetary

policy, that country‘s monetary authority as regulator controls the money

supply usually by targeting interest rate. Shri Rangarajan66 while

commenting on monetary policy observes its importance as under:

―Monetary policy is an arm of macro-economic policy and, its role

and importance are determined in any economy by the overall policy

framework and the various instruments available for implementing policy.

As opposed to fiscal policy, which rests on instruments such as Government

66 Indian Economy : Essays on Money & Finance by Rangarajan, Chapter-5 ‗Dimensions of

Monetary Policy‘, pp 59,60.

146

expenditure, taxes and borrowings, monetary policy acts through

influencing cost and availability of credit and money.‖

……………

―…..in a broad sense, the objectives of monetary policy can be no

different from the overall objectives of economic policy. The broad

objectives of monetary policy in India have been:

(1) To maintain a reasonable degree of price stability and

(2) To help accelerate the rate of economic growth.

The emphasis as between the two objectives has changed from year to

year depending upon the conditions prevailing in that year and in the

previous year.‖

The purpose of the policy can be to promote economic growth, stability

and to check inflation and deflation for desired price movement. Deena

Khatkhate67 while referring to the instrument of money policy observed:

―The principal instruments of money policy are interest rates and

selective credit controls, reserve requirements, credit ceilings, refinancing

facilities is, in some instances open market operations and exchange rate

policies.‖

The same writer68 speaks about the price objectives and ability of the Central Bank to

anticipate public demand for money, further observes:

―……..The relation between the nominal stock of ‗money‘ on the one side,

and price as outputs, and the balance of payments, on the other hand, is

determined by the public demand for money. The price effects of the

public‘s adjustment of its spending (on real or financial assets) when the

real value of its money holdings differs from desired levels, convert ‗given‘

nominal money balance, into the desired real quantity. This process

67 Money & Finance by Deena Khatkhate, p 37, published for Sameensha

Trust…Orient Longman, Mumbai 1998. 68 Ibid page 41

147

provides the link between nominal money and the price level. Its successful

exploitation by Central Banks for attainments of their price objectives

depends upon their ability to accurately anticipate the public demands for

money.‖

While on the same subject Vidya Mahambare69, observes about ‗Limits

of Monetary Policy‘ and concludes:

―The role of the monetary policy is to safeguard the purchasing power of our

money and thereby maintain an environment conducive to growth. Expecting it

to do anything more can only derail our growth story.‖

In India, Reserve Bank of India acting as monetary authority adopts

expansionary or contractionary measures resulting in supply of the money

in the economy rapidly than usual or supply of money slowly than usual.

The policy by these measures influences the outcome of economic growth,

inflation, exchange rates with other currency and un-employment.

The learned author J.D.Sethi 70 while dealing with the subject has expressed the

functions of Monetary Policy and the directions it may take as:

―….(i)To have and also to make use of a most suitable interest rate

structure. (ii) To achieve a correct balance between the demand for and

supply of money. (iii) The provision of proper credit facilities for a growing

economy and stopping its undue expansion; and also the channeling of

credit to users as consistent with pre-planned investment. (iv) The creation,

working and expansion of financial institutions. (v) Debt Management.‖

In short, the method and tools adopted by the monetary policy usually

include increasing interest rates, reducing the monetary base and

69

Vidya Mahambare, Senior Economist CRISIL in statement reproduced in The Financial Express

Lucknow Wednesday May 28, 2011,p 9. 70 Problems of Monetary Policy in an Underdeveloped Country by J.D. Sethi, p 94.

148

increasing reserve requirements71. Towards these ends, the policy makers

ought to have credible announcement, clarity in the policy and reliability.

The learned authority James Forder 72 says:

―Despite the frequent discussion of credibility as it relates to monetary

policy, the exact meaning of credibility is rarely defined. Such lack of

clarity can serve to lead policy away from what is believed to be the most

beneficial. For example, capability to serve the public interest is one

definition of credibility often associated with central Banks. The reliability

with which a central Bank keeps its promises is also a common definition.

While everyone most likely agrees a central bank should not lie to the

public, wide disagreement exists on how a central bank can best serve the

public interest. Therefore, lack of definition can lead people to believe they

are supporting one particular policy of credibility when they are really

supporting another.‖

The monetary policy being macro-economic policy in an economic set-up

and is in contrast to fiscal policy with an object to stabilize the economy by

putting control on the money supply and the interest rates. The Reserve

Bank of India from time to time has taken major monetary policy measures

especially concerning Bank rate, Cash Reserve Ratio and Statutory Liquidity

Ratio. At its inception the Reserve Bank of India by virtue of Act of 1934 the

Bank Rate was fixed at 3.50 w.e.f. 5.7.1935. The Bank Rates have been

increased/decreased from time to time keeping in view the economic

scenario including money market in the country. The Bank Rates are

considered having bearing on the price movement and also economic

development in the areas of Savings, deposits, credit take off etc. A brief

71 Refer to The Banking Regulation Act, 1949 especially Sections 17 and 18

pertaining to Reserve Fund and Cash Reserve read with the Reserve Bank of

India Act 1934. 72 James Forder in Economic Journals Watch December 2004 in article

―Credibility in context : Do Central Bankers and Economists Interpret the

Term Differently ?‖

149

major monetary policy measure concerning Bank Rate can be presented

in a tabular form since the inception of Reserve Bank of India itself in a

manner as follows:

Table – 5.10 Major Monetary Policy Measures73Concerning Bank Rate

Effective Dated Bank

Rate

Effective

Dated

Bank

Rate

Effective

Dated

Bank

Rate

Effective

Dated

Bank

Rate

5.7.1935 3.50 9.1.1971 6.00 22.10.1997 9.00 17.2.2001 7.50

28.11.1935 3.00 31.5.1973 7.00 17.1.1998 11.00 2.3.2001 7.00

15.11.1951 3.50 23.7.1974 9.00 19.3.1998 10.50 23.10.2001 6.50

16.5.1957 4.00 12.7.1981 10.00 3.4.1998 10.00 30.10.2002 6.25

3.1.1963 4.50 4.7.1991 11.00 29.4.1998 9.00 30.4.2003 6.00

26.9.1964 5.00 9.10.1991 12.00 2.3.1999 8.00

17.2.1965 6.00 16.4.1997 11.00 2.4.2000 7.00

2.3.1968 5.00 26.6.1997 10.00 22.7.2000 8.00

GRAPH 5-4

This apart, the monetary policy of the Reserve bank as a Central

Bank envisages Cash Reverse Ratio, Statutory Liquidity Ratio besides fixing

Repo and Reverse Repo Rate. These measures as comprised in monetary

policy act as an appendage to the economic policy propounded in plans

73 Hand book on Statistics on Indian economy 2009-10 , Money & Banking Table 46 ,

Reserve Bank of India 15th September 2010 (www.rbi.org.in/scripts/Publications

view.aspx)

0

2

4

6

8

10

12

14

Dates

Bank Rate

Bank Rate

150

and for fiscal policy formulated by the government from time to time.

Keeping in view, the economic scenario and inflation /deflation, the

movement of the price the Reserve Bank of India monitors the situation and

provides desired measures. In addition to the Bank Rate, Cash Reserve

Ratio when studied reveals that it was kept at 5% of DL and 2% of TL since

5.7.1935. The Statutory Liquidity Ratio was introduced w.e.f. 16.3.1949 and

was fixed at 20%. From time to time there have been variations in Bank

Rate, however, w.e.f. 16.9.1962 the Cash Reserve Ratio was kept at uniform

3.00% of NDTL which continued to remain so till it was increased to 5.00%

w.e.f. 20.6.1973, thereafter to 6.00 w.e.f. 8.9.1983 and reached 7.00% from

22.9.1973. The Cash Reserve Ratio has shown up and down with minimum

4.00 w.e.f. 28.12.1974 and again was increased to 7.00% w.e.f. 21.8.1981.

Since27.11.1981 Cash Reserve Ratio was increased from time to time and

finally was kept at 15.00% w.e.f. 6.8.1984 and remained so upto 10.11.1995

when it was reduced to 14.50% effective from 11.11.1995. After this Cash

Reserve Ratio has shown constant decline and was kept at 9.50 % w.e.f.

22.11.1997. It has shown up and down by .50% or .25% but not exceeding

1.00 and w.e.f. 6.11.1999 it was reduced to 9.50. Just after 14 days it was

again reduced to 9.00. Thenceforth, it has seen constant reduction and

w.e.f. 18.9.2004 Cash Reserve Ratio was maintained at 4.75, which

increased time to time and finally w.e.f. 30.10-.2008 it reached 9.00 and

continued so upto 10.10.2008. From 11.10.2008 Cash reserve ratio was

again reduced to 6.50% and earlier trend of reduction is seen continuously

and w.e.f. 17.1.2009 it was kept at 5.00 and continued so when on

13.2.2010 it was increased to 5.50. But subsequently increased to 5.75 w.e.f.

27.2.2010.

Regarding other monetary policy measures, it is gathered that

Reserve Bank of India introduced Statutory Liquidity Ratio for the first time

w.e.f. 16.3.1949 and was considered to be kept at 20.00. It was increased

from time to time and finally w.e.f. 29.9.19990 it touched 38.50, the peak

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from the date of inception till date. During the referred period of 41 years,

the increase in Statutory Liquidity Ratio was made almost 19 times.

However, w.e.f. 9.1.1993, it was reduced by 25 was kept at 38.25 and a

continuous reduction was made from time to time and it is seen that w.e.f.

8.11.2008 the Statutory Liquidity Ratio was reduced to 24.00 thereafter,

again increased to 25.00 w.e.f. 7.11.2009.

The other measures adopted by the Monetary Policy authority like

Reserve Bank of India have been with respect to Repo and Reverse Repo

Rate wherefrom it is gathered that Repo rate was fixed at 9.00 while

Reverse Repo was kept at 6.75 w.e.f. 27.4.2001. There has been constant

decline in both rate from time to time. However, w.e.f. 31.3.2004 Repo rate

came down to 6.00 while from 25.8.2003 Reverse Repo Rate touched 4.50.

Thereafter, both rates have shown increase, Repo Rate from 30.7.2008 was

increased to 9.00 from 8.50 fixed on 25.6.2008. On the other, The Reverse

Repo increased to 6.00 w.e.f. 25.7.2006 from its 5.75 fixed on 8.6.2006. The

Repo Rate continued to remain so when it was reduced to 5.00 w.e.f.

8.12.2008. Since then it has come down to 4.00 on 5.1.2009, 3.50 on

5.3.2009, 3.25 on 21.4.2009, 3.50 on 19.3.2010 and increased to 3.75 on 20.4.

2010.

The aforesaid measures are instances which are taken under the

monetary policy with implications to stabilize price movement in tune with

desired objectives and to tackle currency fluctuations / undesired price

rise. Recently, Reserve Bank of India in its Macro-economic and Monetary

Development Report74 expressed:

―The inflation outlook, which is being conditioned by both demand-

side and supply-side factors, suggests slow-paced moderation in inflation,

with the possibility of rigidity at above the comfort level in the near term.‖

………

74 Business Standard Tuesday 25th January 2011, Lucknow, p 1, Column 1 & 2.

152

―The anti-inflationary focus of the monetary policy would have to

continue, recognizing the limits of monetary policy in dealing with structural

pressures on inflation, and the need for forward-looking response to

demand-side pressures. Since a lower inflation regime is essential for

sustainable high growth, containing inflation becomes the dominant policy

objective in the current environment.‖

Though the monetary policy has its own limitations, but it definitely

influences the price movement directly and indirectly. The directly as

suggested hereinbefore through the intervention of the Reserve Bank of

India while indirectly any measure taken under monetary policy helps in

credit inflow, savings, capital formation coupled with agricultural and

industrial growth besides other activities, in short acting as an aid to

economic development and in stabilizing price movements. A glance at

growth of deposits and advances from time to time and increase in

customer itself is an evidence towards the implications of monetary policy

and the system including Bank and financial institutions through which it

works. The importance of the monetary policy in India‘s economic

development can be summarized by reference to observations of the

Parliament while passing the Legislation towards Securitisation and

Enforcement of Security Interest by the Bank and Financial institutions.75

The relevant portion of the statement of object and reasons as introductory

to the Act of 2002 is appended:

―The financial sector has been one of the key drivers in India‘s efforts to

achieve success in rapidly developing its economy……….‖

Despite the aforesaid fact there is no dearth for adverse comments

more so when seen from the perspective of common mans interest rather

than economic development and price movement relation towards

75 Statement of Objects and Reasons while passing the Securitisation and Reconstruction of

Financial Assets and Enforcement of Security Interest Act, 2002 (54 of 2002).

153

country‘s growth. Morgan Stanley Report as partially appearing in print

media76 is relevant for reference wherein it say‘s:

―……Indian households are likely to cut back on consumption of food

items further to manage inflation. It also speaks about headline inflation has

been above 8% since 2010. Latest data shows that it stood at 8.66% in April

2011‖

The report also mentions about RBI monetary policy and says ―The RBI, in its

monetary policy for 2011-12, released earlier this month, had said that

international commodities prices are a major area of concern. It had

projected headline inflation to average 9% during the first half of the fiscal,

before moderating to around 6% by year end.‖

A passage from an article published in ―Inclusion‖77 can be a ready

reference towards the same and is quoted herein below:

―For many years, India prided itself on being one of the

emerging market economies (EMEs) with the lowest inflation rate. In

contrast, today the Indian inflation rate is one of the highest among the

EMEs. India is probably the only country, which uses the wholesale price

Index (CPI) for purpose of Policy, while most of the countries use the more

relevant Consumer Price Index (CPI). In the recent period, the CPI peaked

at 10 percent while the CPI peaked at 14 percent. Price indices, the world

over, are doctored and the current inflation rate may have peaked at

around 20 percent. Such high rate of inflation devastates the lowest

income basket. Furthermore, the fact that year -on -year inflation rate is

coming down is a mere statistical phenomena which is of no comfort to the

common person. What is relevant to the common person is the level of

prices which continues to remain high and, as such there is no relief for the

common person.‖

76

The Free Press Journal dated May 25, 2011 Edition Mumbai : Business p 21.

77 INCLUSION July-September 2010, Vol. 1 Issue 2

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Commenting upon the monetary policy Shri Rangarajan78 in the context of

India‘s economic development expresses his view as follows:

―Keeping the price and growth objective in view, the money supply growth

should be so modulated that the inflation rate comes down initially to 6 to 7

per cent and eventually to 5 to 6 per cent. That indeed must be the goal of

monetary policy.‖

In the light of deliberations made, it can be conveniently said that

monetary policy acts as an effective tool and a driving force for stabilizing

the price movement in a desired way. The policy as such is an indicator

toward economic development to which its contribution is both in a direct

and indirect way and that being the reason that Government of India

thought to keep it separate and distinct from the fiscal policy.

4. Other policies and their implication on price movement and economic

development.

In addition to policies framed under five year plans, besides, fiscal

policy and monetary policy as deliberated upon there are other policies

like ‗Price Policy‘, ‗Commercial Policy‘ etc. though not of much importance

in the context of topic under research, however, the price policy needs a

reference as an appendage to other policies concerning the topic. Satish

Munjal 79 while dealing with prices as economic phenomena observes

about their implication as beneficial for some and disadvantageous for

others. The learned author says:

―Price level is an economic phenomena which affects all people. But all

people are not affected alike. When price changes some people are

78 Indian Economy: Essays on Money & Finance by Rangarajan, Chapter 5

‗Dimensions of Monetary Policy‘, p 74. 79

Money and Banking by Satish Munjal, published by National Publishing House,

Naipur, New Delhi Ed. 1977, pp 46,47.

155

benefited while others suffer. Effect in rise in price and fall in price is as

follows.‖

The statement made with respect to implications of price level

and/or the movement of prices cannot be denied but the fact remains

that the price movement with it carries an economic development may be

the different persons and affected differently but country as a whole

visualizes a development especially when the movement on prices is in

accordance with desired objective of the plan and policies where the

price policy softens unwarranted edges. Thus, the Price policy usually

comes into being for fixing the prices of procurement commodities by the

government especially with respect to agricultural produce like rice,

wheat, sugar besides industrial raw material, etc. The goods falling under

essential commodities also get attracted under price policy leaving other

consumer goods to the market for price mechanism. The policy also is

being triggered for prices of exportable commodities for the purpose of

foreign exchange and for maintaining balance of payment. The price

policy also determines wages and wage revisions sometimes as a

government policy and usually in pursuance to a Statute like payment of

Minimum Wages Act. The price policy, though not merely concerned with

maintaining the price line by keeping the prices stable at a desired level

but it is concerned with relative price of goods and services vis a vis their

movement in general.

The price policy has its limited bearings but acts direct with respect to

commodities and services coming under its purview. The policy has

importance and implications in a planned economy in its micro-aspect.

The policy in the planned economy is used to encourage resources for the

production of investment and helps for providing basic consumable goods.

It also has a tendency to circumvent inflationary pressures. In India, its use

has been seen to act as stimulant and deterrent. The impact of the price

policy is creation of buffer stocks, making availability of consumable goods

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especially essential commodities and for stabilizing prices and correcting

seasonal and regional variations with respect to prices and their

movement. Again a reference can be made to article in Inclusion

previously referred where the learned author speaks about the inflation of

supply /demand side and makes a critical observation citing ‗onion‘

inflation as propounded to be supply side phenomena. As per the author:

―It is favorable to talk about imperative need to increase the growth

rate and it is claimed that a higher growth rate will enable an effective

triple down effect, which will benefit the weakest segment of society. It is

argued that inflation is the price to be paid for attaining a higher rate of

growth, furthermore it is argued that the inflation currently experienced in

India is supply side and that the monetary-fiscal policies are inappropriate

to tackle such inflation. It is naïve to claim that supply side inflation can be

tackled by increased supplies. It is one thing to label ‗Onion‘ inflation as

supply side phenomena but when inflation is generated as in the present

instance, it is erroneous to call it supply side inflation.‖

Though the aforesaid statement may have some bearings but it can

be said that the policies are limited in scope and limited to time with main

thrust to curtail undesired price movement. On the other ‗commercial

policy‘ has its own importance especially with respect to trade, business,

foreign investment, industrialization, balance of payment etc. The thrust of

the commercial policy towards economic development. Its implications

are more found in under developed countries and developing countries

than developed countries. In short, the commercial policy has indirect

bearing on the prices than other policies like fiscal policy, monetary policy

and price policy, besides, the policies framed under the five year plans.

In conclusion, it is gathered that five year plans with the fiscal policy thereto

and support by the monetary policy help in economic development and

also for keeping the prices at a desired level. The monetary policy provides

the control measures for the inflation deflation and price movement

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thereto while the fiscal policy in India has more concerned with the

government expenditure and taxation. The country has succeeded in its

planned policy ably supported by the fiscal and monetary policy. The price

policy has also side by side helped in making the consumable goods

available besides preventing exploitation of wage earners by fixing the

prices/wages. The deliberation in the chapter have revealed that it is the

planned economy by virtue of which country has developed from its

freedom days till today. If one compares the plan outlay of first five year

plan which was kept at Rs 1960 Crores in aggregate to its current 11th plan

proposed at Rs 3644718 Crores. On the front of agriculture, industries,

capital formation, investment and savings there is overall development at

the progress apparent at current compelling most of the economists and

global countries to admit that India is going to become a vibrant economy

in the very near future. Accordingly, there is no hesitation in concluding

that the policies propounded in the plans duly supported by other polices

have made a distinct impact on India‘s economy with some exception

during the transitory phase of globalization in 1990-91 and/or

nationalization of 1970 besides some stumbling block due to factors other

than economy like war with China and Pakistan in 1962, 1965/1970.

Therefore, while concluding the chapter it is prudent to provide conclusions

in a separate chapter hereinafter and suggestion as the researcher as

derived from the research on the basis of empirical study based on

authentic data‘s derived from various sources.

** ** **

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Chapter VI

Economic Growth and Income Distribution

It is well recognized fact especially in developing economies that the goal

of improving growth prospects need to be supplemented by

developmental objectives which further envisages reduction in disparities

income wise overall reduction of poverty. This idea of developmental

objectives comes into picture with the realization that issues of unequal

distribution of income remain rigid despite rapid pace of growth. In fact a

number of studies exist that brings forth the fact that growth has been

accompanied by widening of disparities of income. Unequal and sporadic

growth has been little or of no benefit to the section which lives on

subsistence level in the developing economies.

The pre postulated belief that growth trickles down and spreads was the

belief among several developing or even in emerging economies, as they

started strolling on the path of development. As a result of this belief

approaches regarding special programs to generate employment

opportunities, poverty reduction and income inequality reduction were

totally ignored. But the faith of solving these problems with growth got

belied with the defeat of trickle down. Todaro (1993) argued that growth

must be perceived as multi dimensional process involving deep changes in

the social framework, popular attitudes and intitutions of national

importance, along with increased pace of development process ,

inequality reduction, and eradication of poverty. Growth in this essence

must represent the overall gamut of modification by which overall social

system, tuned to diverse basic requirement and the desires of society

groups in that system, shift away from a condition of life widely perceived

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as unsatisfactory and towards a situation or condition of life regarded

materially and spiritually well-off.

For the study of income distribution two distinct approaches have been

applied the first one is related to the degree of relative inequality within an

economy and the second with the degree of absolute poverty.

The term relative inequality is like severe problem as it could mean distinct

things like inequality between two individuals, two society groups, two

states or two countries or in simple manner the gap between the rich and

the poor. But the present study concentrates on unequal distribution across

different sections of the society. Such inequalities of income generally are

measured by the extent to which the income shares of different society

groups differ from their population shares.

Traditionally, in such an approach, we study the income shares of bottom

40 per cent group, middle 40 per cent group and top 20 per cent group of

the population. The ratio of the share of top 20 per cent population to that

of bottom 40 per cent is also sometime examined for the purpose. Many

studies Adelman& Morrees (1974), Ahluvalia (1976a), etc. have examined

inequalities in income through such measures.

The concept of absolute poverty on the other hand, could be defined by

the number of population living below the specific minimum level of

income- an imaginary national or international poverty line. In modern

times, economists have widely used the international poverty line drawn at

1 $ per day, set at 1993 purchasing power parity price level.

Both the approaches of Relative Inequality and Absolute Poverty are not

mutually exclusive, rather are quite inter related. Out of these two the first

one is broader in its scope as it studies income distribution across all

population groups of the society while the second approach restricts itself

only to those individuals who live below a certain imaginary national or

international poverty line.

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The long run relationship between income distribution and economic

growth has been has been one of the most closely investigated issues in

economic theory. In his time-immemorial article Economic growth and

Income Inequality, Kuznets (1955) postulated the hypothesis that early

economic growth augments inequality while later economic growth

narrows it down. Kuznets based his hypothesis on an analytical model by

studying the data of European countries in 1930, which showed gradual

reduction in inequality and considering cross country comparisons

between inequality in developed economies and inequality in two

developing economies, which exhibited considerably excessive inequality

in developing economies. This analysis formulated the inverted U shape

hypothesis and proposed the research objective for further studies in order

to establish the relationship between income distribution and economic

growth.

Nevertheless, the first twenty years of economic growth, immediately

witnessing the World War II, proceeded on the positive note of the

relationship between the two. It was believed that the growth of industrial

sector, if sustained, would gradually spread the benefits of growth to all,

including the deprived section of the society. This optimistic assumption

seemed to have empirical justification that the benefits to newly rich urban

sections, to wage earners in the industrial sector and to a widening middle

class of merchants, professionals and civil authorities, were comfortably

apparent while the data on unemployment, and income distribution were

unavailable to throw a cast of doubt on greener scene of the effects of

development (Adelmen, 1992). The inverted u shaped hypothesis, was

although, ignored by all the economists.

In Indian context the policy makers, perceiving the genuineness of the

deep rooted poverty to their midst, were also doubtful towards trickle down

policies fermented to aid the poor and aimed the country‘s five year plans

since 1951, directly towards poverty reduction. (Fuwa, 1992)

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The first case of failure of development of mainstream western economies

were realized in the 1960s, due to the work of ILO, which put forward the

fact that despite of rapid industrialization and GNP growth, unemployment

of the urban labor force were reaching to the alarming level. The

interlinked problem of low labor absorption and rapid growth of

population, education explosion and overdependence of agriculture

created disguised rural unemployment which further created the problem

of low income, low productivity, disguised urban unemployment in the

informal urban sector and escalated of open unemployment for university

graduates(Adelmen, 1992)the realization of these trends revived interest in

Kuznets hypothesis.

Hence, the income distribution issue from the angle of inequality and

poverty, occupied the center stage in growth and development agenda.

During 1970s the initiation of research in distribution of benefits of growth in

developing counties was the main trend. The first major research on the

relationship between income distribution and economic growth was by

Adelman & Morris (1973). Finalized in 1971, as report to the Agency for

International Development, and it was based on unpublished studies on

income distribution in almost 44 countries, their study confirmed the

increase in inequality at early stage of development posited in the Kuznets

hypothesis. It also indicated that the subsequent decrease in inequality

with growth was not automatic. It depended on the certain policy

selections which were made in the course of development process.

Following the study of Adelman & Morris several other economists used

cross section regression to study the relationship of growth and inequality.

Paukert,1973; Bacha,1979; Chenary,1979; Anand & Kanbur, 1984; Papanek

& Kyn, 1987) thses studies used polynomial functional form that is quadratic

in the log of per capita GNP. They also added some policy variables to the

regressions such as education, population or a social dummy variable. The

samples of different economies varied, sometimes including and

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sometimes excluding developed countries. All the regressions confirmed

the existence of Kuznets Curve. Anand & Kanbur (1984), suggested that the

location of minimum point of U is sensitive to the sample composition and

to the specific functional form. Such sensitivity is to be expected if, as

claimed by Adelman & Morris (1973), the underlying relationship at higher

levels of growth is either U shaped or J shaped, depending on the policy

choices made. Papnek and KYN (1986) contradicted the Anand and

Kanbur contwntion, and found the relationship to be stable and insensitive

to the inclusion or exclusion of specific countries. The conditioning variables

they included, however captured the same policy choices that hurt

whether the relationship is U shaped or J shaped. They also found the

Kuznets Curve to be quite flat (Papanek & Kyn, 1987).

The present chapter examines the theoretical relationship between

inequality and economic growth; and poverty and economic growth.

Hence divided into two sections. Section I discusses the concept and

measure of inequality and poverty, while the Section II discusses the

linkages between inequality and Economic Growth.

Section I

Under this section measures and concepts of inequality and poverty has

been discussed. An attempt has also been made to study the pre-

established assumptions related to inequality and poverty.

Inequality

The term inequality refers to different connotations: it sometimes refers to

inequality between the economies that is the gap between one rich

economy and one poor economy, difference in economic development

of different states within the same country and inequality amongst different

sections of the society. Atkinson (1975) offered a comprehensive review on

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inequality issues. He was of the view that defining inequality is not a usual

business, because it is in itself a value judgment. Nevertheless, he argued,

that some fundamental factors are must to be considered while dealing

with the levels of inequality. Among these factors, the following must be

significant: the distribution of income & wealth, which must be assessed in

the light of individual difference and needs; the decisions made by the

individuals as per their preferences, which may lead to disparities in income

distribution; the equality of opportunity issues; along with the systematic

variation in income and wealth over a certain individual‘s living. The

inequality concept is far from being identical to te poverty concept. The

inequality measurement tools pay attention to the entire income

distribution within a given population or a group of people, whereas the

main purpose of study is on poverty is explicitly to identify and measure the

se of people with less than the minimum requirement for survival. For that

reason, inequality and the poverty studies cannot be conducted on the

same methodological basis using the same tools. Thus a separate set of

tools is required to measure inequality. Several indices have been

developed for this. The simplest measure of inequality is the Lorenz curve

which is a visually satisfying way of representing the inequality of an income

distribution by plotting the cumulative share in total income against the

cumulative proportion of the population.

Then there are certain positive indices and normative indices of inequality

(Subramanium, 1997). The positive indices are essentially statistical measure

of dispersion. Many of these indices are directly based on Lorenz Curve

while, others are not. Certain well known positive indices of inequality are

the range, the variance, the squared coefficient of variations, the variance

of log incomes, the relative mean deviation, the Gini coefficient, and the

Theil‘s two inequality indices. An index such as the range is a very

rudimentary one; while other indices satisfy more demanding properties.

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The Normative indices of inequality (Subramanium, 1997) are based on

writings of Dalton (1920) Atkinson (1970), who have argued that a

meaningful index of inequality must be somehow related to a qualification

of the loss in social welfare attributable to the presence of inequality. The

inequality index is thus imbued with a normative or ethical connotation.

Inequality Measures: The Required Properties

There are number of properties that may be regarded as desirable for the

inequality index to satisfy, have been brought forth in the literature (Foster,

1985). Few of these properties often displayed in the form of axioms- that

are briefly discussed below. Symmetry recommends that an inequality

index should be invariant with respect to a presentation of incomes across

individuals; the transfer axiom requires that, remaining all the other thing

constant , a rank presenting transfer of income from one person to a

poorer person should cause the extent of measured inequality to decline;

transfer sensitivity requires that an inequality index would be more sensitive

to transfers at the lower end of a distribution that an its upper end;

normalization requires the inequality index to assume a value of zero for a

perfectly equal distribution of incomes; continuity requires the inequality

index to be continuous in the domain of income distribution; scale

invariance(or mean - independence) requires the extent of inequality to

remain unchanged if every income in a distribution is multiplied by a

positive real number; replication-invariance (or population-invariance)

requires that if each income in distribution is replicated by m times (where

m is any positive integer), the extent of inequality for the replicated

distribution should be the same as for the original distribution; and sub-

group consistency requires that, ceteris paribus, an increase in inequality in

every sub group within a population should lead to an increase in overall

inequality. The usefulness of an inequality index must be judged in relation

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to the purpose in hand. In the present study, Gini ratio has been used as a

measure of inequality, as it, apart from satisfying many axioms, is also the

one which is widely used in many governmental and institutional studies.

Also, it has been found that different measures of inequality are highly inter-

correlated and as such, the extent of gain possible by augmenting the Gini

Coefficient with other measures of inequality is questionable (ADB, 1984).

Poverty

The term poverty refers to a state of minimal or subsistence level under

which an individual or household is bound to survive in. the definition of

poverty varies according to the values culture and attitude of the

concerned societies. Poverty could be seen partly as a value judgment,

based upon criteria which distinct among societies.

Despite of various prolifered definitions, it is still possible to categories them

as per their school of thought. The first group of definitions relates itself to

the utilitarian approach that is based on classification of preferences for

commodities. To be more specific, this approach stipulates that all poverty

comparisons must be done with reference to the satisfaction of the

individuals under consideration, their utility levels. The theoretical bases for

their approach are in close affinity to contemporary microeconomic

theory. That brings forth the fact that why a feature of this school of thought

is the necessity of avoiding conclusions that predict individual behavior.

The utilitarian school of thought is often challenged by those who are of the

belief that poverty is a function of elementary goods bundle. These goods

could be observed as the minimum requirements in terms of food, shelter or

even social rights. The non utilitarian approach, as it could be named,

provides much more scope in the identification of the deprived by

providing access to great variety in the goods admitted to the basic

consumption bundle.

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Nevertheless, a significant caveat to bear in mind is that this school of

thought ignores any notion of utility.

The distinction between the two approaches could be clarified through an

illustration: it is given the population of a certain country unanimously favors

a civil war which succeeds in ousting the government, and that everyone

prefers the new administration. Also suppose that the consumption of the

poor people has been eroded by the hostilities. On the one hand, the

utilitarian approach would conclude possibly find the opposite, since the

evaluation of poverty in this case is based on the capacity of the

population to obtain the basic consumption bundle (Cote, Sebetian, 2000).

Each approach has its positives and negatives. In fact, the utilitarian

approach could not account for factors such as public goods, human

rights, and other non material elements. Such goods might represent other

sources of well being for individuals. Resultantly, non tangible sources of

being well off might be discarded and in view of some, such discrediting

defeat the utilitarian approach as a relevant criterion of defining poverty.

Conversely, the non utilitarian approach based on partly subjective criteria

in the definition of elementary goods. Certain authors have tried to define

the term poverty in a precise manner. In general, these definitions could be

associated to the previously enumerated school of thought. For instance

Fields (1994), defines the term poverty as the inability of an individual to

afford the basic necessities Ravallion (1994), suggests that the choice of

basic needs should display the general perception of significant

requirement, but also insists on the fact that an analysis of poverty should

be based upon the people‘s evaluation of their own situation that is

whether they consider themselves as poor or not. The opinion of Fields

seems ambiguous; where as the definition given by Ravallion is straightly

utilitarian.

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The last opinion given by Ravallion (1994) could prove to be successful in

drawing our attention by which draws the line of distinction between the

term absolute poverty and relative poverty.

―an absolute poverty line is the best thought of as one which is fixed in

terms of living standards, and fixed over the entire domain of the poverty

comparison; a relative poverty line, by contrast, varies over that domain,

and is higher the average standard of living‖.

A concrete example of a study which clarifies the distinction between

absolute and relative poverty was conducted by Foster (1998). In his study

an initial absolute poverty line was hypothesized without considering

growth in the economies targeted by the study. Subsequently, a second,

relative poverty line is computed for comparison purposes. This last variable

is defined as the percentage of a given standard of living determined from

a list of country‘s specific features.

Another example of an application of absolute poverty theory was

exhibited by Ravallion et. al. (1991). Which suggests two possibilities for

fixing an absolute poverty line: the first technique depends upon the

determination of the price of a basic goods bundle, which must be seen as

an absolute minimum for survival. The second technique consists of taking

the lowest poverty line among all countries in a given study, and

considering this smallest value as the absolute poverty line. In the later

years World Bank started making estimates of absolute poverty across

different countries, by defining an international poverty line at 1$ per day

which was based on purchasing power parity of 1993. In the same way, it

also it has also provided estimates of another poverty line defined by 2 $

per day.

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Poverty Indices

In order o determine the magnitude and indices of poverty, various types

of poverty indices are formulated. The Head count Ratio is one of the

specific indicators which is widely in practice, due to its computational

simplicity. This index is nothing but the proportion of the number of people

in the overall population. But the biggest flaw of this indicator is that varying

degrees of poverty are ignored by this situation, or the other way round

the value of the index will remain intact even if someone considered poor is

falling down to the poorest level. According to Lipton (1997), ‗New

Consensus about poverty‘ identifies three essential determinants which

should be measured by poverty indices. The first is the incidence or the

number of persons falling under the predefined line of poverty; the second

is the intensity, which connotes for depth of poverty as well as incidence;

and the third one refers to severity, which suggests inequality among the

poor.

Considering these above three essential elements, Ravallion (1996),

provides some information on the range of other measures dedicated to

poverty issues. One such measure is average poverty Gap (PG) which

helps to sort out the intensity as well as incidence of poverty.

Another advance index that has been developed from advanced poverty

indices is FGT measure given by Foster, Greer and Thorbecke (1984). As the

time passed this has become usual but is best with problems of

interpretation. A specific interpretation of FGT measure is as a weighted

average of poverty gaps. The weights corresponds to proportional size of

the poverty gaps. For instance, if is in deficit of 10 per cent of poverty line,

then the weight on his poverty gap equals 10 per cent. Whereas, in case of

the PG measure, every distance from the poverty threshold has the same

weight in the calculation of the mean poverty gaps. Along with this one

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significant feature of the FGT index is that the weight assigned to the

individual well being increases with his or her level of poverty.

Sen (1981), points out the fact that a poverty index should satisfy

monotonicity axiom which stipulates that a decline in the income of

someone considered poor must increase the poverty the poverty index.

The shift of axiom , which simply suggests that a transfer from someone

considered poor to someone else situated below the poverty line should

also increase the poverty indicators should also be satisfied. In purview of

these axioms, Sen derived his own poverty index which is viewed as

advance indices, in the sense that it is a poverty measure that incorporates

a measure of inequality in its computation. This poverty index has been

revisited a number of times, by Sen himself as well as by others. Various

governmental and institutional bodies publish data on poverty. Due to the

nature of data availability, easy computation and familiarity, HCR has been

used as a measure of poverty in the present study.

Section II

Linkages between Inequality and Economic Growth

The relationship between inequality and growth is bi-directional, as the

extent to which growth affects inequality; inequality affects growth to the

same extent. The mechanisms running from growth to inequality are

relatively directly associated. The first link is a straightforward link. Fast

paced growth augments demand for labor and the individual who get

benefitted disproportionately are those on the margin of the workforce.

Switching from unemployment to employment, or from part time to full time

employment, significantly augments the income of people at the bottom

of the income distribution and reduces overall inequality. The second is an

indirect link. A society with rapid economic growth becomes richer and

theses supplementary resources could in theory be taxed upon and re

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circulated to the poor to curtail inequality. This undoubtly is a political

economic selection and does not automatically go hand in and with

growth. Due to these reasons, fast paced economic growth specifically

when produces extremely low unemployment proves to be equality

enhancer as the impact of growth on equality proves positive. The first kind

of benefit was highlighted by Kuznets (1955)who postulated that the initial

stages of development are characterized by an increase in inequality, as

individuals shifts from conventional low income generating agriculture

activities to better paid modern sector jobs. As development takes place,

the low income conventional sector gradually becomes irrelevant and the

modern becomes priority, consequently trend towards equality sets in. The

directions of linkages from inequality to growth are more complicated than

the direction of linkages from growth to inequality, both in terms of

mechanisms at work and in terms of sign of impacts. The conventional

thought in this regard got preoccupied by A. Okun‘s well known book

Equality and Efficiency: The Big Tradeoff (1975),which argues that inequality

serves as an incentive, both reward and penalty, to promote efficiency in

the use of resources and to generate a greater and growing national

output.

However, in modern times both the Kuznet‘s and Okun‘s theories have

been widely challenged. The Kuznet‘s curve is unable to display any

support by current inequality trends in inequalities among the advanced

countries. On the other hand, a number of new economic theories have

been formulated which prove Okun‘s contention as untrue by exhibiting

the fact that greater equality could have positive effect on economic

growth (Dollar and Kray, 2000). There exist a number of empirical studies

that favor these theories.

Consequently, in the recent past, a vast literature on the links between

inequality and growth has proliferated. Instead of concentrating on

Kuznet‘s Hypothesis (Kuznets, 1955), the reinvigorating interest in the

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endogenous growth theory has influenced substantial study in to the

exploration of impact assessment of inequality on growth. More recent

developments of this productive strand of literature suggest that social

comparisons, coming from the society‘s perception of inequality, lead to

low rates of growth, this effect being more relevant in developed

economies (Knell, 1998). There exist some models which appeal to the

imperfection of capital markets. According to Capital market models,

redistribution should have positive effects on growth while Political

Economy models point out those strongly progressive redistributive policies

would depress the return on capital, thus decreasing growth (Figini, 1998).

Theoretical literature discovers six main categorical models which displays

the linkages between inequality and growth; which are briefly discussed

below:

1. The Political Economy Model

In contemporary democratic society, the taxation level is decided by the

median voter. It is assumed that taxation is proportional to income, and

public expenditure progressive; therefore, the benefit received by the poor

is greater than the benefit received by the rich. Therefore, the poor would

prefer a high level of tax redistribution. As in unequal societies the income

of the median voter is lower than the mean income, majority rule would

dictate a higher level of redistribution which, in turn, discards investment by

suppressing its net return, and lowers down growth (Alesia and Rodrik, 1994,

Bertola, 1993, Perotti, 1993, Persson and Tabellini, 1994). These findings could

be summarized in the Proposition 1

Proposition I: High inequality, that is, low ratio of median to mean pre-tax

income, leads, to more redistribution and to less growth, through

discouragement of investment.

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The unfavorable impact of inequality would be attenuated by the degree

of wealth based on the system against the poor. The further the society

moves from democratic archetype the less it is possible to reduce the level

of inequality through redistribution. Hence, the previous findings could be

extended allowing for distinct degrees of democracy.

Proposition II: The negative effect of inequality on growth is weaker for

political systems that are less beneficial to the poor (in rich countries or in

countries govern by Dictators).

2. The Capital Market Imperfections Model

This approach is based on the key role played by imperfections in the

capital markets: in societies where agents do not have free access to

borrow, an inequality implies that a relatively larger proportion of the

population is below the threshold cost of education. Therefore, the

investment in human capital is low as does the growth. As a consequence

of this approach, that is outlined by Aghion and Bolton (1992 and 1997),

Chiu (1998), Galor and Zeira (1993), and Saint- Paul and Verdier (1993), is

that redistribution would on a positive note in the growth regression as it

would augment the investment in human capital that is positively linked

with growth. This leads to the given Proposition:

Proposition III: Credit constraints discourage the poor from undertaking

efficient amount of investment and, since there are diminishing returns to

investment, inequality results in lower growth. As a result of redistribution,

total output increases along with growth which allows the poor to invest in

human and physical capital.

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3. The Integrated Model

The Political Economy Model and the Capital Market Imperfections Model

differs with respect to the role played by redistribution. Redistribution lowers

growth according to the Political Economy Model but advances it as per

the Capital Market Imperfections Model. Benabou (1996), suggests an

integrated framework in which the impact of redistribution on growth is not

necessarily linear. He distinguishes two opposite effects. Redistribution is

better if public welfare expenditure encourages financing education in the

world of imperfect capital markets, and worst if it merely transfers income

from rich to the poor, as it discourages the net return on investment of the

rich. Some of the conclusion of Benabou (1996) could be summarized as

follows;

Proposition IV: In the Political Economy Model and the Capital Market

Imperfections Model under any given redistributive policy, inequality

reduces growth. The negative effect vanishes with the extent of pre-

investment redistribution: i). Growth is inverted U shaped with respect to

redistribution and growth maximizing tax rate increases with inequality; ii).

Growth is hill shaped with respect to the degree of wealth bias in the

political mechanism; iii). Redistribution is U shaped with respect to

inequality.

4. The Socio-Political Instability Model

This model insists on the consequence of inequality on political instability

and social unrest. As per the Socio-Political Instability Model, inequality is a

vital determinant of socio-political instability and this, through lower

expected returns on investment, has negative effects on growth. While the

instability channel has been around for a long time, formal models have

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only been exhibited recently by Alesina et.al.(1996), and Benhabib and

Rustichini (1996). Some of the conclusions could be summarized as follows:

Proposition V: Inequality exacerbates social conflict, which in turn makes

property rights less secure and reduces growth.

5. The Fertility/Education Model

Perotti (1996) suggests that inequality has negative effect on economic

growth through the distortion of the households‘ decision on education

and fertility. Parents have to optimize the use of household‘s resources,

alternatively through an improvement in education or in fertility of their

generations to come. As education bears a cost equivalent to the income

foregone while at school, poor households do not invest in human capital

but in the quantity of children. However, growth could only be encouraged

by investment in human capital; therefore, ceteris paribus, a society, in

which there exists high inequality, presents relatively exceeding number of

poor households that invest in quantity rather quality. The high fertility rate

of this society leads to low growth; this link closes the model and is well

known in the literature (Becker and Barro, 1998).

Proposition VI: Greater inequality implies that many relatively poor

individuals invest in the fertility rather than in education of their offspring,

which leads to, ceteris paribus, less investment in human capital and to

meager growth.

6. The Social Comparison Model

Lastly, a contemporary article based on increasing social and

psychological aspects of inequality. Knel (1998) provides an explanation for

the suggestion that the link between economic growth and inequality

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might be stronger in rich countries; he offers a model, directly built on

Benabou (1996), in which individuals make social comparisons. Knell

assumes that maximization of individual utility does not depend solely on

own consumption but also on the average consumption of some reference

group. In an unequal society, poor households are tempted to conform to

the norms and to fulfill social needs and expectations, by involving in

greater consumption activities and by lowering investment in human

capital in order to reduce the gap with richer households. These activities

maximize present welfare but go to the detriment of future welfare and

growth. Knell reports that three factors simultaneously determine the effect

of inequality on growth; the choice of reference group, the degree of

diminishing returns to investment and the strength of future social

comparisons relative to the present ones. Moreover, the impact of

inequality on growth would be higher in societies where social comparisons

are of greater importance, as it is in developed countries. This leads to the

Proposition VII.

Proposition VII: Inequality, in the society where social comparisons are of

vital issues, implies that households augment their current consumption to

the detriment of investment in human and physical capital, therefore

lowering growth.

The above discussed seven propositions devised from the literature on

inequality and growth sufficiently exhibits the motive associated with

negative linkages between inequality and growth, which has been found

to be robust across many empirical studies. This also brought forth the fact

that there are needs for social policy measures in order to reduce

inequality.

Thus, whether we consider the theoretical mediums; the relationship

between inequality and growth or whether we consider clues from social

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justice theories, equity is desirable from both the perspectives. It has been

broadly realized that road to greater growth need not pass through

unequally driven societies. Therefore, suitable policy measures, ensuring

equity in income distribution, need to be taken up by all economies round

the world.

Economic Growth and Income Distribution: Some Important Studies

In the present chapter, the review of the empirical work on Economic

Growth and Income Distribution has been undertaken. The review of these

studies provides a broad spectrum of work done in this area and basis for

the formulation of appropriate methodology for the present study. What

follows is not an exhaustive review of the research done in this area; rather

the idea is to highlight, in a general way, the type of work done in this

direction. A brief review of some significant studies has been presented

below in a chronological order:

In his classic paper, Kuznets (1955) put forward the idea of an association

between inequality and economic growth. Based on the evidence from

time series data on England, Germany and United States, Kuznets

hypothesized the famous Inverted U shape relationship between growth

and inequality. The mechanism underlying this relationship was also

discussed by Kuznets. He emphasized on stressing economic, social and

political factors as explanations of the statistical regularities he observed.

But the foremost of these factors, one which provided the attention of

Kuznets analysis and has become important in the recent literature, is the

migration of population from conventional to modern activities. This

process of migration of population, along with formalization of what he

regarded as the stylized facts of economic growth, permitted Kuznets to

derive predictions of the behavior of inequality during the course of growth:

―An invariable accompaniment of growth in developed economies is the

shift away from agriculture, a process usually referred to as industrialization

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and industrialization. The income distribution of total population, in the

simplest model may therefore be viewed as a combination of the income

distribution of the rural and the urban populations. What little we know of

the structures of these two component income distribution reveals that: a).

the average per capita income of the rural population is usually lower than

that of the urban population; b). inequality in the percentage shares within

the distribution for the rural population is somewhat narrower than in that

for the urban population…. Operating with this simple model, what

conclusions do we reach at? First, all other conditions being equal, the

increasing weight of urban population means an increasing share for more

unequal of the two component distributions. Second, the relative

difference in per capita income between the rural and urban population

does not necessarily drift downward in the process of economic growth: in

fact, there is some evidence to suggest that it is stable at best, and tends to

widen as per capita productivity in urban pursuits increases more rapidly

than in agriculture. If this is so, inequality in the total income distribution

should increase.‖ This underlying model of population shift may be termed

as the Kuznets‘ process, which inspired much of the later empirical literature

on inequality and growth.

On the basis of above theoretical foundation Kuznets (1955) conducted a

study for five countries viz. India, Ceylon, Puerto Rico, US and the UK.

Measuring inequality by the income shares of various quintiles, Kuznets

observed greater inequality in the developing countries. He explained the

distinction between under developed and developed countries in the

following manner: ― The under developed countries have no middle class;

there is a sharp contrast between the preponderant proportion of the

population whose mean income is significantly lower than the generally

lower economy wise average, and a small top quintile group with a very

large relative income excess. The developed countries, on the other hand,

are characterized by a much more gradual rise from low to high incomes

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shares, with substantial groups receiving more than the high countywide

income average, and the top groups securing smaller shares than the

comparable ordinal groups in underdeveloped economies‖. Viewed from

this perspective, the variations inequality reflects real distinction across

economies in participation in advanced or modern sectors of the

economy.

The pattern of greater relative income distribution in under developing

countries than in developed countries was confirmed by subsequent study

carried out considering eighteen countries by Kuznets (1963) he confirmed

that the share of the upper income groups were distinctly ahead in

underdeveloped economies than in developed economies. Although the

shares of the lowest income groups in some under developing economies

were lower than in some developed economies, the differences were

much narrower than for the shares of the upper income groups. The shape

of the income distribution curve was different in under developing

economies than in developed economies which followed that the Gini

coefficient of inequality was greater in under developing economies than

in developed economies.

Kuznets found Gini coefficient to be .44 for the under developing

economies included in the study, while in developed economies it was

0.36. On that evidence, Kuznets was led to the view that the level of

economic growth as measured by Gross National Product per capita and

a major determinant of the extent of income inequality in an economy. The

specific nature of that dependence has come to be known as the Inverted

U shape hypothesis which states that relative inequality rise during the early

stages of growth, reaches a peak, and then declines in the later stages.

Adelmen and Morris (1973) gathered data for forty-three developing

countries and presented considerable evidence on the correlates of

relative income inequality. By means of analysis of variance they found six

factors to be important in explaining variations in relative income

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inequality, one of which was the level of economic development.

Adelmen and Morris (1973) concluded their study by saying, ―Our

conclusions underline the urgent need to discard as outmoded the view

that economic growth in low-income economies benefits the masses.

Development is accompanied by an absolute as well as a relative decline

in the average income of the very poor.‖

Paukert (1973) defined Adelmen and Morris estimates. He discarded

information thought to be particularly unreliable, added some new

countries where good data had recently become available, and

presented summary information on the size distribution of income in 56

countries. For each several alternative relative measures of inequality,

Paukert found that inequality begins at a comparatively low level, reaches

a peak in the economies with per capita incomes of $301-$500, and then

diminishes at higher incomes. Thus he reconfirmed the inverted U

hypothesis.

Papanek and Kyn (1985) analyzed cross section and time series data for 83

economies and found no systematic relationship between equality and the

rate of economic growth. They found some support for the Kuznets‘

hypothesis that inequality increases as per capita income rises to about

$400 and then declines, with further income increase, but they dubbed this

empirical support as not strong and may be weakening over time. The

study found dualistic social –political system to be highly unfavorable for

equality. Neither the extent of government intervention in the economy nor

the rate of manufactured exports was found to be systematically related to

income distribution. Educational participation, and a reduction in the share

of primary exports in GDP, where both, found to be favorable for equality.

The study concluded on an optimistic note that rapid growth in a mixed

economy is quite consistent with unchanged, or even improved, income

distribution even at early stages of growth.‖

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Ram (1985) investigated two related issues, first, the relative importance of

income level and equality for an improvement in the provisions of basic

needs in under developed economies and second about the difference, if

any, in that regard between the low income and middle income under

developed countries. This has been done by using globally comparable

GDP per capita, along with the World Bank Data on seven basic needs

indicators and one income equality measure. Measure regression model

was used to access these issues. The study concluded that income seems

important in almost all cases but the importance of income equality is

observed only on a limited scale. The study further reveals that although

income is more important in low income under developed economies, the

relationship studied appears broadly similar in the context of low income

and middle income under developed economies.

Papanek and Kyn (1987) combined cross section and time series analysis

had found support for the Kuznets‘ curve. They used the income share of

various deciles as dependent variables, and log of per capita income, its

square, time, socio-political dummy variables, education and the structure

of exports as independent variables. They confirmed the Kuznets‘ U

hypothesis in their regressions but found the Kuznets‘ curve to be quite flat.

They also investigated the hypothesis that faster growth is associated with

greater deterioration in the share of income accruing to the poorest

deciles. The study confirmed the hypothesis but again found that the

deterioration in income share with more rapid growth is small.

Ram (1988) used the international comparable data on inequality and

income to reassess the empirical status of Kuznets‘ u curve hypothesis. The

study observes that the hypothesis seems well supported when both

developed economies and under developed economies are included in

the sample. However, the position changes, rather dramatically, if the

sample is restricted to under developed countries, and very small support

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for the hypothesis is observed. The study concludes that some of the

support reported in earlier studies may have been due to the use of

conventional gross domestic product per capita. The result based on Gini

coefficient seems less favorable to the hypothesis that those derived from

household income shares.

Fields (1989) tested the hypothesis that economic growth tends to reduce

poverty by taking up data for 18 countries. He found that poverty fell in 14

countries, rose in 3 and exhibited no clear tendency in 1 economy. In 2 of

the 3 cases in which poverty rose, the economy had suffered an economic

decline. In only one case positive economic growth was not accompanied

by a fall in poverty. Thus, the study confirmed the hypothesis that poverty

declines as the economies grow.

Adelman and Fuwa (1992), using the data on 41 developed and

developing economies, also tested the Kuznets‘ curve for 1980s. their results

suggested that in 1980s, Kuznets‘ U shape had become Kuznets‘ j shape,

i.e. in the initial years of growth the income share of the poor declines very

sharply, reaches its lowest near income level characterizing semi industrial

nature of the economy, and for all practical purposes, remain there.

Recovery against pre-development shares is gradual, and is not achieved

even long after economies become fully developed. The study suggested

that the structural adjustments policies and financing methods used to

support growth during the 1980s have exacerbated the growth equality

trade-off for the poor.

Anand and Kumar (1993) undertook a critical appraisal of the literature on

equality and growth, and particularly the influential examples of it due to

Ahluwalia (1976) and Ahluwalia, Carter and Chenery (1979), wherein they

confirmed the Kuznets U hypothesis and their results have been used as the

basis of projections of inequality and poverty. Anand and Kanbur,

therefore, tested the robustness of Ahluwalia’s estimates with respect to

variations in functional form and data set, and found them to be lacking.

182

Alensina and Rodrik (1994)regressed per capita income growth over the

period 1960-85 on a variety of independent of variables, such as initial per

capita income and the measure of initial human capital. They also

included initial inequality of the income and initial inequality of land as

variable. Their regression results indicated a substantial negative

relationship between initial inequality and subsequent growth. Particularly

strong was the influence of Gini coefficient, which represented the initial

inequality in land holdings. Their results suggested that an increase in land

Gini coefficient by one standard deviation point would decrease

subsequent economic growth by as much as 0.8 percentage points every

year.

Birdsall, Ross and Sabot (1995) on the basis of their research of East Asian

Economies, challenged the conventional Theories that there is a tradeoff

between increasing growth and declining inequalities they reached the

conclusion that East Asian Economies have followed the path of growth

over three decades ago, with relatively low levels of income inequality,

and also appeared to reduce income inequalities. They argued that

policies that minimize poverty and income inequality, such as emphasizing

greater quality basic education and increasing demand of labor, also

stimulated growth. It was perceived that paced growth and shortened

inequality led to greater demand for, and supply of education. They

displayed cross country regression results which were consistent with a

positive casual effect of low inequalities on economic growth and with low

inequality of income as an independent contributing factor to East Asian

Economies rapid growth. Thus, they reached on the conclusion that

policies for distributing growth could also stimulate growth.

Deininger and Squire (1996), utilizing both Gini coefficient and quintile share

data explained the regional and inter-temporal distinction in inequality. The

study highlighted the familiar fact that in Latin America is significantly

greater than in rest of the world. They also considered the

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contemporaneous association between growth, inequality and poverty.

For the 95 growth spells for which they have data on income shares, no

synchronized relationship between growth and inequality were discovered,

nevertheless, a solid positive association between growth and poverty

reduction was identified.

Perotti (1996) suggested that inequality and growth are negatively related.

The household‘s decisions on fertility and education could shows the

medium by which inequality negatively affects growth.

Deininger and Squire (1998), new cross country data on income and asset

distribution which showed that (i) there is a strong negative relationship

between initial inequality in the asset distribution and long term growth; (ii)

inequality reduces income growth of poor, but not of rich; and (iii)

available longitudinal data provide little support for the Kuznets‘ hypothesis.

Thus, it was found that the policies that increase aggregate investment and

facilitate acquisition of assets by the poor might thus be doubly found

fruitful for growth and poverty alleviation.

Gallup, Radelet and Warner (1998) used the sample of 69 economies that

included 448 growth periods, with an average growth period of 2-7 years.

They discovered that in a simple regression of the income growth, ‗the

elasticity of connection‘ was almost unity. The study also exhibited the fact

that although the starting income share of the poor was low, the

subsequent income growth of the poor is greater than mean income

growth. This exhibits a tendency for economies to converge to similar

income shares for the poorest quintile groups.

Deininger and Olinto (1999) assessed the effect of inequality in asset

distribution on subsequent growth. They found asset inequality to be lead

casual determinant of economy‘s growth performance even if panel data

techniques are used. They found that in addition to a direct growth

reducing effect, high land ownership inequality also poses a limit to the

effectiveness of educational policies in contributing to aggregate growth.

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The regressions run by them, detected, negative and significant interaction,

between inequality and the stock of human capital. The authors found that

asset inequality has a negative incentive effect that goes beyond the

traditional medium of credit market imperfections and reduced

investments.

Datt and Mukherjee (2000) analyzed the pattern of income distribution

across 15 major states of India for the time period of 1960-1994. The study

concluded that trends in both rural and urban inequality for many states,

which are quite contradictory to the notion common in certain circles that

inequality is a random variable which oscillates within a trend. The trends

presented a varied picture. For the urban sector, there were 3 states which

explained decline in inequality in this period under consideration, for the

rural sector there were states experiencing significant trend declines as well

as others experiencing trend increases. The existence of these trends was

indicative of a systematic component to the evaluation of inequality in

these states. The difference between trends across states was found to be

important and the notion of a common time trend for the series as a whole

was rejected by the data.

Dreze and Srinivasan (2000) in their study presented estimates of rural and

urban poverty and inequality for the sixty constituent regions of India‘s

major states during the period 1972-1988, which were based on NSSO data.

The study discovered that headcount ratio of rural poverty has declined in

almost all regions, but there are larger inter regional disparities in per capita

expenditure which remained unchanged, though there was some variation

in headcount index. In terms of intra regional inequality in consumer

expenditure for rural constituencies, there had been significant changes in

region specific Gini ratio, with inequality rising in almost half of the regions

and declining in the other half. The mean Gini ratio nevertheless was

virtually the same in both years. Cross section patterns in 1972 and 1988

displayed no sign of the declining trend in Kuznets‘ curve.

185

Fielding (2001) used cross country data to estimate the impact of GNP and

other indicators of development on inequality. The overall picture that

emerged was that there is a correlation between reduction in inequality

and improvements in growth indicators such as per capita income, literacy

and life expectancy. Inequality was found to be dependent on mean

income levels, in the form of Kuznets‘ curve relationship, although the

sensitivity of income inequality to income was estimated to be lower than

has been suggested by some previous studies. At very high income levels,

the negatively sloped part of the Kuznets‘ curve reinforced the negative

correlation between inequality and other development indicators and at

very low income levels the positively sloped part of the Kuznets‘ curve

reduced the correlation.

The above studied empirical researches are the significant one in the huge

amount of available literature on Growth and Inequality. After going

though the all available research literature, one could easily conclude that

there is no unanimity among the economist, with respect to the relationship

between inequality and growth. Where as some economists, rejected it

altogether. The present study aims at exploring the relationship between

these, in the light of recent enlarged and improved data set on inequality.

186

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192

Chapter -VII

Analysis of Economic Growth and Income Distribution The present chapter is divided into three sections, Section-I describe

the various methodologies which have been used for the present analysis,

whereas the Section-II, examines the trends in inequality and the trends in

Poverty has been discussed in Section-III.

Section- I

Methodology

In order to, examine the Indian experience with respect to

poverty and inequality. Data on 16 select states have been taken into

consideration. These 16 states includes: Andhra Pradesh, Assam, Bihar,

Gujarat, Haryana, J&K, Karnataka, Kerala, Maharashtra, Madhya Pradesh,

Orissa, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh and West Bengal. A

cross sectional analysis of poverty and inequality in these states of India has

been carried out considering four select time periods viz. 1983-84,1993-

94,2004-05 and 2009-10. For this purpose 16 variables are considered for

analysis, which represents the social, economic and demographic

characters.

The following techniques which are used for the analysis, discussed below;

1. Gini Ratio

The Gini Ratio is a measure of inequality of a distribution. It is defined as a

ratio with values between 0 and 1: the numerator is the area between the

Lorenz curve of the distribution and the uniform distribution line; the

denominator is the area under the uniform distribution line.

193

Figure 7.1 The Lorenz Curve

Graphical representation of the Gini Ratio

The Gini index is the Gini Ratio expressed as a percentage, and is equal

to the Gini Ratio multiplied by 100. (The Gini Ratio is equal to half of the

relative mean difference.) The Gini Ratio is often used to measure income

inequality. Here, 0 corresponds to perfect income equality (i.e. everyone

has the same income) and 1 corresponds to perfect income inequality (i.e.

one person has all the income, while everyone else has zero income). The

Gini Ratio can also be used to measure wealth inequality. This use requires

that no one has a negative net wealth. It is also commonly used for the

measurement of discriminatory power of rating systems in the credit risk

management.

194

2. Poverty Headcount ratio (PHCR)

The poverty Headcount Ratio is one of the most widely used poverty

indicators due to its computational simplicity. Because of its aforesaid

characteristics and familiarity, the same has been utilized as a measure of

poverty under considered study. The poverty Headcount Ratio can be

defined as;

PHCR= q/n

Where PHCR is poverty Headcount Ratio

‗q‘ represents the number of poor people

‗n‘ represents the total population

3. Regression Analysis

Linear regression equations were fitted by regressing dependent variable

on each of the independent variables separately on each of the

independent variables separately as well as jointly (through multiple

regressions)

Yi= β0 + β1 X1i + ……………. + βk Xki + ui (k= 1, 2…)

Where, for the ith country, Yi stand for the value of the dependent variable,

Xi s stands for the explanatory variables and β stands for the unknown of the

regression model to be estimated.

The statistical significance of estimates of β1 was examined by applying t-

test; r2/R2 was computed to see the percentage variations in the

dependent variable explained by a particular independent variable or all

the independent variables jointly.

The polynomial regression analysis was also carried out in the following

form:

Y = β0 + β1 X + u

Y = β0 + β1 X + β2 X2+ u

Y = β0 + β1 X + β2 X2+ β3 X3 +u

195

Where X is independent variable X2 and X3 are the square and cube of this

independent variable and u is the disturbance term. The explanatory

power of the regression equation was studied with r2/R2. Significance of R2

was also checked by applying F-test, estimated as under:

F = R2 (k-1)/ (1- R2) (n-k) ~ (k-1) and (n-k) d.f.

The fitted lines of regression have also been presented graphically,

wherever required.

4. Correlation Analysis

In order to examine the inter-correlations amongst different determinants of

inequality and poverty, correlation matrices were constructed. To test the

significance of correlation coefficients, t-test has been applied.

5. Step wise Regression Analysis

In multiple regression analysis, we often come across the problem of multi-

collinearity. The consequences of multi- collinearity lie in inaccurate,

imprecise and unstable estimates. To overcome this problem, step-wise

regression analysis technique was applied to compare the explanatory

power of different sets of multiple regression equations; adjusted coefficient

of determination (R2) has also been calculated for each regression

equation.

R2 = 1- [(n-1)/ (n-k) {1-R2}]

6. Factor Analysis

The determinants of inequality and poverty are basically socio economic

and demographic by nature. Such variables often have been found to be

highly correlated amongst themselves. This carries the problem of Multi-

collinearity and the consequences of this problem are inaccurate and

unreliable results. The statistical technique that can be more usefully

applied in such a situation is Factor Analysis. Factor Analysis attempts to

196

estimate the value for the coefficients of regressions when the variables are

regressed upon the factors In Factor Analysis a given set of n variables are

categorized into p groups called factors which are less in number than the

set of original variables. The variables within the group are of similar nature

or are complimentary with respect to the phenomenon under study. The so

obtained factors are known to be independent of each other. That is,

factors Fi and Fj are orthogonal Vari-max.

However, one of the limitations of Factor Analysis is that a number of times,

variables turn out to be strongly associated with more than on Factors thus

creating difficulties in interpretations.

Ever since the initiation of the plan wise development in India, the State

Policy Makers have laid emphasis on the objective of reasonable

egalitarian distribution of the product of growth through reduction

inequality and eradication of poverty. This objective is articulated in various

five-year plan documents with consecutively epitomized announcements

of ‗equitable growth‘, ‗growth with distribution‘, ‗growth with social justice‘

and to the most recent ‗inclusive growth‘.

The achievement of these objectives requires annulment of formidable

issues of poverty and inequality. The length and breadth to which India has

succeeded to reach its objective has been analyzed under present

Chapter that has been divided into two sections. Sec-I of the Chapter

analyzes the trends and determinants of income inequality in India, through

cross sectional analysis of select four time periods, which are; 1983-84, 1993-

94, 2004-05, 2009-10. Whereas analysis of trends and determinants of

poverty for the above mentioned select time periods has been carried out

in Sec-II.

197

Section-II

Trend of Income Inequality

It could be comprehensively quoted that inequality in society, economy

and in demographic clusters or altogether, the consumption distribution or

the income distribution or similar other idiosyncrasy –connotes the

significant magnitude of goodness of the before mentioned clusters.

Inequality measures could be computed for consumption distribution,

income distribution or for similar other variables like, land and other

perpetual and primary variables.

Quintile-wise Percentage Share

Under this parenthesis's effort has been made to recognize the relevance

of percentage share of quintiles (Q1 to Q5). Similarly, specific time period of

1983-84, 1993-94, 2004-05 and 2009-10 have been taken into consideration

in order to represent the changes occurred in quintile percentage–share in

consumption expenditure. The Quintile-wise percentage shares of overall

consumption expenditure possessed by distinct groups ranging from Top

Quintile (Q5) which connotes richest 20 % population group. Bottom Quintile

(Q1) which is the poorest 20 % group and the rest are Second (Q2), Third

(Q3) and Fourth (Q4) Quintiles, consisting 20 % of population in each group

as per their consumption expenditure share. (Table 7.1)

During 1983-84, the Bottom 20% of population (Q1) possessed

8.7 per cent of share in total consumption expenditure. The top Quintile

(Q5) possessed 40.1 percentage shares in overall consumption expenditure.

Further, the percentage share of consumption expenditure held by Q2, Q3

& Q4 were 12.8%, 16.6% & 21.8% respectively. The ratio of top (Q5) to

bottom (Q1) quintile as a measure of relative inequality in the economy

was 4.61.

For the year 1993-94, the top quintile Q5 & Q2 were 40% & 12.8%

respectively, which also depicts the rigidity in these quintiles, when

198

compared with the year 1983-84. The bottom quintile (Q1) was 9.1 per cent,

which as well shows an increase of .05 percentage points and rest of the

three quintiles were on the declining side when compared with the cross-

sectional year 1983-84.

During the year 2004-05, the ratio of top and bottom quintile viz, Q5/Q1 was

significantly 4.9 times. This suggests that the inequality gap has increased

by0.03 times, when compared with 1993-94.

For the final cross sectional year 2009-10, the percentage share of

consumption expenditures of all the quintiles, except Q5 (42.8%) were

reduced significantly. Furthermore, the inequality gap has also increased

following the pattern of 1993-94.

When the time period 1983-84(which is also considered pre-reform period in

this study) & 2009-10 are compared in order to ascertain the changes

occurred in the overall percentage distribution of shares in the

consumption expenditure over 26 years of the time period, the display is

not very encouraging as the inequality gap, i.e.,Q5/Q1 Q5/Q1 is five times,

which was 4.6 times in the year 1983-84. Acknowledging, the year 1992-

93as post reform period, when compared with contemporary 2009-10, the

top-bottom ratio in 1993-94 was 4.4 times, which has increased by 0.6 times

in 2009-10. The increase in the top-bottom ratio could be considered as

the cumulative effect of the increase in percentage share of Q5 by more

than 2.5 percentage points, when compared with the same quintile of

1993-94, which further reduced the share of other quintile groups (Q1 to Q4)

, consecutively with respect to the year 1993-94. Here, due to

considerations must be given to understand the increase and decrease

(When compared with the previous point of time) in Quintiles & Q5/Q1

Ratios, which has been explained through stated orderly points below;

1. The increase in Q1 by 0.5 percentage points during the year 1993-94

suggests that, this amount of percentage share in consumption

expenditure has been added to Q1 as a result of simultaneous

199

reduction in other quintile groups (Q2 to Q5) with respect to the

previous point of time 1983-84.

2. Similarly, in 1993-94, when Q3 & Q4 were reduced by 0.1 & 0.3

percentage points respectively. Which connotes that their percentage

points have been shifted to other quintile groups (Q1 in this case) from

1983-84.

3. As stated earlier, the ratio between top (Q5) & bottom (Q1) has

increased from 4.6 (1993-94) to 4.9 (2004-05). This (Ratio) 4.9 suggests

that, the top quintiles (Q5) percentage share in consumption

expenditure is 4.9 times of bottom quintile (Q1). Again, there was an

increase of 0.3 times in the share of before mentioned quintile groups,

when compared with the same ratio of 1983-84.

Under the aegis of above stated points, the relevance of the provided

table could be understood as it exhibits the percentage distribution and

the changes in percentage distribution among different quintile groups (Q1

to Q5) during the time periods under consideration.

Table 7.1 Shares of Quintiles in Total Consumption Expenditure

Quintile 1 8.7 8.8 9.3 9.2 9.2 8.9 9.1 8.9 9.9 8.6 8.5

Bottom 20 %

Quintile 2 12.8 12.6 13 13.3 12.7 12.2 12.8 12.4 14 12.2 12.1

Second 20 %

Quintile 3 16.6 16.3 16.5 16.8 16 16.4 16.5 16 17.8 15.8 15.7

Third 20 %

Quintile 4 21.8 21.3 21.7 21.7 20.6 21.5 21.5 20.2 22.1 21 20.8

Fourth 20 %

Quintile 5 40.1 41.1 39.5 39 41.5 41 40.1 42.5 36.2 42.2 42.8

Top 20 %

Q5 ÷ Q1 4.6 4.7 4.2 4.2 4.5 4.6 4.4 4.8 3.7 4.9 5

GINI INDEX 0.311 0.319 0.311 0.311 0.325 0.326 0.308 0.328 0.261 0.334 0.339

Source: http: //wdi.worldbank.org/table/12.9-tableno=2.9

http://dataworldbank.org/indicator/SI/.pov.Gini

Distribution Measure: Gini Ratio

The Gini Ratio column in the Table 7.2 exhibits the extent to which

Distribution of Consumption Expenditure; oscillate between perfect equality

and inequality, as measured by Gini Ratio for India for period overtime. The

200

Gini Ratio for India has usually varied between 0.311 percentage points

(1983-84) and 0.339 percentage points (2009-10), displaying no

appreciable change in the Distribution of Consumption Expenditure from

pre-reform to post-reform period. Over the past 26 years of time duration

since 1983-84, the Gini Ratio has declined considerably by 0.261

percentage points in the year 1999-2000, but for the entire time period

(1983-2010) the shift in Gini has remained more towards one (1) and less

towards zero (0) which explains that there has been no encouraging

change in context of reduction in inequality.

Table 7.2 Rural and Urban Gini Ratio in Consumption Expenditure of India

Source: Estimates of Planning Commission 61st Round

Note: Gini Ratio is calculated assuming that all individuals within each States have gross

income Equal to Per Capita GSDP. This method ignores the Inequality arising out of the

Unequal Distribution within each States, and focuses only on Inequality.

Income Distribution Pattern in India The issue of inequalities in India began in 1980‘s and still under debate, with

various studies unable to give a unanimous verdict.

In pursuance of determining the impact of changes in the per-capita

state domestic product (PCSDP) on inequalities, liaison between Gini Ratio

and PCSDP has been studied for 16 specific & larger states in India for four

time periods viz. 1983-84, 1993-94, 2004-05, & 2009-10, through cross

1983-84 1993-94 2004-05 2009-10

RURAL URBAN RURAL URBAN RURAL URBAN RURAL URBAN

INDIA 0.297 0.325 0.282 0.340 0.266 0.348 0.276 0.371

ANDHRA PRADESH 0.292 0.306 0.285 0.320 0.252 0.342 0.269 0.353

ASSAM 0.192 0.248 0.176 0.286 0.182 0.301 0.220 0.328

BIHAR 0.255 0.297 0.222 0.307 0.185 0.312 0.215 0.319

GUJRAT 0.252 0.264 0.236 0.287 0.251 0.295 0.252 0.309

HARYANA 0.271 0.304 0.301 0.280 0.295 0.326 0.278 0.357

J&K 0.221 0.235 0.234 0.281 0.197 0.241 0.221 0.307

KARNATAKA 0.299 0.330 0.266 0.315 0.232 0.358 0.231 0.375

KERALA 0.330 0.371 0.288 0.338 0.294 .353 0.350 0.400

MADHYA PRADESH 0292 0.290 0.277 0.327 0.237 0.351 0.276 0.365

MAHARASHTRA 0.283 0.329 0.302 0.351 0.270 0.350 0.244 0.380

ODISHA 0.266 0.294 0.243 0.304 0.254 0.330 0.247 0.375

PUNJAB 0.279 0.321 0.265 0.276 0.263 0.323 0.285 0.358

RAJASTHAN 0.340 0.301 0.260 0.290 0.204 0.303 0.214 0.316

TAMIL NADU 0.324 0.347 0.307 0.344 0.258 0.345 0.257 0.327

UTTAR PRADESH 0.290 0.312 0.278 0.323 0.234 0.339 0.438 0.321

WEST BENGAL 0.284 0.328 0.251 0.334 0.241 0.356 0.220 0.384

201

sectional analysis. The liaison between Gini & PCSDP has been analyzed by

adapting under linear, quadratic and cubic forms of the fitted line plot of

regression equation. The outcome of the Polynomial functions adapted to

establishing the liaison between LTNPCSDP (PCSDP transposed to

LTNPCSDP).

The Polynomial Regression Table: 7.3 exhibits that the relationship Gini &

LTNPCSDP remained inconsiderable, irrespective of the forms (Linear,

Cubic, Quadratic) fitted, although in this case, cubic equation has the

highest R2 (8.5%), hence considered as the best fit. (Fig. 7.3)

Table 7.3: Polynomial Functional Form for the Year 1983-84

Regression Coefficient

Polynomial Functional Form Constant LTNPCSDP LTNPCSDP2 LTNPCSDP3 R2 F P

Linear Form .286 .0270 - - 2.4 .34 .568

Quadratic Form .288 .0361 .1284 - 3.6 .25 .785

Cubic Form .295 .0486 .5953 1.031 8.5 .37 .776

Fig.7.2 Fitted Line: GINI versus LTNPCSDP

0.60.50.40.30.20.10.0-0.1-0.2

0.38

0.36

0.34

0.32

0.30

0.28

0.26

0.24

0.22

0.20

LTNPCSDP1983

GIN

I19

83

S 0.0392977

R-Sq 2.4%

R-Sq(adj) 0.0%

Regression

90% CI

Fitted Line PlotGINI1983 = 0.2864 + 0.02703 LTNPCSDP1983

202

In case of time period 1993-94, again the outcome of cubic equation is

proven to be the best fit, as the value of R2 & F is 30.6% & 5.49 respectively.

(Table. 7.4) The Polynomial Regression Equation for 1993-94 shows inequality

and LTNPCSDP have positive relationship at 90 per cent confidence

interval. (Fig. 7.4)

Table 7.4: Polynomial Functional Form for the Year 1993-94

Regression Coefficient

Polynomial Functional Form Constant LTNPCSDP LTNPCSDP2 LTNPCSDP3 R2 F P

Linear Form .254 .0602 - - 28.2 5.49 .034

Quadratic Form .264 .0125 .0484 - 29.3 2.69 .105

Cubic Form .272 .099 .3562 0.228 30.6 1.76 .208

Fig. 7.3 Fitted Line: GINI versus LTNPCSDP

0.90.80.70.60.50.40.30.20.10.0

0.34

0.32

0.30

0.28

0.26

0.24

0.22

LTNPCSDP1993

GIN

I19

93

S 0.0227951

R-Sq 28.2%

R-Sq(adj) 23.0%

Regression

90% CI

Fitted Line PlotGINI1993 = 0.2544 + 0.06019 LTNPCSDP1993

For the time period under consideration i.e. 2004-05, the linear form proved

to be the best fit as the Table. 6.3, exhibits the value of R-Square, Adjusted

R-Square, Test of Statistical Significance (F-value) and P-value (associated

with test statistics) are 24.3%, 29.3%,5.81 & 0.30 respectively. This gives a

203

statistical view that, in India, states with greater per capita state domestic

product, paradoxically bears greater unequal distribution of income. (Fig.

7.5)

Table 7.5: Polynomial Functional Form for the Year 2004-05

Regression Coefficient

Polynomial Functional Form Constant LTNPCSDP LTNPCSDP2 LTNPCSDP3 R2 F P

Linear Form .256 .0771 - - 29.3 5.81 .034

Quadratic Form .258 .0721 0 .0049 - 29.3 2.70 .105

Cubic Form .292 -0.404 1.02 -0.572 38.0 2.46 .113

Fig 7.4 Fitted Line: GINI versus LTNPCSDP

1.21.00.80.60.40.20.0

0.40

0.35

0.30

0.25

0.20

LTNPCSDP2005

GIN

I20

05

S 0.0344355

R-Sq 38.0%

R-Sq(adj) 22.5%

Regression

90% CI

Fitted Line PlotGINI2005 = 0.2921 - 0.4040 LTNPCSDP2005

+ 1.020 LTNPCSDP2005**2 - 0.5729 LTNPCSDP2005**3

204

The outcome (See Table. 7.6) of Polynomial Regression Analysis for 2009-10

exhibits that, the liaison between Gini and PCSDP remained insignificant,

regardless of whatever regression forms have been applied. Only the cubic

expression gives the maximum value of R- Square (21.4%) which must be

considered as the best fit at 10 per cent level of significance. The linear and

quadratic expressions were proved to be incapable, to qualify the best fit

criteria. (Fig. 7.6)

Fig 7.5Fitted Line: GINI versus LTNPCSDP

1.351.301.251.201.151.101.051.00

0.35

0.30

0.25

0.20

0.15

0.10

LTNPCSDP2010

GIN

I20

10

S 0.0396201

R-Sq 21.4%

R-Sq(adj) 1.8%

Regression

90% CI

Fitted Line PlotGINI2010 = 40.55 - 104.2 LTNPCSDP2010

+ 89.47 LTNPCSDP2010**2 - 25.49 LTNPCSDP2010**3

Table 7.6: Polynomial Functional Form for the Year 2009-10

Regression Coefficient

Polynomial Functional Form Constant LTNPCSDP LTNPCSDP2 LTNPCSDP3 R2 F P

Linear Form .276 .0295 - - 0.4 0.05 .822

Quadratic Form -0.071 .566 .254 - 0.7 0.05 .956

Cubic Form 40.55 -104.2 89.47 -25.49 21.4 1.09 .390

205

Hence, the above Polynomial Regression analysis of the Distribution

Paradigm for the select sixteen states of India for the specified time periods

(1983-84, 1993-94, 2004-05 & 2009-10) under consideration, suggests no

definite arrangements for the analysis of relationship between Gini Ratio

and PCSDP, nevertheless these are the trivial manifestation that these two

are positively associated with each other.

Determinants of Income Distribution In India

This part of the study attempts to determine the significant factors which

directly affect the Inequalities in sixteen states of India. Under the aegis of

four time periods; 1983-84, 1993-94, 2004-05 & 2009-10, nevertheless there

are numerous factors viz. Social, Economic and Demographic, which plays

the role of catalysts for income distribution being equal or unequal.

Under the present analysis 16 variables are considered for analysis, which

represents the Social Economic and Demographic Characters are as

follows;

1. Gini Ratio (considered as dependent variable)

2. Per Capita State Domestic Product in Log form(LTNPCSDP)

4. Per cent figure of Urban Population (PURPOP)

5. Literacy Rate (LITRAT)

6. Life Expectancy (LIFEX)

7. Infant Mortality per 1000 Child (INFMORT)

8. Population Growth Rate (GRTPOP)

7. Per cent value of Population Working (PWPOP)

9. Population Density (DENPOP)

10. Per cent value of Laborers Primary Sector (PLBPS)

Per cent value of Laborers Secondary Sector (PLBSS)

11. Per cent value of Laborers Tertiary Sector (PLBTS )

12. Per cent of Value Added by Primary Sector (PVAPS)

13. Per cent of Value Added by Secondary Sector (PVASS)

14. Per cent of Value Added by Tertiary Sector (PVATS )

206

15. Ratio of Sex defining Female per 1000 males (SXRAT)

Impact assessments of these variables on inequalities have been done

using various statistical techniques viz. General Regression, Multiple

Regression and Factor Analysis for reducing multi-colinearity problem.

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

STATISTICAL INTERPRETATION: REGRESSION ANALYSIS

The present Section interprets the statistical outcome of General Regression

Analysis applied for the select years 1983-84, 1993-94, 2004-05 and 2009-10.

During the year 1983-84, Table. 6.7 encapsulates the outcome of regression

Table 7.7 Determinants of Income Distribution Simple Regression Analysis- Gini Ratio as dependent variable (1983-84)

Variable Constant Regression Coefficient R2 F

(T-value) (T-value)

LTNPCSDP 0.286 0.0270 2.4 .34

(14.83) (0.58)

PURBPOP 0.246 0.002 20.4 3.51

(8.74) (1.87)

LITRAT 0.258 0.001 16.3 2.53

(9.06) (1.59)

LIFEX 0.121 0.003 12.3 1.96

(.970) (1.40)

INFMORT 0.344 -0.007 14.5 2.38

(10.58) (-1.54)

GRTPOP 3.15 -0.009 0.5 0.07

(4.48) (-0.27)

PWPOP 0.308 -0.001 1.5 0.20

(16.80) (-0.45)

DENPOP 0.286 0.000 2.5 0.37

(14.54) (0.60)

PLBPS 0.391 0 .001 16.0 2.48

(6.77) (-1.58)

PLBSS 0.264 0.005 13.8 2.08

(10.55) (1.44)

PLBTS 0.281 0.001 1.5 0.22

(8.29) (0.47)

PVAPS 0.291 0 .001 0.4 0.06

(13.56) (0.24)

PVASS 0.296 -0.001 0.0 0.0

(20.25) (-0.01)

PVATS 0.216 0.001 12.1 1.93

(3.72) (1.39)

SXRAT -0.012 0.003 14.5 2.38

(-0.06) (1.54)

207

analysis, which further suggests that, on the basis of Coefficient of

Determination (R2) PURPOP, LITRAT & PLBPs have significant and positive

impact on GiniRatio. SEXRAT, PLBSS & PVATS were also affecting inequality

positively but significant only at 10 per cent level. Similarly, INFMORT &

PLBSS are adversely affecting inequalities.

For the year 1993-94, the coefficient in regression analysis for PURPOP,

PLBTS, PVASS, PVATS, PVAPS were found to be positively and significantly

influencing inequalities. PLBSS & PWPOP are also impinging upon Gini ratio

positively but significantly, whereas INFMORT shows a negative relation with

the dependent variable i.e. Gini.

208

Table 7.8 Determinants of Income Distribution

Simple Regression Analysis- Gini Ratio as dependent variable (1993-94)

Variable Constant Regression Coefficient R2 F (T-value) (T-value)

LTNPCSDP 0 .254 0.060 28.2 5.49

(16.46) (2.34)

PURBPOP 0.238 0.002 40.5 9.53

(13.88) (3.09)

LITRAT 0.260 0.001 4.8 0.70

(7.66) (0.84)

LIFEX 0.129 0.003 20.3 3.57

(.970) (1.40)

INFMORT 0.328 -0.001 21.0 3.72

(15.14) (-1.93)

GRTPOP 0.334 -0.022 9.4 1.46

(8.61) (-1.21)

PWPOP 0.268 0.004 23.6 4.32

(23.97) (2.08)

DENPOP 0.279 0.002 4.4 0.65

(21.24) (0.81)

PLBPS 0.292 -0.001 0.0 0.0

(6.77) (-1.58)

PLBSS 0.267 0.003 21.9 3.92

(21.79) (1.44)

PLBTS 0.239 0.003 34.2 7.29

(12.53) (2.70)

PVAPS 0.263 0.005 28.4 5.56

(22.14) (2.36)

PVASS 0.272 0.0027 29.2 5.78

(31.53) (2.40)

PVATS 0.193 0.003 29.2 5.77

(4.81) (2.40)

SXRAT 0.095 0.0021 12.6 2.01

(0.70) (1.42)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

In the year 2004-05, three variables i.e. PLBPS, INFMORT & LIFEX with higher

coefficient of Determination (R2) which are 58.4%, 35.8% & 31.7%

respectively, affecting negatively to the Gini ratio. PLBTS, PLBSS, LTNPCSDP,

PURPOP & PVATS exhibit positive strong relation with Gini as the R2 value of

all the above variables are on the higher side. Further T-value (Slope of the

line) and F-value (F-test statistic) explains a positive impact on Gini.

209

Table 7.9 Determinants of Income Distribution

Simple Regression Analysis- Gini Ratio as dependent variable (2004-05)

Variable Constant Regression Coefficient R2 F

(T-value) (T-value)

LTNPCSDP

PURBPOP

LITRAT

LIFEX

INFMORT

GRTPOP

PWPOP

DENPOP

PLBPS

PLBSS

PLBTS

PVAPS

PVASS

PVATS

SXRAT

0.257

(10.05)

0.259

(9.67)

0.216

(2.63)

-0.022

(-0.16)

0.389

(13.97)

0.371

(10.66)

0.300

(15.48)

0.291

(15.23)

0.457

(13.93)

0.249

(10.58)

0.218

(8.64)

0.289

(14.86)

0.305

(21.12)

0.180

(2.82)

0.109

(.55)

0.078

(2.41)

0.094

(2.19)

0.015

(1.21)

0.053

(2.55)

-0.038

(-2.80)

-0.302

(-1.68)

0.003

(0.88)

0.0001

(1.41)

-0.0025

(-4.43)

0.001

(2.98)

0.004

(4.00)

0.005

(1.53)

0 .002

(0.92)

0.003

(2.14)

0.001

(1.05)

29.3

25.5

9.4

12.3

35.8

16.8

5.2

12.5

58.4

38.8

53.4

14.3

5.7

24.6

7.3

5.81

4.79

1.45

1.96

7.82

2.83

0.77

1.99

19.64

8.89

16.03

2.34

0.84

4.58

1.10

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

During the time period 2009-10, PLBPS, PWPOP exhibit a positive &

significant relation with inequalities, whereas PLBTS, LIFEX & LITRAT are

inversely affecting inequalities at 5%, & 10% significantly.

210

Table 7.10 Determinants of Income Distribution

Simple Regression Analysis- Gini Ratio as dependent variable (2009-

10) Variable Constant Regression Coefficient R2 F

(T-value) (T-value)

LTNPCSDP 0.276 -0.0295 0.4 0.05

(1.79) (-0.23)

PURBPOP 0 .249 -0 .0028 0.6 0.09

(8.16) (3.09)

LITRAT 0.332 -0 .0123 5.0 0.74

(3.12) (-0.864)

LIFEX 0 .482 -0.0036 8.3 1.26

(.970) (1.40)

INFMORT 0.231 0.0021 0.7 0 .10

(7.43) (0.32)

GRTPOP 0.206 0.023 5.4 0 .79

(5.17) (0.89)

PWPOP 0.219 0.003 11.0 1.73

(11.50) (1.31)

DENPOP 0.238 0.006 0.2 0.03

(11.45) (0.17)

PLBPS 0.148 0.018 17.9 3.06

(6.77) (-1.58)

PLBSS 0.257 -0.002 2.7 0.38

(9.23) (-0.62)

PLBTS 0.322 -0.0033 23.7 4.35

(8.08) (-2.09)

PVAPS 0.227 0.0027 4.2 0.62

(11.15) (0.79)

PVASS 0.240 0.0020 0.1 0.01

(16.45) (0.10)

PVATS 0.182 0.0013 4.3 0.63

(4.81) (2.40)

SXRAT 0.179 0.0007 0.7 0.10

(.70) (1.42) *indicates significant at 5 per cent level **indicates significant at 10 per cent level

MULTIPLE REGRESSION ANALYSIS: GINI & ASSOCIATED VARIABLES

For the purpose of figuring out the multiple repercussions of all the 15 select

variables on Gini, a Multiple Regression Analysis has been carried out. The

outcome of this analysis could be witnessed through tables (Table. 6.10 to

6.13), which suggests the causation scenario under the previously specified

years (1983-84, 1993-94, 2004-05 & 2009-10).

211

In case of specified year 1983-84, the Multiple regression analysis ,

establishes the fact that PLBPS (Per cent value of Laborers Primary Sector),

PLBSS (Per cent of Value Added by Secondary Sector) and PVATS (Per cent

of Value Added by Tertiary Sector), among which PLBPS (Per cent value of

Laborers Primary Sector) and PLBSS (Per cent of Value Added by

Secondary Sector) are negatively but significantly where as PVATS (Per

cent of Value Added by Tertiary Sector) is positively and significantly

influencing the Gini ratio with 43.44 per cent of variation at 5 per cent level

of confidence.

Table: 7.11 Multiple Regression (1983-84)

Constant PLBPS PLBTS PVATS R2

(T-VALUE) (T-VALUE) (T-VALUE)

0.3925 -0.0014** - - 16.42**

(-1.54)

0.5440 -0.0027* -0.0034* - 33.68

(-2.36) (-1.69)

0.4399 -0.0021* -0.0045* 0.0028* 43.84*

(-1.78) (-2.15) (1.34)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

In the year 1993-94, PLBTS (Per cent value of Laborers Tertiary Sector),

PWPOP (Per cent value of Population Working) and SXRAT (Ratio of Sex

defining Female per 1000 males) are convincingly reflecting their impact

on inequalities at 5 per cent significant level with 61.11 per cent variance.

Whereas PVAPS (Per cent of Value Added by Primary Sector), PVASS (Per

cent of Value Added by Secondary Sector), LTNPCSDP (Logarithmic

Transformation Per Capita State Domestic Product) and SXRAT (Ratio of Sex

defining Female per 1000 males) proved to be a best alternative which

were influencing inequalities at 10 per cent significance level.

212

Table: 7.12 Multiple Regression (1993-94)

Constant PLBTS PWPOP SXRAT R

(T-VALUE) (T-VALUE) (T-VALUE)

0.2483 -0.00208** - - 39.12**

(2.89)

0.2297 -0.0022* 0.0026* - 61.11*

(3.62) (2.61)

0.1103 0.0019 * 0.0027* 0.0013** 68.54*

(3.34) (2.80) (1.61)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

During the year 2004-05 putting together a variance of 46.72 per cent, here

PLBPS displays a significant and negative variance with inequalities,

whereas PWPOP proved to be a positive at 5 per cent level of significance.

In this fashion, the overall enquiry through statistical analysis establishes the

fact that the structural factors like PLBPS, PLBSS & PVATS, and demographic

factors such as LIFEX, LITRAT, PWPOP & PURPOP, along with economic

factors like LTNPCSDP, are the significant factors which have a determining

effect on unequal distribution of income as measured by Gini Ratio. Which

further suggests, importance of PCSDP (Per Capita State Domestic

Product), PLBPS (Per cent value of Laborers Primary Sector) & INFMORT

(Infant Mortality per 1000 Child) are the key determinant which are in some

way or the other, negatively affecting Gini Ratio.

213

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

For the year 2009-10, PLBTS, PVATS, LITRAT and DENPOP were identified as

significant determinants for inequalities. All these variables were found to

be significant at 5 per cent level and are able to explain the overall

variance as close to 69.86 per cent in inequality. Higher contribution of

tertiary sector to gross domestic product was found to be positively

affecting inequalities. LITRAT and DENPOP were found to be positively and

significantly affecting Gini, as higher dependency on service sector, low

rate of literacy and high density of population was seen to be promoting

inequalities.

Table: 7.13 Multiple Regression (2004-05)

Constant PLBPS PLBTS R2

(T-VALUE) (T-VALUE)

0.4572 -0.00246* - 58.38*

(-4.43)

0.4425 -0.00250* -0.0030* 65.40*

(-4.76) (1.62)

214

Table: 7.14 Multiple Regression (2009-10)

Constant PLBTS PVATS LITRAT DENPOP R2

(T-VALUE) (T-VALUE) (T-VALUE) (T-VALUE)

0.3217 -0.0032* - - - 23.70*

(-2.09)

0.2015 -0.0052* 0.0035* - - 50.46*

(-3.48) (2.65)

-0.00016 -0.0093* 0.0038* 0.0039* - 65.76*

(-4.24) (3.32) (2.32)

-0.01181 -0.001181* 0.0034* 0.0043* 0.00003* 69.86*

(-4.50) (3.01) (2.57) (1.22)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Thus the entire analysis suggests that the variables like PLBPS, PLBTS, LITRAT,

DENPOP, and PVATS are significant determinants of inequality, as reflected

by the Gini. Nevertheless, from policy point of view, for decreasing

inequality it desired to promote economic activities so that PCSDP could

be raised, that would further percolate the higher per capita value

addition in primary sector that would prove to be helpful in reducing

inequality.

GINI RATIO AND ASSOCIATED VARIABLES: DEGREE OF CORRELATION

This part of the study emphasizes upon the analysis of the degree of

correlation between Gini Ratio and its associated variables. Fact findings

have been represented along with the tables (7.15 to 7.17) for the specified

years i.e. 1983-84,1993-94, 2004-05 & 2009-10, by taking into consideration,

sixteen Indian States.

215

Table 7.15 Correlation Analysis of Select Inequality Determinants 1983-84

GINI LTNPCSDP PURPOP LIFEX INFMORT GRTPOP DENPOP PLBTS PVAPS PVASS PVATS SXRAT

GINI 1 0.15 0.44 -0.38 -0.38 -0.07 0.15 0.012 0.06 0 0.34 0.38

LTNPCSDP - 1 0.4 0.21 0.21 -0.05 0.03 0.3 0.41 0.38 -0.17 0

PURPOP - - 1 0.43 -0.49 0.03 0.01 0.54 0.39 0.68 0.42 0

LIFEX - - - 1 -0.89 -0.19 0.51 0.62 -0.04 0.19 0.51 0.29

INFMORT - - - - 1 -0.03 -0.27 0.46 0.1 -0.2 -0.59 -0.22

GRTPOP - - - - - 1 -0.03 -0.46 -0.02 -0.18 -0.2 -0.61

DENPOP - - - - - - 1 0.5 0.13 0.16 0.33 0.3

PLBTS - - - - - - - 1 0.4 0.49 0.64 0.12

PVAPS - - - - - - - - 1 0.54 0.39 0.15

PVASS - - - - - - - - - 1 0.32 0.1

PVATS - - - - - - - -

- 1 0.22 SXRAT - - - - - - - - - - - 1

The correlation analysis of Inequalities as measured by Gini and its

associated variable for the year 1983-84, suggest that there are greater

degree of interdependence among them. LTNPCSDP, GRTPOP, PLBTS &

PVAPS exhibit that they are putting an impact on Gini. Furthermore,

GRTPOP & PVAPS are negatively associated with inequalities. INFMORT

reflects a significant but negative association with LIFEX, whereas DENPOP

has positive but significant correlation with LIFEX, again DENPOP also bears

a negative and significant relation with GRTPOP. PLBTS has positive and

significant correlation with PURPOP, LIFEX & DENPOP, similarly PVASS exhibits

mutual interdependence with PURPOP & PVAPS significantly. The other

variable like PVATS shows positive association with LIFEX & PLBTS, and show

a significantly negative correlation with INFMORT. In the same year (1983-

84) SXRAT was also negatively but significantly associated with GRTPOP.

The above analysis suggests, a mutual correlation among the variable with

each other either positively or negatively, which further suggests how these

variables representing social, economic & demographic characters, affect

each other and make a significant impetus on Income Distribution in India.

During the year 1993-94, correlation outcome (Table. 7.16) suggest that

Gini is positively and with a significant extent associated with LTNPCSDP,

216

Table 7.16 Correlation Analysis of Select Inequality Determinants 1993-94

GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT

GINI 1 0.48 0.61 0.21 0.43 -0.44 -0.31 0.47 0.22 0.11 0.44 0.59 0.53 0.54 0.53 0.34

LTNPCSDP - 1 0.74 0.24 0.43 -0.47 -0.17 0.12 0.01 -0.16 0.69 0.45 0.41 0.4 0.17 0.22

PURPOP - - 1 0.3 0.53 -0.51 -0.19 0.13 -0.03 -0.22 0.76 0.6 0.36 0.62 0.37 0.18

LITRAT - - - 1 0.71 -0.85 -0.58 -0.42 0.39 -0.71 0.48 0.66 -0.24 -0.03 0.59 0.54

LIFEX - - - - 1 -0.88 -0.46 -0.3 0.4 -0.53 0.54 0.68 -0.05 0.04 0.61 0.43

INFMORT - - - - - 1 0.59 0.25 -0.55 0.51 -0.65 -0.74 0.04 0.15 -0.66 -0.58

GRTPOP - - - - - - 1 0.1 -0.49 0.09 -0.48 -0.54 0.11 -0.04 -0.3 -0.79

PWPOP - - - - - - - 1 0.11 0.57 0.01 -0.03 0.82 0.65 0.12 -0.07

DENPOP - - - - - - - - 1 0.01 0.42 0.44 0.13 -0.02 0.47 0.25

PLBPS - - - - - - - - - 1 -0.11 -0.21 0.37 0.21 -0.33 -0.17

PLBSS - - - - - - - - - - 1 0.73 0.31 0.46 0.36 0.28

PLBTS - - - - - - - - - - - 1 0.23 0.34 0.64 0.38

PVAPS - - - - - - - - - - - - 1 0.61 0.28 -0.14

PVASS - - - - - - - - - - - - - 1 0.24 0.07

PVATS - - - - - - - - - - - - - - 1 0.47

SXRAT - - - - - - - - - - - - - - - 0.36

- - - - - - - - 1

217

PURPOP,PLBTS, PVAPS, PVASS & PVATS. PURPOP exhibits a positive and significant

association with Gini & LTNPCSDP. LIFEX also reflects a higher interdependence

with LTNPCSDP, PURPOP and LITRAT at 5 per cent confidence interval. Similarly

other variables like INFMORT, GRTPOP, DENPOP, PLBPS, PLBSS, PLBTS, PVAPS, PVASS,

and PVATS & SXRAT had shown a higher degree of association with each other.

Hence in case of 1993-94, it could be concluded that the role of these specified

variables have increased with reference to the previous year (1983-84), as their

effectiveness either positive or negative on Inequalities have been established by

the Correlation outcome.

The Correlation Analysis for the year 2004-05(Table. 7.17) suggests that, Gini

bears a positive and significant association with LTNPCSDP, PLBTS, PURPOP,

LIFEX, PLBTS & PVATS. Similarly, from the table itself it could be witnessed

that all the specified variable exhibit a greater degree of mutual

interdependence with each other varying from 5 to 10 per cent

significance level. Accordingly these variables play a crucial role in

determining the Inequality level in the select sixteen States of India,. Hence

on an overall basis this correlation analysis suggests the significant role of

the specified variables in Distribution Parity and Economic Growth.

218

Table 7.17 Correlation Analysis of Select Inequality Determinants 2004-05

GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT

GINI 1 0.54 0.5 0.3 0.56 -0.59 -0.41 0.22 0.35 -0.76 0.62 0.73 0.37 0.23 0.49 0.27

LTNPCSDP - 1 0.84 0.37 0.51 -0.47 -0.36 -0.18 -0.25 -0.56 -0.68 0.42 0.25 0.63 0.27 0.25

PURPOP - - 1 0.31 0.52 -0.55 -0.28 -0.18 -0.15 -0.66 0.8 0.55 0.24 0.73 0.33 0.03

LITRAT - - - 1 0.61 -0.66 -0.47 -0.4 0.11 -0.5 0.32 0.54 -0.37 0.13 0.41 0.4

LIFEX - - - - 1 -0.86 -0.4 -0.28 0.26 -0.77 0.6 0.7 -0.11 0.15 0.55 0.3

INFMORT - - - - - 1 0.58 0.08 0.45 0.77 -0.66 -0.75 0 -0.29 -0.7 -0.5

GRTPOP - - - - - - 1 0.05 0.18 0.56 -0.46 -0.57 -0.06 -0.05 -0.47 -0.8

PWPOP - - - - - - - 1 0.19 0.04 0.19 -0.04 0.9 0.53 0.15 0

DENPOP - - - - - - - - 1 -0.23 0.24 0.25 0.23 -0.07 0.18 0.15

PLBPS - - - - - - - - - 1 -0.84 -0.94 -0.18 -0.27 -0.58 -0.2

PLBSS - - - - - - - - - - 1 0.67 0.33 0.47 0.38 0.13

PLBTS - - - - - - - - - - - 1 0.18 0.26 0.67 0.2

PVAPS - - - - - - - - - - - - 1 0.5 0.21 -0.16

PVASS - - - - - - - - - - - - - 1 0.09 -0.03

PVATS - - - - - - - - - - - - - - 1 0.1

SXRAT - - - - - - - - - - - - - - - 0.2

- - - - - - - - 1

219

During the year 2009-10 (Table. 7.18) Gini had shown a significant relation

with LTNPCSDP & PLBTS where LTNPCSDP has a negative and PLBTS makes a

positive impact on Gini. Similarly all the other variables are displaying a

correspondence with each other, positively or negatively in a significant

way.

220

Table 7.18 Correlation Analysis of Select Inequality Determinants 2009-10

GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT

GINI 1 -0.06 -0.08 -0.22 -0.28 -0.08 0.23 0.33 0.04 0.42 -0.16 -0.48 0.2 0.02 0.2 0.08

LTNPCSDP - 1 0.3 0.14 0.23 -0.24 0.24 0.3 0.47 -0.33 0.47 0.3 0.3 0.34 0.27 -0.33

PURPOP - - 1 0.74 0.74 -0.79 -0.54 0.06 -0.04 -0.74 0.72 0.65 0.1 0.59 0.39 0.33

LITRAT - - - 1 0.73 -0.7 -0.69 -0.14 0.18 -0.7 0.56 0.83 -0.07 0.35 0.35 0.54

LIFEX - - - - 1 -0.91 -0.47 -0.13 0.37 -0.84 0.26 0.79 -0.11 0.25 0.42 0.32

INFMORT - - - - - 1 0.58 0.01 -0.33 0.76 -0.66 -0.73 0.04 -0.28 -0.61 -0.41

GRTPOP - - - - - - 1 0.16 0.04 0.6 -0.39 -0.68 -0.09 0.02 -0.4 -0.76

PWPOP - - - - - - - 1 0.22 0.12 0.06 -0.21 0.92 0.47 0.22 -0.01

DENPOP - - - - - - - - 1 -0.3 0.33 0.37 0.19 -0.17 0.38 0.14

PLBPS - - - - - - - - - 1 -0.73 -0.77 0.85 -0.14 -0.34 -0.43

PLBSS - - - - - - - - - - 1 0.58 0.16 0.37 0.17 0.14

PLBTS - - - - - - - - - - - 1 -0.13 0.2 0.49 0.44

PVAPS - - - - - - - - - - - - 1 0.42 0.07 -0.15

PVASS - - - - - - - - - - - - - 1 0.07 0.48

PVATS - - - - - - - - - - - - - - 1 0.11

SXRAT - - - - - - - - - - - - - - - 0.21

- - - - - - - - 1

221

Hence, the above study depicts that he Social, Economic and

Demographic factors are vital factors in shifting the Gini (as a measure of

inequality) in positive or negative direction.In order to avoid the problem of

multi-colinearity (as these variables are highly correlated) the analysis

further requires an analysis of Factors through Rotated Factor Analysis

approach.

REDRESSING MULTI-COLLINEARITY: FACTOR ANALYSIS

In order to determine the significant factors from the select variables which

are highly interdependent and creating a problem of multi-colliniearity, an

attempt has been to correct the problem of multi-colliniearity by applying

Factor Analysis approach under which Rotated Factor Analysis (Varimax)

technique has been exercised. The outcome of the above approach for

the cross-sectional year 1983-84, 1993-94, 2004-05 & 2009-10 has been

exhibited in Table7.20-7.24 and in year-wise write-up below subsequently.

ROTATED FACTOR ANALYSIS

Write-up for the year 1983-84:

The Rotated Analysis Technique with orthogonal Varimax Rotation has

been used. Taking into consideration twelve variables on the basis of

Regression results, the analysis has yielded four factors explaining total

variance of 78.023 per cent; Factor 1 of 1983-84 shows high loadings for

INFMORT, PLBPS, PLBTS, PVATS, DENPOP, PURPOP & LIFEX, further this factor

explains 30.076 per cent. The Second Factor displays 18.99 per cent of

individual variance and 48.275 per cent of cumulative variance and the

variables loaded heavily in in this factor are; PVAPS, PVATS, PVASS, PLBTS &

PURPOP.

222

Fig.7.7

Factor Analysis 1983-84: Eigenvalues

Fig.7.8

Scree Plot

223

Table 7.19 Factor Analysis on Correlations with 4 Factors: Varimax (1983-84)

Rotation Matrix

-0.78982 0.44939 -0.39343 0.13946

0.31426 0.65316 0.32964 0.60495

0.49268 0.07513 -0.85716 0.13002

0.18629 0.60480 0.04282 -0.77310

Final Communality Estimates

LTNPCSDP 0.81339

PURPOP 0.82314

LIFEX 0.93256

INFMORT 0.95037

GRTPOP 0.86910

DENPOP 0.61856

PLBPS 0.90115

PLBTS 0.75504

PVAPS 0.78783

PVASS 0.56355

PVATS 0.84365

SXRAT 0.50446

Variance Explained by Each Factor

Factor Variance Percent Cum Percent

Factor 1 3.6091 30.076 30.076

Factor 2 2.1839 18.199 48.275

Factor 3 2.1684 18.070 66.345

Factor 4 1.4013 11.678 78.023

Rotated Factor Loading

Factor 1 Factor 2 Factor 3 Factor 4

INFMORT 0.965567 -0.041863 -0.002732 0.127646

PLBPS 0.889690 -0.151035 0.290652 -0.048037

PVAPS 0.124163 0.853049 0.041244 0.207406

PVATS -0.547724 0.632202 -0.186061 -0.330675

PVASS -0.190531 0.590065 -0.079064 0.415717

PLBTS -0.494451 0.569831 -0.385325 0.193318

DENPOP -0.318446 0.176947 -0.695210 -0.050227

GRTPOP -0.048309 -0.130251 0.921182 -0.034924

LTNPCSDP 0.090640 0.210707 -0.053778 0.870568

PURPOP -0.544139 0.496186 0.171766 0.501344

LIFEX -0.922223 0.019068 -0.274506 0.079681

SXRAT -0.174668 -0.140839 -0.673250 0.029100

224

Similarly, this factor analysis exhibits negatively loaded variable such as

PLTS, DENPOP & SXRAT and positively loaded variable such as GRTPOP.

Factor 3 explains individual variance of 18.070 per cent and cumulative

variance of 66.345 per cent. Finally the Forth Factor explains high factor

loading for PVATS although it is negatively loaded (which means it is quite

helpful in reducing inequality). Further the positively loaded variables are

PVASS, LTNPCSDP and PURPOP which means these variables assumed to

be significant in augmenting Inequality. Overall the individual and

cumulative variances for the same factor are 11.678 % & 78.023 %

respectively. The Final Communality estimates for almost all variables are

almost one (1), leaving few variables like, DENPOP, PVASS & SXRAT which

are on the lower side of the communality estimates showing minimum

estimates of 0.61856, 0.56355 & 0.50446 respectively. These variables further

explain they are weakly related with their respective factors. Substantively,

these factors exhibit that the variables are appropriate for Factor Analysis;

again they display four clear cut patterns and suggest that they are not

correlated with each other.

Write-up for the year 1993-94:

Under this specified period of time starting from the Eigen Value, which

suggests that the, first factor with bears the Eigen Value of 4.9407 (Highest

among the rest) which accounts for 49.407 per cent of total information

among all three factors. The second Factor has the Eigen Value of 2.5122

which accounts for 25.122 per cent of total information. The Third Factor

exhibits Eigen Value of 1.0600 which corresponds for 10.600 per cent of

total sought information, here the terminology ―total information‖ connotes

total variance explained.

As the Table 7.20 suggests, the Rotated Factor Analysis for the year 1993-94

contains three factors which further exhibits, that the first factor have 3

items(PURPOP, LTNPCSDP & PLBSS) which are above 0.50 benchmark and

one item (PLBTS) bears the loading almost equal to bench mark with overall

225

cumulative variance of 29.691 per cent. The communality estimate for all

the items are almost closer to 1 (Standard) but certain items (PURPOP,

LIFEX, INFMORT, PWPOP, PLBSS, PVAPS) have more than 0.75 estimated

value. Factor 2 explains, 26.154 per cent and total cumulative variance of

55.845 per cent. Under this factor 5 items were selected out of these five

items, three items (PVATS, LIFEX & PLBTS) have higher loadings where as

remaining two items (PLBSS & INFMORT) bears lower loading and which

further display weak and negative relation to their respective factor.

Table 7.20 Factor Analysis on Correlations with 3 Factors: Varimax (1993-94)

Rotation Matrix

Final Communality Estimates

LTNPCSD 0.72297

PURPOP 0.83905

LIFEX 0.84004

INFMORT 0.90410

PWPOP 0.87901

PLBSS 0.78262

PLBTS 0.70575

PVAPS 0.82567

PVASS 0.72132

PVATS 0.73593

Variance Explained by Each Factor

Factor Variance Percent Cum

Percent

Factor 1 2.9691 29.691 29.691

Factor 2 2.6154 26.154 55.845

Factor 3 2.3719 23.719 79.565

Rotated Factor Loading

Factor 1 Factor 2 Factor 3

PURPOP 0.845653 0.275292 0.219400

LTNPCSDP 0.810666 0.222372 0.127844

PLBSS 0.796153 0.369538 0.110482

PVATS 0.039554 0.813805 0.268493

LIFEX 0.431739 0.767520 -0.254071

PLBTS 0.500198 0.669176 0.088071

PWPOP -0.016336 -0.086560 0.933407

PVAPS 0.186543 0.096045 0.884110

PVASS 0.520865 0.032175 0.670063

INFMORT -0.467354 -0.797936 0.221300

226

Write-up for the year 2004-05:

For this period 12 items (Variables) are selected on the basis of regression

analysis for the purpose of Rotated Factor Analysis. Under this analysis,

Rotated Factor loadings has extracted three factors out of which Factor 1

displays that inter-correlation for three items

Table 7.21 Factor Analysis on Correlations with 3 Factors: Varimax (2004-05)

Rotation Matrix

0.81209 0.47270 0.34214

-0.21385 0.78662 -0.57921

-0.54293 0.39721 0.73990

Final Communality Estimates

LTNPCSDP 0.75472

PURPOP 0.85685

LIFEX 0.79221

INFMORT 0.86622

GRTPOP 0.81874

PLBPS 0.92869

PLBSS 0.80993

PLBTS 0.85570

PVAPS 0.36056

PVASS 0.78377

PVATS 0.54765

SXRAT 0.94760

Variance Explained by Each Factor

Factor Variance Percent Cum Percent

Factor 1 4.4897 37.414 37.414

Factor 2 2.8399 23.666 61.080

Factor 3 1.9930 16.608 77.689

Rotated Factor Loading

Factor 1 Factor 2 Factor 3

PLBTS 0.894307 0.203343 0.120673

LIFEX 0.869949 0.084131 0.168292

PLBSS 0.664208 0.598900 0.100387

PVATS 0.650110 0.047086 0.350416

PVASS 0.062651 0.883032 0.009701

PURPOP 0.487223 0.785303 0.052573

LTNPCSDP 0.342104 0.752816 0.266364

PVAPS -0.009465 0.580196 -0.154403

GRTPOP -0.420454 -0.065151 -0.798571

INFMORT -0.831252 -0.165673 -0.384439

SXRAT 0.145118 -0.072841 0.959811

PLBPS -0.906677 -0.306260 -0.113271

227

(GRTPOPO, INFMORT & PLBPS) are weak as they come out with negative

values. Similarly, PURPOP and LTNPCSDP could be dumped because of

their weak relation with other items, remaining items (PLBTS, LIFEX, and

PLBSS & PVATS) with equal to or more than 0.50 values could be retained.

Factor 2 Exhibits higher correlation values for items like PLBSS, PVASS,

PURPOP, LTNPCSDP, PVASS with their respective factors. Similarly, Factor 3

displays SXRAT as its significant item as its loading is strong.

Write-up for the year 2009-10: During this Specified year 10 variables were

Factor Analyzed. The Final Communality Estimates for all the ten items

under analysis exhibits that almost all the variables bears high

communalities displaying a proximity towards one (Standard) ,except

PVATS which shows weak association with its Factor.

As far as the variance is concerned, Factor 1 displays point variance of

4.3796 per cent of individual variance and 43.796 per cent of cumulative

variance. Rotated Factor Loadings for Factor 1 is positive and above 0.50

for 5 items (PLBTS, LITRAT, LIFEX, PLBSS & PVATS). Similarly, PLBPS and GRTPOP

also represent significant but negative loading with Factor 1.

In case of Factor 2 the cumulative variance is 63.384 per cent and it

considers only two items (PWPOP & PVAPS) as significant and positively

related. Similarly, Factor 3 has an Eigen Value of 1.3139 and overall

cumulative variance of 76.523 per cent. Under this factor has a high

loading of 0.8312 where as PLBSS and GRTPOP has weak relational

tendency.

The overall outcome of Factor Analysis for the select four time

periods exhibit various number of factors with their underlying items and in

almost all Factor Analysis the extracted items like LTNPCSDP, PVAPS, PLBSS,

GRTPOP, INFMORT, PVATS, PVAPS, PWPOP & PURPOP identified as

significant items which in common parlance play a vital role in

determination of Inequality (as these variables are a mix of Social,

economic and Demographic factors) in select sixteen States of India.

228

Table 7.22 Factor Analysis on Correlations with 3 Factors: Varimax (2009-10)

Final Communality Estimates

LTNPCSDP 0.78228

LITRAT 0.73510

LIFEX 0.79189

GRTPOP 0.88180

PWPOP 0.93112

PLBPS 0.83137

PLBSS 0.61106

PLBTS 0.86236

PVAPS 0.87934

PVATS 0.34599

Variance Explained by Each Factor

Factor Variance Percent Cum Percent

Factor 1 4.3796 43.796 43.796

Factor 2 1.9587 19.587 63.384

Factor 3 1.3139 13.139 76.523

Rotated Factor Loading

Factor 1 Factor 2 Factor 3

PLBTS 0.905904 -0.136911 0.151500

LITRAT 0.853218 -0.079397 0.028514

LIFEX 0.832044 -0.131708 0.286794

PLBSS 0.642769 0.078992 0.437801

PVATS 0.529396 0.256363 0.002176

PWPOP -0.083637 0.953923 0.118973

PVAPS -0.036890 0.927555 0.132759

PLBPS -0.853030 0.111815 -0.302005

LTNPCSDP 0.173869 0.247313 0.831195

GRTPOP -0.824034 0.019862 0.449860

229

SECTION-III

Trends in Poverty

In the present section an analysis of Income Distribution has been carried

out vis-à-vis Poverty. In India Poverty, has remained an undisputed cause of

worry, for Socio-economic thinkers & planners. With an ultimate objective of

reducing Poverty, there have been various plans, policies and strategies

evolved since Independence. As a matter of fact there has been more

than 60 years since Independence; even then we accommodate more

than 30 crores of people living under the state of abject Poverty. One

cannot deny the fact that the incidence of Poverty has penetrated in all

dimensions, whether it is Demographic, Social, or Economic dimensions,

although there are variations in their degrees of intensity. Similarly, one

could not deny the fact that, there were various efforts made by the

Government in order to alleviate Poverty, considering the unpredictable

behavior of our economy as a whole, under the plan period, the policy

makers during pre-reform period concentrated their efforts towards growth

cum moderate development on the basis and faith in ―Trickle Down

Approach‖ which suggests that the ―favorable outcome naturally

permeates to all‖. But the outcome remained unchanged as the

percentage of poor stick to the same alarming position. After this not so

encouraging experience, the policy makers shifted their efforts towards

various social welfare and social security programs, which result a decline

in percentage of poor to almost 37 percent from 50 per cent in 1970s.

During the post-reform period due to emergence of numerous reformation

steps, the Government focused itself towards inclusive growth, which

connotes development through participation, which further alleviated the

poverty at almost 29 per cent level. Although this declining percentage

figure over the period of time seems impressive but when these

percentage figures are converted into number of people become almost

230

350 million, which exhibits the darker side of truth, as these 350 million

people living under the sufferance of dire poverty till 2009-10 as per the

Planning Commission, Government of India estimates.

POVERTY ANALYSIS

Data and Information on Poverty, in India is quite easily available as there

are various Governmental and Non- Governmental agencies (to be more

specific NSSO, through its various rounds of surveys provides ample amount

of Data on Poverty, so is Planning Commission) regularly conduct surveys

and research on Poverty in India. There are various approaches used for

estimating Poverty in India, to name a few Tendulkar Methodology and

Lakadwala Methodology is usually followed by planning Commission. An

expert Group was also constituted by Planning Commission in the year

1989, which has submitted its findings and estimation on number and

proportion of Poor in 1993, since then these methods are used for Poverty

analysis. Under the current study the table# on State wise percentage

growth and reduction in poverty level are presented, under the aegis of

select year 1983-84, 1993-94, 2004-05 and 2009-10, of which we will discuss

in detail in the upcoming parenthesis.

Table.7.23 Percentage of Poor in Select States during Four Cross Sectional Years

Source: Planning Commission Data, Govt. of India

*HCR: Head Count Ratio as a measure of Poverty

STATES HCR1983-84 HCR1993-94 HCR2004-05 HCR2009-10

ANDHRA PRADESH 29.0 22.2 29.6 21.1

ASSAM 41.0 40.9 34.4 37.9

BIHAR 62.1 55.0 54.4 53.5

GUJRAT 32.8 24.21 31.6 23.0

HARYANA 21.4 25.1 24.1 20.1

J&K 24.3 25.2 13.1 9.4

KARNATAKA 38.3 33.2 33.3 23.6

KERALA 40.5 25.4 19.6 12.0

MADHYA PRADESH 44.0 42.5 48.6 36.7

MAHARASTRA 43.5 36.9 38.2 24.5

ORISSA 65.3 48.6 57.2 37.0

PUNJAB 18.2 11.8 20.9 15.9

RAJASTHAN 34.5 27.4 34.4 24.8

TAMIL NADU 51.7 35.1 29.4 17.1

UTTAR PRADESH 47.1 40.9 40.9 37.7

WESTBENGAL 54.9 35.7 34.2 26.7

231

Keeping in view the cross sectional Years; 1983-84, 1993-94, 2004-05 & 2009-

10, the above Table7.23 suggests that, in case of Andhra Pradesh amid

1983-84 (as Pre-reform period) HCR (Head count Ratio as a measure of

Poverty) was more than 29 per cent, which slumped to 22.2 per cent in

1993-94 (Post-reform) , but this downturn pace of HCR has again shown a

skyward increase of up to 29.6 per cent (2004-05); which further settled

down to 21.1 per cent in the year 2009-10. Thus it could be witnessed from

the Table itself that the Poverty as measured by HCR is not following any

specific pattern; rather it looks like peaks & valleys under four specified

years.

This vivacity in HCR, are not alone for Andhra Pradesh, other States like

GUJRAT, HARYANA, MADHYA PRADESH, ODISHA, PUNJAB, RAJASTHAN,

witnessed the same heave behavior of HCR. It could be seen that among

all the Select States percentage of poor in BIHAR in 2009-10 is almost 54 per

cent, which were 62 per cent in 1983-84, which further reflect that in the

past 27 year there were reductions of 8 percent in HCR; again which put

forwards the fact that BIHAR still accommodates almost 54 per cent of poor

people. WEST BENGAL has succeeded up to a certain extent in reducing

the percentage of Poor, which was 54.9 per cent in 1983-8 and after 26

years it downslide to 26.7 per cent in 2009-10. Similarly another State

ODISHA which borne the burden of more than 65 per cent of Poor amid

1983-84, has successfully brought down this percentage to 37 per cent in

2009-10, again J&K has a HCR of 24.3 per cent in 1983-84, which came

down to 9.4 per cent in 2009-10. This exhibits an encouraging scenario as

far as percentages are concerned.

The Head Count Ratio in ASSAM in 2004-05 were 34.4 per cent, which were

41.0 per cent and 40.9 per cent during 1983-84 and 1993-94 respectively,

has in the recent years of 2009-10 augmented to 37.9 per cent, which is

quite on the higher side when we compare it with 20004-05. Again, some

232

States like TAMIL NADU and KERALA have shown the most encouraging

scenario, as Poverty percentages; firstly, in TAMIL NADU significantly

improved to 17.1 per cent in 2009-10 from 51.7 per cent during 1983-84.

Secondly in KERALA the same percentage came down to 12 per cent

(2009-10) from 40.5 per cent (1983-84). ASSAM, BIHAR, MADHYA PRADESH &

UTTAR PRADESH after 27 years of time duration still require some diligent

efforts, while executing Poverty reduction policies and plans. Thus, the

comprehensive analysis of the above HCR estimates of 16 states of India

brings forth the fact that although HCR shows a declining trend in almost all

the States except few, even then the rate of decline of HCR percentages

are not so impressive in case of aforesaid States, which further suggests

there is still a long way to go.

STATISTICAL INTERPRETATION: REGRESSION ANALYSIS

This part of the section analyses the outcome of Regression Analysis for the

year 1983-84, 1993-94, 2004-05 and 2009-10. Under the select year1983-84,

the Coefficient of Determination (R2) is higher and significant for INFMORT,

GRTPOP, PWPOP, SXRAT, and LIFEX & PLBSS, which again creating a catch-

22 situation as GRTPOP seems quite helpful in reducing Poverty as its R2

displays negative association with HCR (dependent variable) where as

INFMORT is augmenting Poverty as the coefficient of determination is 28.9

per cent. LIFEX is also displaying a dominant role in Poverty reduction with

significant R2 (17.2 %) and negative regression Coefficient, similarly PLBSS

and PLBTS proved to be significant at 10 per cent level with negative T-

Values (test statistic with student distribution). Hence the above analysis

displays the significant and specified variables whose dominance could

not be ignored while assessing poverty scenario.

233

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Amid 1993-94, LIFEX proved to be highly significant at 5 per cent level, with

43.3 per cent of R2 and negative coefficient; which suggests that there is

negative association between Poverty and LIFEX. Similarly, LTNPCSDP,

Table 7.24 Poverty Determinants in India

Regression Results (1983-84)

CONSTANT REG. COEFF R2 F

(T-VALUE) (T-VALUE)

GINI 55.16* -49.38* 1.9 0.27

(-1.95) (-0.52)

LTNPCSDP 39.19 3.82** 0.4 0.06

(-5.9) (0.24)

PURPOP 53.705* -0.585 10.8 1.7

(5.05) (-1.38)

LITRAT 36.9 0.0855 0.6 0.08

(2.82) (0.29)

LIFEX 114.5* -1.21** 17.2 2.9

(2.63) (-1.7)

INFMORT 16.2 0.34 28.9** 5.7

(1.53) (2.39)

GRTPOP 90.2 -22.27 28.3** 5.52

(4.22) (2.35)

PWPOP 29 1.77** 21.9** 3.64

(4.22) (1.91)

DENPOP 34.2 0.022 7.6 1.15

(4.99) (1.07)

SXRAT 81.1* 0.13 17.7 3.01

(-1.16) (1.73)

PLBPS 8.9 0.48 11.1 1.62

(0.36) (1.27)

PLBSS 50* -1.34 7.6 1.07

(5.65) (-1.3)

PLBTS 48.7 -0.43 3.5 0.5

(4.05) (-0.71)

PVAPS 37.8 0.48 1.2 0.16

(4.88) (0.41)

PVASS 38 0.45 3.2 0.46

(7.37) (0.68)

PVATS 49.1* -0.27 1.1 0.15

(2.22) (-0.39)

234

PURPOP, LITRAT and PLBSS are also significant and inversely related with

HCR, which further exhibits the fact that these variables are considerably

helpful in Poverty reduction. PLBPS, PWPOP and INFMORT are significant

only at 10 per cent level with high and positive Coefficient of

Determination, in other words this means, the above 3 variables in some

way or the other augmenting Poverty.

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Table 7.25 Poverty Determinants in India

Regression Results (1993-94)

CONSTANT REG. COEFF R2 F

(T-VALUE) (T-VALUE)

GINI 46.5* -46.2** 1.2 0.17

(1.42) (-0.41)

LTNPCSDP 48.4* -27.36* 32.3* 6.68

(7.6) (-2.58)

PURPOP 51.8* -0.74 30.8* 6.23

(6.6) (-2.5)

LITRAT 50.3* -0.29 10 1.55

(3.59) (-1.75)

LIFEX 132* -1.58 43.3* 10.71

(4.36) (-3.27)

INFMORT 18.4 0.23 15.6* 2.59

(1.94) (1.61)

GRTPOP 31 1 0.1 0.02

(1.79) (0.12)

PWPOP 25.7 1.21 18.2* 3.12

(5.24) (1.77)

DENPOP 30.8 0 1.5 0.22

(5.45) (0.47)

SXRAT 27.6 0 0.1 0.01

(0.45) (0.09)

PLBPS 17.1 0.29 30.1* 5.56

(2.42) (2.36)

PLBTS 48.1* -0.72 17.4* 2.96

(5.3) (-1.72)

PVAPS 32.2 0.15 0.2 0.03

(5.41) (0.17)

PVASS 32.1 -0.32 0.7 0.1

(7.39) (.31)

PVATS 44.8* -0.32* 2.4 0.35

(2.24) (-0.59)

235

Considering the Regression outcome for the year 2004-05, LIFEX bears the

dominant Coefficient of Determination of 55.1 per cent and F- test as a

measure of Statistical Significance of the regression equation as a whole is

also significant, further with negative T-value (-4.15) suggests a vital

association with HCR. Accordingly, PLBPS, LITRAT and INFMORT are

significantly measuring and displaying their per cent variance; 29.1 %, 27.5

% and 27.5 % respectively. Other variables like PLBTS, LTNPCSDP, PUPOP,

PLBSS and PVATS & Gini negatively but significantly explaining their

association with HCR with negative test of Student Distribution.

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Table7 .26 Poverty Determinants in India

Regression Results (2004-05)

CONSTANT REG. COEFF R

2 F

(T-VALUE) (T-VALUE)

GINI 61.6* -87.75* 8.1 1.23

(2.45) (-1.11)

LTNPCSDP 48.7* -19.47* 19.6* 3.41

(5.78) (-1.85)

PURPOP 48.8* -0.54 19* 3.29

(5.65) (-1.81)

LIRAT 86* -0.79 0 5.31

(3.78) (-2.3)

LIFEX 171 -2.13 55.1* 17.2

(5.17) (-4.15)

INFMORT 13.8 0.37 27.5* 5.31

(1.51) (2.3)

GRTPOP 27.2 3.61 2.5 0.36

(2.34) (0.6)

PWPOP 26.1 1.37 16** 2.66

(4.63) (1.63)

DENPOP 32.5 0 0.5 0.07

(5.16) (0.27)

SXRAT 33 0 0 0

(0.52) (0.02)

PLBPS 2.89 0.53 29.1* 5.75

(0.22) (2.4)

PLBSS 47.6* -1.19 17.3** 2.93

(5.63) (-1.71)

PLBTS 52.7 -0.77 20.8* 3.68

(5.2) (-1.92)

PVAPS 29.9* 0.7 3.8** 0.55

(4.7) (0.74)

PVASS 33.9* 0.02 0 0

(7.37) (0.04)

PVATS 68** -82* 16.3** 2.74

(3.28) (-1.65)

236

Finally, comprehension of the results of the Regression Analysis for the year

2009-10, exhibits that, in this year PURPOP, LITRAT, LIFEX, PLBSS & PLBTS are

negatively but significantly denting HCR, as their measure of association

(R2) representing per cent variance of 58.2 %, 27.5 %, 34.9 %, 28.9 % & 30.9 %

respectively.

Table 7.27 Poverty Determinants in India

Regression Results (2009-10)

CONSTANT REG. COEFF R

2 F

(T-VALUE) (T-VALUE)

GINI -4 125* 19* 3.29

(-0.24) (1.81)

LTNPCSDP 32* -4.75* 0.1 0.02

(0.72) (-0.13)

PURPOP 50.1* -0.75 58.2* 19.49

(8.75) (-4.41)

LITRAT 87.9* -0.82 27.5* 5.32

(3.28) (-2.31)

LIFEX 169* -2.12 34.9* 7.5

(3.24) (-2.74)

INFMORT 6.09 0.42 40.3* 9.44

(0.87) (3.07)

GRTPOP 1.87 15.86 32.4* 6.72

(0.19) (2.59)

PWPOP 20.3** 1.03 10.2* 1.59

(3.68) (1.26)

DENPOP 20.2 0.01 9.7 1.5

(3.55) (1.23)

SXRAT 60.97 -0.3 2.8 0.4

(1.11) (-0.63)

PLBPS 15.5 0.79 43.9* 10.94

(-1.21) (3.31)

PLBSS 41.5 -1.45 28.9* 5.69

(6.05) (-2.39)

PLBTS 53 -1.06 30.9* 6.26

(4.48) (-2.5)

PVAPS 22.2 0.76 4.4 0.64

(3.79) (0.8)

PVASS 28.4* -0.38 3.5 0.5

(6.86) (-0.71)

PVATS 36.2* -0.2 1.45 0.21

(1.65) (-0.45)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

237

MULTIPLE REGRESSION ANALYSIS: HCR & ASSOCIATED VARIABLES

Write-up for the Year 1983-84

The Multiple Regression output for the year 1983-84, exhibits that the

estimated intercept (HCR) is 18.32 and the slope for this constant is 0.32. The

t-statistic for INFMORT is 1.99 and its P-value is 0.069, the estimated S, which

is equivalent to the root square of Mean Standard Error, is 12.6, again the

coefficient of determination is 24.91 per cent and the adjusted value of

Coefficient of Determination is 18.65 per cent.

Similarly the output of second step of the analysis, the value of constant

making negative associations (-69.70) with predicted variable and the

slope of the INFMORT is 0.88. The values of T-statistic for testing with 4.79 and

its P-value is equal to 0.001and the T-statistic for βLITRAT=0 is 3.80 and its P-

value is 0.003 which is greater than benchmark i.e. 0.001. Further the t-

statistic for the estimated S, which root-square of MSE (Mean Standard

Error)is 8.68 and the R2 is 67.58 per cent and the adjusted R2 is 61.58 per

cent.

The third step of the analysis exhibits, the value of constant (HCR) showing

negative associations (-154.29) with the predicted variables and the

estimated slope βINFMORT = 0.82 and the estimated slope for βLITRAT = 0.86,

again the slope for βSXRAT = 0.106. The T-statistic significance for βINFMORT = 0 is,

4.91, for βLITRAT = 0 is, 2.93 and for βSXRAT = 0 is, 1.90, further the p-values for t-

statistic significance of βINFMORT, βLITRAT & βSXRAT ARE 0.001, 0.015 & 0.087

respectively.

Finally, the fourth step of the analysis suggests that, another predictor

PWPOP has been added, reaching the number of predictors in the final

model to four, here the estimates of constant to -152.4, the estimated slope

of bINFMORT = 0.77, the estimated slope for bLITRAT = 0.85, again the estimated

slope for bSXRAT = 0.102 and lastly the estimated slope of bPWPOP = 0.80

The t- statistic for testing βINFMORT = 0 is 4.63, where as its p-value is = 0.001,

similarly t-statistics for testing βLITRAT = 0, βSXRAT = 0 & βPWPOP = 0 are 2.99,1.89 &

238

1.30 respectively. The estimated S, which is equal to the root square of

mean standard error, is 7.55 and the coefficient of determination is 79.89

per cent.

On an overall basis the above analysis suggests that, the above

variables (INFMORT, LITRAT, and SXRAT & PWPOP) affect Poverty

significantly either positively or negatively during the year 1983-84.

Table7.28 Poverty Determinants in India

Multiple Regression Results (1983-84)

CONTANT

INFMORT

LITRAT

SXRAT

PWPOP

R2

(T-VALUE

(T-VALUE) (T-VALUE) (T-VALUE)

18.32**

0.32

-

-

-

24.91**

(1.99)

-

-

-

-69.7*

0.88**

1.11*

-

-

67.58*

(4.79)

(3.8)

-

-

-154.29*

0.82**

0.86**

0.106**

-

76.15*

(4.91)

(2.93)

(1.9)

-

-152.2*

0.77**

0.85**

0.102**

0.8**

79.89*

(4.63)

(2.99)

(1.89)

(1.3)

Write-up for the Year 1993-94

As in this case the analysis has been stretched into ten steps, instead of

explaining each step, here interpretation has been done on the basis of

final model extracted by the Multiple Regression Approach.

The model brings forward 10 predictors, similarly the estimate for the

intercept is bHCR = 393.4, and the estimated slope bLIFEX = -3.74, again the t-

statistic for testing βLIFEX = 0 is -31.84 where as its p-value is <.001 which

means that the predictor LIFEX is significantly helpful in reducing Poverty.

The estimated slope for bINFMORT = -0.950and its t-statistic for test βINFMORT = 0 is

-19.74 with p-value of <.001 Similarly the estimated slope for bLTNPCSDP,

bPWPOP, bPURPOP, bDENPOP, bPVASS and bGRTPOP, bPLBSS & bSXRAT are equal to -11.7,

0.44, -0.831, -0.0067, 0.763, and -6.40, -0.76 & -0.0275 respectively. The

estimated square root for MSE for this model is 0.656 and the estimated R2 is

99.90 per cent along with adjusted R2 of 99.66 per cent, which suggest that

239

the variables entered as predictors depicts great significance and

association with the intercept (HCR).

Table. 7.29 Poverty Determinants in India

Multiple Regression Results (1993-94)

CONSTANT LIFEX INFMORT LTNPCSDP PWPOP PURPOP DENPOP PVASS GRTPOP PLBSS SXRAT R2

(T-

VALUE)

(T-

VALUE) (T-VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE) (T-VALUE) (T-VALUE)

133.7 -1.61 - - - - - - - - - 41.37

-3.03 - - - - - - - - -

333.9 -4.15 -0.66 - - - - - - - - 63.56

-4.01 -2.7 - - - - - - - -

365.3 -4.24 -0.85 -25 - - - - - - - 82.59

-5.66 -4.6 -3.47 - - - - - - -

313.5 -3.53 -0.79 -29.5 0.92 - - - - - - 89.82

-5.38 -5.22 -4.89 2.67 - - - - - -

324.5 -3.56 -0.83 -18.7 0.97 -0.5 - - - - - 94.21

-6.83 -6.87 -2.94 3.52 -2.61 - - - - -

361.8 -3.76 -1.05 -20.6 1.28 -0.75 -0.015 - - - - 97.3

-9.81 -9.23 -4.45 5.71 -4.64 -3.03 - - - -

352 -3.61 -0.999 -17.1 0.81 -1.01 -0.013 0.53 - - - 98.71

-12.49 -11.39 -4.69 3.43 -6.64 -3.43 2.76 - - -

350.5 -3.53 -0.948 -18.8 0.8 -0.99 -0.014 0.55 -2.8 - - 99.24

-14.5 -12.61 -5.87 4.1 -7.85 -4.4 3.44 -2.04 - -

345.9 -3.59 -0.861 -12.8 0.34 -0.75 -0.003 0.8 -4.2 -0.73 - 99.65

-19.76 -13.02 -4.15 1.41 -5.58 -0.6 5.12 -3.59 -2.44 -

393.4 -3.74 -0.95 -11.7 0.44 -0.831 -0.006 0.76 -6.4 -0.76 -0.067 99.9

-31.84 -19.74 -6.29 3.04 -9.93 -2.09 8.24 -6.56 -4.33 -3.2

Write-up for the Year 2004-05

In this year the analysis extracted two predictors in its final model; the

standard deviation for the estimated intercept HCR is 171.0 in the first step

and 297.2 in second and final step, again the standard deviation for the

estimated slope bLIFEX = -3.72 and the tstatistic for testing BLIFEX = 0 is -1.72

along with the p-value of 0.108. The standard deviation of the estimated

slope bINFMORT = -0.44 and its t-statistic for testing BINFMORT = 0 is -1.72 with p-

value of 0.108. Similarly, the square root of MSE in final step is 7.85 with

estimated R2 of 63.49 per cent and adjusted R2 of 57.87 per cent. Hence in

the year 2004-05 the analysis suggest that there are two predictors which

exhibit their association with HCR upto a certain level of significance.

240

Table7.30 Poverty Determinants in India

Multiple Regression Results (2004-05)

CONTANT

LIFEX

INFMORT R2

(T-VALUE

(T-VALUE)

171.0**

-2.13*

- 55.13**

(4.15)

-

297.2*

-3.72*

-0.44* 63.49*

(-3.58)

(1.72)

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Write-up for the Year 2009-10

The outcome of the analysis exhibits; the standard deviation of the

estimated intercept (HCR) is -247.2 and the square root of standard error

mean is 1.53 with 99.41 per cent of R2 along with adjusted R-square of 98.23

per cent .

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

Table. 7.31 Poverty Determinants in India

Multiple Regression Results (2009-10)

PURPOP GINI PVASS DENPOP SXRAT INFMORT LIFEX PVATS PLBSS GRTPOP R2

CONSTANT

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE)

(T-

VALUE) (T-VALUE)

(T-

VALUE) (T-VALUE)

50.09 -0.75 - - - - - - - - - 58.2

-4.41 - - - - - - - - -

22.98 -0.72 109 - - - - - - - - 72.39

-5.01 2.58 - - - - - - - -

27.73 -0.95 101 0.78 - - - - - - - 81.38

-6.14 2.78 2.41 - - - - - - -

22.79 -0.98 95 0.94 0.12 - - - - - - 91.75

-9.09 3.78 4.11 3.72 - - - - - -

-663 -1.07 89 1.07 0.12 0.036 - - - - - 93.68

-9.54 3.78 4.81 3.84 1.75 - - - - -

-30.79 -0.78 86 0.95 0.016 0.039 0.22 - - - - 95.73

-4.56 4.23 4.67 4.79 2.23 2.08 - - - -

-142 -0.87 111 0.98 0.013 0.044 0.401 1.43 - - - 97.45

-5.98 5.6 5.87 4.59 2.98 3.44 2.32 - - -

-186.9 -0.86 108 0.97 0.012 0.035 0.543 1.92 0.3 - - 98.8

-8.08 7.43 7.95 5.27 3.12 5.47 3.97 2.81 - -

-234.2 -1.03 116 1.01 0.008 0.038 0.621 2.45 0.43 0.41 - 99.15

-7.1 8.12 8.86 2.42 3.64 6 4.41 3.37 1.56 -

-247.2 -1.11 131 1.08 0.007 0.02 0.7 2.86 0.48 0.44 -3.7 99.41

-7.79 8.03 9.36 2.47 1.37 6.52 4.97 3.94 1.85 -1.49

241

*indicates significant at 5 per cent level **indicates significant at 10 per cent level

The above analysis explains that 10 variables; PURPOP, GINI, PVASS,

DENPOP, SXRAT, INFMORT, LIFEX, PVATS AND PLBSS & GRTPOP, are

significantly display their association with Poverty (HCR). These variables

exhibit clear cut impact on poverty either they are helpful in reducing

poverty or they play role of catalyst in its increase.

Head Count Ratio(HCR) AND ASSOCIATED VARIABLES:

CORRELATIONASSESSMENT

In order to ascertain the inter-correlation among Poverty and its associated

variables, a correlation analysis has been carried out for the cross sectional

years; 1983-84, 1993-94, 2004-05 & 2009-10.

During the year 1983-84, HCR exhibits positive and significant association

with INFMORT and GRTPOP, which suggests they are in some way or the

other increasing poverty. Other variables like INFMORT, DENPOP, PLBTS and

PVASS are inter- correlated with variables like LIFEX, GRTPOP, PURPOP and

PVAPS, again they exhibit their p-value < 0.001 which express their

significance level.

Table7.32 Correlation Analysis of Select Poverty Determinants 1983-84

GINI LTNPCSDP PURPOP LIFEX INFMORT GRTPOP DENPOP PLBTS PVAPS PVASS PVATS SXRAT PHCR

GINI 1 0.15 0.45 0.36 -0.38 -0.075 0.16 0.13 0.06 -0.003 0.35 0.4 -0.14 LTNPCSDP 1 0.4 0.04 0.22 -0.05 0.04 0.3 0.42 0.39 -0.18 -0.01 0.03 PURPOP

1 0.44 -0.49 0.32 0.2 0.55 0.4 0.7 0.5 0 -0.33

LIFEX

1 0.9 -0.2 0.51 0.62 -0.04 0.2 0.52 0.3 -0.41 INFMORT

1 -0.04 -0.3 -0.47 -0.11 -0.21 -0.6 -0.22 -0.54

GRTPOP

1 -0.57 -0.47 -0.03 -0.2 -0.21 -0.61 -0.54 DENPOP

1 0.51 0.14 -0.16 -0.34 0.31 0.28

PLBTS

1 0.41 0.49 0.64 0.12 -0.18 PVAPS

1 0.54 0.4 -0.15 0.12

PVASS

1 0.32 0.11 0.18 PVATS

1 0.22 -0.11

SXRAT

1 0.42 PHCR

1

242

Table7.33 Correlation Analysis of Select Poverty Determinants (1993-94)

GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT PHCR

GINI 1 0.58 0.64 0.22 0.46 -0.45 -0.31 0.49 0.22 -0.01 0.47 0.59 0.53 0.54 0.54 0.35 -0.11

LTNPCSDP 1 0.79 0.31 0.53 -0.56 -0.31 0.11 0.02 -0.24 0.72 0.49 0.36 0.43 0.23 0.38 -0.58

PURPOP

1 0.31 0.54 -0.52 -0.19 0.14 -0.05 -0.34 0.77 0.61 0.35 0.65 0.35 0.18 -0.55

LITRAT

1 0.7 -0.85 -0.55 -0.41 0.39 -0.71 0.47 0.64 -0.26 0.01 0.54 0.49 -0.31

LIFEX

1 -0.88 -0.44 -0.3 0.39 -0.65 0.55 0.68 -0.06 0.06 0.57 0.39 -0.65

INFMORT

1 0.58 0.25 -0.53 0.54 -0.64 -0.72 0.07 -0.14 -0.61 -0.55 0.39

GRTPOP

1 0.07 -0.49 0.08 -0.49 -0.47 0.12 -0.02 -0.18 0.73 0.03

PWPOP

1 0.1 0.56 0.03 -0.01 0.82 0.64 0.18 -0.01 0.42

DENPOP

1 0.01 0.41 0.45 0.12 -0.04 0.46 0.21 0.12

PLBPS

1 -0.17 -0.26 0.33 0.17 -0.36 -0.15 0.55

PLBSS

1 0.73 0.3 0.5 0.34 0.24 -0.44

PLBTS

1 0.24 0.35 0.6 0.24 -0.41

PVAPS

1 0.61 0.32 -0.15 0.04

PVASS

1 0.22 0.04 0.08

PVATS

1 0.37 -0.15

SXRAT

1 0.02

PHCR

1

243

For the year 1993-94, correlation output depicts that HCR has strong

interdependence with PLBPS as their r = 0.5474 and their p- value < .0347 is

also significant. Similarly, HCR also exhibits significant correlation with

LTNPCSDP, PURPOP & LIFEX with significant p- values. Apart from HCR other

variables like GRTPOP, PWPOP, DENPOP, and PLBSS & PVATS are also

mutually associated with each other significantly (p- value < 0.001).

In the year 2004-05, Poverty is significantly correlated with INFMORT with

strong r- value (0.5245) and its significant p- value <.001. Accordingly other

variables are also displaying their significant and strong correlation with

each other, which could be witnessed from the table itself.

Table 7.34 Correlation Analysis of Select Poverty Determinants (2004-05)

GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT PHCR

GINI 1 0.54 0.5 0.3 0.56 -0.6 -0.41 0.22 0.36 -0.76 0.63 0.73 0.37 0.24 0.5 0.27 -0.28

LTNPCSDP - 1 0.84 0.37 0.51 -0.47 -0.36 0.18 -0.25 -0.56 0.7 0.45 0.25 0.63 0.27 0.25 -0.44

PURPOP - - 1 0.31 0.52 -0.56 -0.28 0.18 -0.16 -0.66 0.8 0.55 0.24 0.73 0.33 0.03 -0.44

LITRAT - - - 1 0.61 -0.67 -0.47 -0.4 0.11 -0.5 0.33 0.54 -0.37 0.01 0.41 0.4 -0.52

LIFEX - - - - 1 -0.88 -0.4 -0.28 0.26 -0.77 -0.66 -0.75 0 -0.29 -0.7 -0.5 0.52

INFMORT - - - - - 1 0.58 0.08 -0.45 0.77 -0.67 -0.75 0 -0.29 -0.7 -0.5 0.52

GRTPOP - - - - - - 1 0.05 -0.18 0.56 -0.46 -0.57 0.06 -0.05 -0.47 -0.8 0.15

PWPOP - - - - - - -

1 0.19 0.04 0.19 -0.04 0.9 0.53 0.15 0 0.4

DENPOP - - - - - - - - 1 0.19 0.04 0.19 -0.04 0.9 0.53 0.15 0

PLBPS - - - - - - - - - 1 -0.84 -0.94 -0.18 -0.22 -0.58 -0.2 0.53

PLBSS - - - - - - - - - - 1 0.67 0.33 0.47 0.38 0.13 -0.41

PLBTS - - - - - - - - - - - 1 0.18 0.26 0.67 0.2 -0.45

PVAPS - - - - - - - - - - - - 1 0.5 0.21 -0.16 0.19

PVASS - - - - - - - - - - - - - 1 0.09 -0.03 0.01

PVATS - - - - - - - - - - - - - - 1 0.45 1

SXRAT - - - - - - - - -- - - - - - - 1 0

PHCR - - - - - - - - - - - - - - - - 1

For the select year 2009-10, Poverty shows an inverse relation with PLBTS

with significant p-value of 0.0254. Similarly other variables are also mutually

inter dependent on each other.

Hence, the overall correlation analysis for the specified four years suggests

that HCR has continuous bonding either positive or negative with other

244

variables; similarly other variables are also mutually related with each other

creating a problem of multi- colliniarity, which would be dealt in further

part.

245

Table 7.35 Correlation Analysis of Select Poverty Determinants (2009-10)

2010 GINI LTNPCSDP PURPOP LITRAT LIFEX INFMORT GRTPOP PWPOP DENPOP PLBPS PLBSS PLBTS PVAPS PVASS PVATS SXRAT PHCR

GINI 1 -0.06 -0.07 -0.22 -0.28 0.08 0.23 0.33 0.04 0.4 -0.16 -0.48 0.2 0.02 0.2 0.08 0.43

LTNPCSDP - 1 0.3 0.14 0.27 -0.24 0.24 0.3 0.47 -0.33 0.47 0.3 0.3 0.34 0.27 -0.33 -0.03

PURPOP - - 1 0.74 0.74 -0.79 -0.54 0.66 -0.04 -0.74 0.72 0.65 0.1 0.59 0.39 0.33 -0.76

LITRAT - - - 1 0.73 -0.7 -0.69 -0.14 0.18 -0.7 0.56 0.83 -0.07 0.35 0.35 0.54 -0.52

LIFEX - - - - 1 -0.91 -0.47 -0.13 0.37 -0.84 0.62 0.79 -0.11 0.25 0.42 0.32 -0.59

INFMORT - - - - - 1 0.58 0.01 -0.33 0.76 -0.66 -0.73 0.04 -0.28 -0.61 -0.41 0.63

GRTPOP - - - - - - 1 0.16 -0.04 0.6 -0.39 -0.68 0.09 0.02 -0.4 -0.76 0.56

PWPOP - - - - - - - 1 0.22 0.12 0.06 -0.21 0.92 0.46 0.21 -0.01 0.31

DENPOP - - - - - - - - 1 -0.3 0.33 0.36 0.19 -0.17 0.38 0.14 0.31

PLBPS - - - - - - - - - 1 -0.73 -0.77 0.08 -0.14 0.34 -0.43 0.66

PLBSS - - - - - - - - - - 1 0.58 0.16 0.37 0.12 0.14 -0.53

PLBTS - - - - - - - - - - - 1 -0.13 0.2 0.49 0.43 -0.55

PVAPS - - - - - - - - - - - - 1 0.42 0.07 -0.15 0.2

PVASS - - - - - - - - - - - - - 1 0.07 -0.06 -0.18

PVATS - - - - - - - - - - - - - - 1 0.48 -0.12

SXRAT - - - - - - - - - - - - - - - 1 0.16

PHCR - - - - - - - - - - - - - - - - 1

246

REDRESSING MULTI-COLLINEARITY: FACTOR ANALYSIS APPROACH

In this part in of the analysis, an effort has been made to redress the issue of

Multi-collinearity, though Factor analysis approach; Factor analysis exerts

upon determining the latent variables that exhibits the correlation pattern

within a set of select variables. Further it helps in identifying a few numbers

of factors, which are capable of explaining overall variance. Variables are

selected on the basis of regression analysis outcome for factor analysis. The

outcomes of the Rotated Factor Analysis have been discussed below in

coherence of the select years.

ROTATED FACTOR ANALYSIS

Write-up for the year 1983-84:

During the year 1983-84, the Rotated Factor Analysis Technique with

Orthogonal Varimax Model, extracted 3 Factors, the variance explained by

the Factor I is 29.139 per cent. Similarly, the second Factor and third Factor

explain the cumulative variance of 56.159 % & 76.383 % respectively. The

final communality estimates of the variables included are rather low with

SXRAT (.40) which suggests that this variable is weakly related with its Factor.

However the overall communality estimate exhibits that, the set of variables

are least adequately related for factor analysis. The 3 extracted factors,

substantively confers, that the model has diagnosed three clear cut

patterns of response among the latent variables and these factors are

independent of each other.

The Rotated Factor Loadings brings forward loading of three factors which

has been extracted one after another, the factor 1, exhibits that PLBPS,

INFMORT and PWPOP have positive and high Variations, similarly PLBSS,

PLBTS, DENPOP and LIFEX have inverse variations. The values of items

depicts their weight and correlation with the Factors, which could be

understood as; the loadings for factor 1 suggests that the ‗values‘ of items

such as PLBPS (0.835634) is the ‗weight‘ of correlation between PLBPS and

Factor one. Moving on to the next Factor; the factor 2 yielded two

247

negative and weak weighted items, which depicted low variance with

negative effects. PVASS, PURPOP, PLBSS, PLBTS and LIFEX exhibit positive

effects, among these five items, two items (PLBTS & LIFEX) are showing weak

association and low variations, similarly three items (PVASS, PURPOP &

PLBSS) display strong correlation (as the weights are significant) with their

respective factor (Factor 2).The Third Extracted Factor depicts that there

are two items i.e. PLBPS which is negatively and wealy associated and

GRTPOP is negatively related but exhibits a strong variance with the Factor

3. The other items brought forth by the third factor are PLBTS, DENPOP,

SXRAT & LIFEX are positively related, out of which possess significant weight

with factor 3.

Overall, the analysis suggests that the PLBPS, PLBTS and LIFEX have

shown variations, which are sometimes negatively weak or positively strong

and vice- versa, again they represent the fact that these items play a

dominant role either in reducing or augmenting Poverty.

248

Table7.36 Factor Analysis on Correlations with 3 Factors: Varimax

(1983-84)

Final Communality Estimates PURPOP 0.83049

LIFEX 0.90548

INFMORT 0.78750

GRTPOP 0.78605

PWPOP 0.68647

DENPOP 0.66119

PLBPS 0.95779

PLBSS 0.91574

PLBTS 0.65082

PVASS 0.81073

SXRAT 0.40985

Variance Explained by Each Factor Factor Variance Percent Cum

Percent

Factor

1

3.2053 29.139 29.139

Factor

2

2.9722 27.020 56.159

Factor

3

2.2246 20.223 76.383

Rotated Factor Loading Factor 1 Factor 2 Factor 3

PLBPS 0.835634 -

0.381574

-

0.337507

INFMORT 0.818425 -

0.335988

-

0.069219

PWPOP 0.752704 0.295766 0.180081

PVASS 0.153429 0.877619 0.130284

PURPOP -

0.270098

0.860365 -

0.131554

PLBSS -

0.486748

0.801941 0.188969

PLBTS -

0.327779

0.597114 0.432242

GRTPOP -

0.123632

-

0.089117

-

0.873395

DENPOP -

0.309086

0.131381 0.740535

SXRAT -

0.085508

0.001853 0.634455

LIFEX -

0.843593

0.301594 0.320738

249

Table7.37Factor Analysis on Correlations with 3 Factors: Varimax (1993-

94)

Rotation Matrix 0.66395 0.64014 -

0.38651

0.56597 -

0.09236

0.81924

-

0.48873

0.76268 0.42362

Final Communality Estimates LTNPCSDP 0.72761

PURPOP 0.78739

LITRAT 0.87402

LIFEX 0.79462

INFMORT 0.90021

PWPOP 0.67199

PLBPS 0.72422

PLBSS 0.78703

PLBTS 0.73572

PVATS 0.70176

Variance Explained by Each Factor Factor Variance Percent Cum

Percent

Factor

1

3.0381 30.381 30.381

Factor

2

2.5930 25.930 56.311

Factor

3

2.0735 20.735 77.046

Rotated Factor Loading Factor 1 Factor 2 Factor 3

PURPOP 0.859482 0.220600 0.004175

LTNPCSDP 0.841764 0.128368 -

0.050650

PLBSS 0.832961 0.303106 -

0.036492

PVATS 0.151605 0.823644 0.019778

LITRAT 0.239400 0.658700 -

0.618727

PLBTS 0.562906 0.641563 -

0.085141

LIFEX 0.481696 0.594010 -

0.457977

PWPOP 0.095201 0.094244 0.808730

PLBPS -

0.095690

-

0.293600

0.793009

INFMORT -

0.499632

-

0.681282

0.431774

250

Write-up for the year 1993-94:

Analysis for the year 1993-94, depicts that the Eigen Values, which has

extracted three factors, of which the factor 1 represents 54.053 per cent of

total information, similarly total information provided by the factor 2 and 3

are 73.595 & 10.257 per cent respectively.The Scree Plot of the analysis

displays, three factors which are drawn pre-dominantly to the very left at

vertical line, which is relatively the graphical representation of Eigen Value

extraction. The variance explained by factor 1 is 30.381 percent, while

factor to explains individual and cumulative variance of 25.930 & 56.351

per cent respectively. Finally the factor 3 accounts for 20.735 per cent of

individual and 77.046 per cent of cumulative variance. The outcome of

Rotated Factor Analysis exhibits; the correlation and weight of the items

within each factor. The factor 1 has six items (LTNPCSDP, PLBSS, PLBTS, LIFEX

& INFMORT), out of which INFMORT expresses inverse variation. The other

extracted items of factor 1 are strongly and positively correlated with the

factors, which suggest they significantly play a role in augmenting Poverty.

The second factor brings forth INFMORT as negatively varied item with

significant load, PLBSS has positive but weak relation with the factor, and all

the other items are significantly and positively associated with the factor.

The third factor derived was as such due to PWPOP and PLBPS bears high

loading and depicts strong relation with its factor. LITRAT and LIFEX display

strong loadings but they are inversely related with the factor which further

suggests that they are quite helpful in reducing Poverty.

Write-up for the year 2004-05:

The final communality estimates, included are high, as all the underlying

variables explain proximity with the standard communality i.e. +1.

The variance explained by factor 1 cumulatively are 32.856 percent, and

by factor 2 & 3 are 59.47 & 77.245 per cent respectively.

The Rotated factor Loadings exhibit that factor 1 shows high loading for

PLBTS, PVATS, GINI, LIFEX and LITRAT & PLBSS, all these are positively loaded

251

with the factor 1. On the hand INFMORT and PLBPS are strong but inversely

loaded which suggest these two items of the factors are affecting poverty

inversely. Similarly, factor 2 yields that there are 3 weak items namely PHCR,

INFMORT and PLBPS which are depicting their weak and inverse correlation

with their factor, all the other 6 items are significantly loaded. LIFEX and

LITRAT in factor 3 displaying an inverse shift when compared with their

loading in previous two factors. Factor 3, exhibits that PWPOP, HCR, and

INFMORT bears positive loading but to be specific INFMORT is weakly

loaded, which further suggests its insignificant association factor 3.

7.38 Factor Analysis on Correlations with 3 Factors: Varimax Rotation Matrix

0.72134 0.60082 -0.34452

-0.00526 0.50218 0.86475

0.69257 -0.62196 0.36540

Final Communality Estimates GINI 0.65500

LTNPCSDP 0.79869

PURPOP 0.84291

LITRAT 0.60078

LIFEX 0.87423

INFMORT 0.85632

PWPOP 0.68580

PLBPS 0.90159

PLBSS 0.84760

PLBTS 0.87793

PVATS 0.64821

PHCR 0.68031

Variance Explained by Each Factor Factor Variance Percent Cum Percent

Factor 1 3.9427 32.856 32.856

Factor 2 3.1941 26.617 59.473

Factor 3 2.1326 17.771 77.245

Rotated Factor Loading Factor 1 Factor 2 Factor 3

PLBTS 0.855954 0.322350 -0.203375

PVATS 0.795363 0.091830 -0.084708

GINI 0.673757 0.443299 0.067340

LIFEX 0.603531 0.387763 -0.599685

LITRAT 0.414885 0.170985 -0.631989

PURPOP 0.272671 0.873013 -0.080042

LTNPCSDP 0.183281 0.867476 -0.112177

PLBSS 0.477010 0.786585 -0.036607

PWPOP 0.126535 0.234535 0.784083

PHCR -0.264325 -0.358883 0.694005

INFMORT -0.772715 -0.335885 0.382638

PLBPS -0.754125 -0.524975 0.239354

252

Write-up for the year 2009-10:

For the specified year 2009-10, thirteen variables have been selected on

the basis of Regression output. In order to assess their significance and

reduce the multi-collinearity obstacle, Rotated Factor analysis has been

carried out. The analysis extracted four factors, again the analysis also

depicts final communality estimates which are significantly high and

express their nearness to the standard estimate (+1). Here, the high

communality estimates suggest that the variable chosen for the analysis

strongly associated with their respective factors.The variance explained by

factor1 & 2 are 43.176 % & 57.927 % respectively, again the variance

explained by second and fourth factor are 69.279 % & 79.607 %

respectively. The term variance explanation refers to ‗per cent share of

total information provided‘ by each factor.

The Rotated factor loading for the factor 1 depicts high and positive

loading for LIFEX, PLBTS, PURPOP, and PLBSS & LITRAT where as LTNPCSDP &

PVASS has weak loading with the factor. INFMORT, PLBPS & GRTPOP has

negative and strong loading with its factor.

Factor 2 suggests that there are four items loaded out of which GRTPOP

and LTNPCSDP have positive and high load with their respective factor.

Similarly, factor 3 has also loaded four items (PURPOP, LTNPCSDP, PVASS &

PVAPS) that possess significant weight and positive relation. Factor 4

extracted 3 items, out of which INFMORT has negative association and

weak loading against the factor. Accordingly PVATS and SXRAT have

positive relation but low weight of SXRAT explains that its association with

the factor is weak.

253

Table 7.39 Factor Analysis on Correlations with 4 Factors: Varimax (2009-

10)

Final Communality Estimates GINI 0.71514

PURPOP 0.94887

LITRAT 0.78056

LIFEX 0.85522

INFMORT 0.82442

GRTPOP 0.84464

PWPOP 0.64868

DENPOP 0.93845

PLBPS 0.85337

PLBSS 0.68138

PLBTS 0.87179

PVASS 0.81229

SXRAT 0.78950

Variance Explained by Each Factor Factor Variance Percent Cum Percent

Factor 1 5.5311 42.547 42.547

Factor 2 2.0424 15.711 58.258

Factor 3 1.6831 12.947 71.205

Factor 4 1.3077 10.059 81.264

Rotated Factor Loading Factor 1 Factor 2 Factor 3 Factor 4

PURPOP 0.882640 0.231506 0.145792 -0.308168

LIFEX 0.871878 0.177984 -0.147523 0.203981

PLBSS 0.814392 0.000669 0.068069 0.116216

PLBTS 0.797623 0.323342 -0.324281 0.160869

LITRAT 0.750165 0.453803 -0.093901 -0.055308

PVASS 0.553842 -0.250852 0.472024 -0.468850

SXRAT 0.207644 0.858577 0.063885 0.071756

PWPOP 0.070416 -0.171291 0.780512 0.072012

GINI -0.332325 0.198918 0.749917 0.052465

PLBPS -0.834857 -0.261651 0.244734 -0.167424

GRTPOP -0.446176 -0.778060 0.194359 0.049130

INFMORT -0.833459 -0.322173 -0.050140 -0.153151

DENPOP 0.271583 -0.002676 0.150995 0.917543

Thus, on an overall basis we could easily acknowledge the fact

that variables like PLBPS, PLSS, PLBTS and LIFEX, which are also a mix of

Social and Structural factor, prove to be significant factors in determining

Poverty. Similarly all other variables vitally considerable, in overall analysis of

poverty or in wider terms determining Income Distribution.

After analyzing the income Distribution from Inequality and Poverty angle

suggestions and Recommendation are provided in next chapter.

254

To sum up, In order to ascertain as to what happens to the

inequalities with change in per capita state domestic product(PCSDP) in

relation to Gini with the help of polynomial functional forms for which linear,

quadratic and cubic forms were fitted . The results brought forward the fact

that there were no significant relation between Gini and PCSDP although

there exists a very weak sign of their being positive relation. As such

Kuznets‘ hypothesis relationship could not be traced in Indian economic

growth concept.

An analysis has been also carried out to analyze the extent and

determinants of poverty in select states of India, at the select four time

periods, the study explored that at national level poverty has fallen from as

high as 55.30 per cent in 1983-84 to 25.10 per cent which could be believed

as significant achievement for the goal of eradication of poverty. However,

a specific disturbing development over the time period 1983-84 to 2009-10

is the constant widening gap among states in terms of poverty eradication.

It was found that the coefficient of variation of Head Count Ratio in select

states have moved up from 22.10 per cent to 56 per cent in 2009-10, that

alarms for initiating certain policy measures for the to promote growth and

development activities, so that size of the cake could be enlarged and

higher per capita value addition could be encouraged in order to reduce

inequality and eradicate poverty.

255

Chapter VIII

Policy Actions for Equal Income Distribution

Economists have been working on the issue of equal distribution for a long

time with one term swaying the popular view in certain time periods; and

the other heading the list of priorities at some other times. Till seventies, the

economist were only concentrated towards the attainment of efficiency,

whereas the issue of equality were on the back side of the agenda. After

the collapse of the trickledown effect, the issue of equality came into the

scene as the prime concern. Consequently, a new breed of economic

thinkers aimed at meeting the basic individual requirements or ensuring

growth with the equality were proposed. Nevertheless, these basic

requirements and equality along with growth strategies were short-lived;

the ideological ascendancy of neo-liberalism in the leading developed

countries and policies of international financial institutions cause the

demise of equality with growth strategies.

By mid-80s, in the neo-ideological dispensation of stabilization and

structural adjustment, socio-economic policy was associated with fiscal

crisis of the state, which was treated as one more source of economic

instability and inflation. Moreover, the association of social development

with state intervention opened it to neo-liberal attack, which termed it as

one of the sources of economic failure. These arguments were

smoothened by the common critique of the welfare state, which is often

accused of inefficiency for (i) crowding out the more efficient private

sector; (ii) distorting labor markets by introducing all kind of restrictions; (iii)

blunting incentives for all types of unemployed workers to seek

employment. Due to neo liberal skepticism about social solidarity, social

expense were witnessed derailing from stabilization and it was thought that

these would have to be curtailed if fiscal deficits were to be checked

(Mkandawire, 2001). This shift in the policy led to curtail in social

256

investments, privatizations of social programmes and the abandonment of

social planning as an integral part of policy making. Thus, the pressures for

cutting public social expenses has been unrelenting, with the result that the

long run affects of such curtailment on growth have been lost sight of. And

if at all social expenditure has been justified, it has been as a remedial

measure, limited to safety webs for vulnerable groups, with no

consideration of the implications for future growth.

Nevertheless, there has been turn around in the economic thinking in the

recent times with equality again getting attention in the discourses about

growth. A United Nation Report (2008) attributes following reasons for this:

i) The rediscovery of poverty in national and international policy

discourses.

ii) The realization that it is not biologically given, but instead in a socially

constructed capacity or potential resulting from deliberate

investment in human capital or institutional arrangements, that

determines the participation of individuals from different social groups

in labor markets.

iii) The revival of interest in growth economics and the emergence of so-

called new growth theories that acknowledged that social growth

contain vital instruments for economic growth.

iv) An interest in social equality, both as an instrument for the promotion

of growth and as an end in itself.

v) An interest in social security, in light of the greater economic volatility

of economies in the context of free markets, globalization and

greater vulnerability of even larger societies.

vi) The historic learning of the significance of social policy in the late

industrializers.

Thus the above stated factors have led to the evolution of interest in social

policy for ensuring equality. The demand for equality ensuring policies have

257

also gathered momentum due to the underconsumptionist and political

instability models which highlight the need for equality in the growth

process.

Before moving to the policy actions for ensuring equal income distribution,

it would be wise to clearly understand the definition of equality. According

to Kuznets‘(1955) Equality refers to two things:

“The absence of systematic discrimination in rates of return for

economically similar goods and services: and (ii) the restraints of

inequalities in opportunities to members of the society for more productive

and greater yielding rates. If they have the required capacities….an

indispensable requirement of the modern economic growth, the basic

philosophy on which it rests and which it source of its great dynamism, is the

belief that equality of both political and economic opportunity is to be

extended to all groups within the society; consequently any differences in

opportunities realized should be based largely upon difference in human

capacity tested in action rather than on preconceived notions of

inequality” thus in easy words equality refers to fairness and justice, in the

manner in which the economy‘s output is distributed between individuals

which is exclusively expressed in terms of income or wealth. The most

important objective of the modern economic policy is to ensure maximum

welfare of its citizens and the key to it lies in ensuring equality which calls for

adopting certain policies which at the same time should not interrupt

growth.

Policies

In the year 1979 Ahluwalia suggested six broad areas for policy makers to

intervene for the pursuance of objective of achieving equality, which is

discussed below:

1. Factor markets, which determine factor prices, utilization levels and

factor incomes, giving us the basic functional distribution of income.

258

2. Ownership and control on physical capital and labor skills in the

population which translates the functional distribution of income into

size distribution of income. Changes in ownership pattern overtime are

an important element determining changes in the distribution of

income.

3. Taxation of personal income and wealth which operates on the size

distribution of income as a fiscal corrective on market determined

income.

4. Provision of public consumption goods, or direct income transfer by

state, which complements post tax income distribution pattern and

jointly determine the net fiscal impact on the size distribution of income.

5. Commodity markets, which are closely, associated with the equilibrium

in the factor markets. The commodity composition of final demand

obviously affects the pattern of demand for factors and hence factor

incomes.

Conversely, the income distribution directly determines commodity

demand through consumption patterns. These five components

constitute a closed loop describing the general equilibrium

determination of income in an economy.

To these, sixth component, which is crucial, although somewhat less

subject to government influence, can be added.

6. The state of the technology, which determines the level of total output

and the degree of substitutability between factors.

The policies aiming at achieving equal growth objective could affect

income distribution through several instrumental determinants that

could be economic, social, cultural, political and demographic in

nature. It would be worthy here to outline different policy implications

one on one.

Unequal distribution of wealth, asset, or income, in present times, has been

singled out as a significant determinant of inequality, the most vital asset

259

that comes in mind, is the immovable property i.e. land. Economists have

been zeroed in on the significance of land reforms as an instrument for

ensuring equality. Land reforms are desirable for reducing the

concentration of land holdings in the hands of richer classes. A study

conducted by Adelman and Geir (1969), however, reached at the

conclusion that land reforms are to be insignificant in improving relative

income distribution. They reached to this conclusion on the basis of the fact

that agricultural poor, after getting redistributed land, fail to maintain its

productivity due to scat resources at their disposal. Thus for land reforms to

be a successful policy for equality ensuring objective, supportive measures

should also be taken.

In several developing economies as agriculture is the main livelihood

mediunm and in these economies major proportion of population resides in

rural areas. Therefore, the incidence of poverty and inequality also lies

more in the agriculture sector, which points to the need for enhancing

productivity in the agriculture sector. For this, enhanced technology, hybrid

seeds, and improved quality fertilizers, etc are need to be utilized in agro

operations. To this end, ample support should be provided from the

government side. However, Adel man and Geir (1983) in their findings

brought forth the fact that such technology primarily benefit middle quintile

groups and top quintile farmers only. Whereas agricultural poor farmermers

were unable to receive any benefit from such development, to an extent

they become the first survivor of backwash effects. They start stressing upon

rural development policies rather than technological innovation. Rural

developments policies could take the form of starting rural public works

and setting up rural cooperatives. Rural public works could lead to

substantial enhancements in the real income of the poor, especially

landless poor‘s. Rural cooperatives, by making the crop, subsidizing the

agricultural inputs and providing low cost credit, could become effective

policy tool for poverty reduction.

260

In their other works Adelman, Morris and Robinson (1976), on the basis of

experience of forty three developing countries, underscored the

significance of agricultural terms of trade. The agricultural terms of trade

are particularly crucial to inequality reduction. The study found that an

increase in agricultural terms of trade raises the income of the small farmers

and to a lesser extent, landless labor, and hurts urban groups, including the

urban poor. On an overall basis, even though the incomes of the rich

farmers are raised more than proportionately and the urban poor are hurt,

the net reduction in poverty is significant. Policy actions are required to

maintain the agricultural terms of trade, as the terms of trade have a

neutral tendency to worsen with growth. Governments could perform this

effectively by utilizing various policy supports like easy agricultural credit,

subsidies, support prices, crop insurance, etc. Ahluwalia (1976a) also

suggests that for inequality to decline, the share of agricultural sector in

total production must be increased by increasing productivity in this sector

which also helps in improving its terms of trade with other sectors.

Policies towards urbanization could also be beneficial in reducing

inequality. In current study, urbanization has been found to be negatively

and significantly affecting Gini ratio at all the tree points of time. Adelman,

Morris and Robinson (1976) also highlighted the significance of urbanization

by laying insistence on rural urban migration. In general, the incomes of the

urban poor are much higher than the incomes of the rural poor, so that

one would expect migration to alleviate overall poverty. However it should

be applied with such policies that could raise the productivity of

agriculture, otherwise agricultural output may decline leading to higher

costs of living, further impoverishing urban workers. The population policy

can also be instrumental in checking inequalities. There majority of

developing countries suffer from increasing growth rate of population.

These countries could do well to curtail down their population growth rates

and restrict it to around one percent or so. An effort was made to study the

261

impact of population growth on inequality in the present study and it was

discovered that increasing growth rate of the population is often related

with greater inequalities. Adelman and Morris (1973) found that reduction in

the rural population reduces poverty by decreasing the agricultural labor

force. It leads to an increase in average land holdings through reductions

in the number of farm households and also results in a more intensive use of

labor. In contrast, the study found that reducing the urban population

leads to an increase in overall poverty by restricting the supply of urban

goods, thus causing their prices to rise, and by lowering the demand for

food products, thus causing their prices to fall the consequence id the

deterioration in the agricultural terms of trade. The negative effect of urban

population reduction could be mitigated by induced increase in migration

to replace the lost urban and act as a substitute for direct reduction in rural

population. Ahluwalia (1976b) also found reduced population growth rates

to be useful in curbing inequalities.

Structural changes are significant ingredient of economic development of

an economy. Hence, suitable policies must be formulated which could

make the structure of a country more conducive to growth. For bringing

about equality in income distribution, such policies must be framed which

encourages greater participation of labor force in service sector as the

growth in this sector is found to have negative impact on inequalities.

Higher employment and value addition in this sector have been found to

have dampening impact on Gini ratio under the present study. Higher

employment and value addition in the secondary sector has also been

found to be negatively affecting inequalities. The governments could also

encourage small scale and tiny industries by providing them easy credit,

subsidies, etc. these structural changes are also desirable for bringing

improvements in terms of trade for agricultural sector. Adelman and Morris

study (1973) also supports the above arguments.

262

Development strategies that stress the growth of more diversified

manufactured exports tend to have favorable distributional effects. They

lead to higher incomes for middle quintile groups. And in economically

advance countries may even improve the position of the poor. In present

study, the economies with higher percentage of manufactured goods

meant to export were found to have lesser inequalities, which points to the

importance of structure of exports in working out the problem of inequality.

Adelman and Morris study (1973) found that developing economies could

vitally surf over their hurdles of poverty and inequality by involving in labor

export strategies.

Perhaps the most frequently proposed anti poverty measure is that of direct

transfer to the poor. Two distinct types of transfer programs could be used:

i). Direct income transfers, and ii). Price transfers for consumption of

necessities. Such transfers could help the certain target group and have

been followed in several economies. Adelman and Morris study (1973)

reached the conclusion that such policies have least leakages and market

distortions effects. The study, nevertheless, found that the effects of the

price subsidy programs get eroded overtime, as income rise, the share

spent on necessities falls. Also in case of such programs, the effects last as

long as the program is in effect and therefore, if such programs are to be

the major tool of anti poverty policy, society must be committed to

persistently large welfare budgets. Also, the governments should be vigilant

about the mis-utilization of such schemes.

Expansion in the direct economic role of the government could be another

policy tool for ensuring equalities. Ranis and Fei (1964) found that

economies at the intermediate and high levels could enhance the income

distribution by expanding the direct economic role of the government‘s

share in net investment, nevertheless, this policy seems to be favorable to

middle quintile, reduces the share of top quintiles, but do no good to

bottom quintile groups. The leveling effects of top quintile found to be

263

significantly ideological rather than a consequence of the disinterestedness

of the authorities; that is, economies with heavy government sectors are

typically socialist economies and therefore opposed to the accrual of large

profits in the hands of upper income groups. Adelman and Morris study

(1973) also discovered significant direct government economic activity to

be equality enhancing. Nevertheless , in the present scenario of

globalization , liberalization and privatization the relevance and scope for

exercising this policy option has prove to be limited.

Tax system provides the planners with another tool for fighting inequalities.

To check inequalities, a progressive tax structure could be devised so that

rich bear greater burden of taxes than the poor. However, the tax rates

should not be so high as to have disincentive impact on investment.

Adelman and Morris (1973), in their study of 43 underdeveloped economies

found tax structure to be unimportant determinant of income distribution.

They attributed this finding to the fact that in under developing economies,

tax base is sufficiently low and as such there is little scope for the impact.

The policy implication which can be derived from the above study is that,

efforts should be made to bring optimum number of individuals under the

tax bracket. Although while applying this tool, governments must be

cautious about disincentive effects of higher tax rates. Tax structure should

be moderately progressive in character, so as to restore a balance

between the twin objectives of equality and efficiency.

The most significant tool to face off with unequal distribution of income is

investment in human capital. Human capital formation takes the form of

better education, health and environmental facilities. The key to higher

growth as well as equality, significantly lies in stepping up the rate of human

capital formation. In the present study, educational dimension of human

capital formation has been represented by primary and secondary school

enrolment ratio and literacy rate. It has been found that higher primary and

secondary enrolment ratio have dampening effect on inequalities as

264

measured by Gini ratio. It has also been found that higher expenditure on

public health and education programs helps in reducing income

disparities. Adelman and Morris (1973) also outlined the significance of rate

of improvement in human resources as a toolm to take care of income

inequalities.

Chiswick (1971) presented a model in which differences in the earnings of

the individuals are accounted for solely by distinction in their training. He

deducted that variability in earned income should be functionally related

to four factors:

i). The inequality of investment in human assets.

ii). The mean level of investment in human asset.

iii). The mean level of the rate of return to human asset investment.

iv). The inequality in the rate of return to investment in human asset.

Thus, he concluded that by bringing about inequality in human capital

investment, egalitarian goals can be attained.

Adelman (1974) outlined the significant role played by human asset in

inequality eradication. Literacy, he says, will create more skilled manpower

which in turn will make a shift from low paid, unskilled employment to high

paid, skilled employment. This switch over, it is argued, produces greater

labor incomes, a reduction in skill differentials and an increase in the share

of wages in overall output. Hence inequality declines as literacy expands.

Therefore, efforts should be made by governments of various developing

economies to spread education far and wide. Primary education should

be made free and compulsory. Health facilities should also be promoted sa

as to improve the general health of the work force.

Tesliuc (2001) in her study for Romania, also stressed the need for human

asset creation for fighting out poverty and inequality. Finnie (2001), in a

study in Canada, highlights the need for governments to support individuals

invest in their earning capacities which will help them in moving up the

income level over time, and enhancing the opportunities available to the

265

next generation. UNDP poverty report, 2008, (UNDP, 2008), presents a two

track approach to poverty reduction: growth on one track and human

development on the other. The report highlighted that these two tracks

rarely interact and the latter track is instrumental in directly curtailing

poverty.

One way to make dent on growing inequalities could be, to strengthen the

unity among the poor. It has been found that if poor organize themselves in

a proper manner, then they could claim their share of power more

effectively. Effective and strengthened deprived unions should be formed

which could cater the bottom quintiles a platform to voice their basic

needs.

Greater participation of females in the work force can also bring about

reduction in inequalities. In the present study, higher female participation in

work force has been found to be making negative dent on inequalities, as

measured by the Gini ratio. These results are in conformity with Adelman

and Morris (1973) study. Thus, Policies aiming at gender empowerment also

help in bringing about more equitable income distribution.

Another policy for ensuring equality could increase the efficiency of

financial establishments by utilizing certain improvements. Poor farmers

must be provided access to credit. Cheap credit should also be available

to small scale industries. Nevertheless, Adelman and Morris (1973), found no

systematic relation between financial institutions and distribution of income.

Larger political participation by the public has also been advocated as

one policy option for ensuring equality. However, hopes on this front get

little support from empirical findings such as those conducted by Ranis and

Fei (1964), and Adelman and Morris (1973). These studies suggest most

important instruments for increasing political participation in developing

economies are those that involves basic modifications in social and

economic and political foundation as well as basic reorientation of growth

planning. The initiation of genuinely permissive and efficient party systems,

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and the expansion of the political role of the middle quintile, and the

growth of social and economic establishments of two type that favor the

inclusive system s, all that needed a set of concurrent structural

modification that could be achieved only with a wide approach of

advancement and further growth. Thus the path to social justice through

greater political participation is no less thorny than the path to social justice

through improving the distribution of income.

Going through the various policy options available to the policy makers,

one could clearly assume that adoption of one or two certain policies.

Greater magnitudes of the policy effort are necessary to avoid rapid

erosion of benefits. Since individual programs tend to be considerably less

effective than packages of programs and the benefit of single-pronged

interventions rapidly trickle up, therefore a big push balanced system

appears to be best. Nevertheless, a successful big push requires a major

government intervention and large implicit and explicit economic transfers.

Therefore , the implementation of a successful equality efficiency program

would entail either a change in the ideology of the ruling class towards

explicit egalitarian concerns or a certain extent of centralization of

authority in order to overcome resistance by the rich, or most likely a

combination of both. The problem would then remain of reducing the

power of the centralized authority once its basic job is completed.

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CHAPTER- IX

Conclusion & Suggestions for Policy Implication

This Chapter examines the relationship among Inflation, income distribution,

and Economic Growth in India. The effect of income distribution on

economic growth and how inflation relates to income distribution had

been appeared in many studies. However, most of the studies are focused

on the United States, the United Kingdom and the developing countries in

Latin America. There is lack of studies on emerging economies in South East

Asia. To fill the gap, an attempt has been made to examine the relation

among economic growth, income distribution and inflation in India. Error-

Correction model is used to examine the co-integration movement of the

data in 1983-2010.

Income Inequality and Economic Growth

Hypothesis of economic theory suggests that income inequality is

negatively associated with economic growth. There exist three

explanations that relates income inequality with growth. Alesina and

Roderick (1994) and Person and Tabellini (1994) are of the view that in

political-economy approach to explain the relationship between income

distribution and economic growth considering developing economies with

reference to inequality. The concerned hypothesis suggests that median

voter favours the policies of the government that improves the access of

resources from top to bottom quintile. Such policies of resources

redistribution impedes economic decision by relying on tax -promotion

activities. Consequently, income inequality is negatively relates with

economic growth.

Socio-political instability approach is used to explain the relation differently.

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((Perotti, 1993), (Alesina & Perotti, 1994), and (Benhabib & Rustichini, 1996)).

Suggest that growth is suppressed by income inequality because of social

conflict that exists in the societies. Their hypothesis suggests that societies

with higher income inequality face more social conflict, and unlawful

activities that impedes development and investment in the economy.

Further, Knack and Keefer (2000) arued that in a highly distinct society,

individuals possess distinct culture and expectation are difficult to make

decision on self-enforcing agreement. Therefore, increase in social

distinctiveness reduces economic growth.

The third approach explains the imperfection of capital markets ( (Aghion

& Boltion, 1992), (Banerjee & Newman, 1993), (Galor & Zeira, 1993), (Aghion

& Bolton, 1997), (Chiu, 1998)). Under the imperfect capital market

approach, income inequality is associated with minimal access to credit for

the bottom quintiles. As such quintiles would not have enough income and

have no access to credit opportunities in order to invest in education

activity, income inequality degrades aggregate investment in human

capital and reduces economic growth for societies.

Inflation and Income Inequality

A mechanism through which inflation could affect income inequality

negatively is by switching income away from wage earners, towards profits.

Tyson (1998) suggests that inflation erodes depreciates real minimum

wages and reduces the income of the poor. Furthermore, inflation is a tax

on poor, who posses their larger fraction of wealth in flat money, more

heavily than the rich who possess both capital and flat money. Therefore,

inflation is claimed to augment income inequality in this sense. Supporting

evidences could be witnessed in Björklund (1991), Blejer and Guerrero

(1990), and Silber and Zilberfarb (1994).

On the other hand, empirical evidences suggesting, inflation may

decrease income inequality could be seen in Bach and Stephenson (1974),

Blinder and Esaki (1978), Blank and Blinder (1986), and Romer and Romer

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(1998). Inflation reduces income inequality through two mediums. First,

Inflation shifts

income from nominal lenders creditor to nominal debtor. As summarized by

Laidler and Parkin (1975), inflation adverse the income of the poor and the

rich significantly as the middle quintile usually possess more nominal debt

than the bottom and the top quintiles. Therefore, inflation is claimed for

decrease inequality.

Second, inflation could also promote redistribution of income through the

tax mechanism. Under the tax mechanism with progressive tax-scales,

inflation transfers higher income earners into higher tax brackets. The present chapter considers the Gini coefficients, CPI and GDP of India

from 1983 to 2010. Table 9.1 exhibits the descriptive statistics of the data.

In the table 9.1 LogGini, LogCPI, and LogGDP are the Log values of Gini, CPI

and GDP respectively. DlogGini, DlogCPI, and DlogGDP refer to the

difference of corresponding data between two successive years. Table 9.2

shows the correlation matrix of DlogGini, DlogCPI and DlogGDP

Table 9.1. The Descriptive Statistics of Data.

Table9. 2. Correlation Matrix of Variables DLogGini DLogGDP DLogCPI DLogGini 1.000 .932 .902 DLogGDP .932 1.000 .470 DLogCPI .970 .470 1.000

Gini LogGini DlogGini CPI LogCPI DlogCPI Dinflate GDP LogGDP DlogGDP

Mean 31.26 1.4946 0.135 70.70 1.7926 0.02707 -0.0085 19915 4.0883 0.0780

Median 31.70 1.5011 0.0017 69.41 1.8413 0.02719 -0.00080 13747 4.1376 0.0602

Maximum 33.90 1.5302 0.3668 130.80 2.1166 0.05593 0.01661 0.05593 0.59 0.43

Minimum 26.00 1.4150 -0.0969 24.303 1.3856 0.00501 -0.02344 2094 3.210 0.0328

Std. Dev. 1.90 0.0283 0.0969 34.33 0.2357 0.01185 0.01132 19059 0.4620 0.119

Skewness -1.49 -1.65 0.0748 0.26 -0.34 0.59 -0.11 1.31 -0.09 5.11

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Gini, CPI, and GDP refer to Gini coefficient, the Wholesale Price Index, and

the Gross domestic product of India respectively. LogGini, LogCPI, and

LogGDP are converted the log values of Gini, CPI and GDP respectively.

The Gini coefficient of India ranges from 31.4 to 34.92 with an average of

33.15. The coefficient changes nearly 1% per year on an average, it exhibits

the fact that income distribution in India is rather stable in past two

decades.

The wholesale price index of India ranges from 22.66 to 130.3 with an

average 76.46. India has a mild inflation (DlogCPI) with average of 3.4% per

year during 1983 – 2010. Dinflate refers to the difference of DlogCPI

between two successive years. The value of Dinflate variates from; -0.1 to

0.008, with an average of -0.003. Which explains that inflation rate in India

remained quite stable in past two decades In other words; inflation rate in

India is stable.

Unit root test (ADF)

Before running regression on the data, ADF unit root test is utilized to check

whether LogGini, LogCPI, LogGDP, and DLogCPI are indicate order 1 (I(1))

integration. Table 9.3 shows the results of ADF unit root test. According to

the results, LogGini, LogCPI, LogGDP, and DLogCPI cannot reject the

hypothesis of having a unit root. On the other hand, DLogGini, Dinflate, and

DLogGDP reject the null hypothesis that there exists a unit root at 5%

significant level. To conclude, LogGini, DLogCPI, and LogGDP are I(1) order

integration.

As utilizing non-stationary variables directly in regression could be result in

spurious regression, it is vital to ensure that all the variables exercised upon

in the regression depict stationarity. According to the results of the ADF unit

root test, LogGini and DLogCPI are non-stationary variables. Therefore, it

would be unsuitable to use them as regression variables. Under the present

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analysis, error-correction model as formulated by Granger and Weiss (1983)

and Engle and Granger (1987) is run to analyze the co-integration linkages

among inflation, income distribution and economic growth.

Table 9.3. ADF Unit root test results

Error correction model as suggested by Engle and Granger (1987) is a two-

series approach to identify whether the dependent variable co-integrates

with the independent variables. In the first equation, Ordinary Least Square

is performed to estimate the variables in levels. The regression equations

are:

LogGDPt = α1 + β1 LogGinit + ut (1)

LogGinit = α2 + β2 DlogCPIt + et (2)

In the above equations, α1 and α2 are the constant terms. Moreover, ut and

et connotes the estimated residuals at time t for the equations. The

regression results of equation (1) And (2) are displayed in Table 9.4. & 9.5

VARIABLES ADF TEST STATISTIC 1 % CRITICAL LEVEL 5 % CRITICAL LEVEL

LogGini -0.188 -5.008 -3.0004

DlogGini -2.11 -1.03 -0.80001

LOgCPI -1.911 -7.336 -4.1034

DlogCPI -3.011 -5.777 -3.0112

Dinflate

7.11** -3.336 -2.8814

LogGDP -2.002 -3.36 -2.0003

DlogGDP -5.003** -4.199 -3.1818

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Table 9.4.: REGRESSION RESULTS ON THE DATA

REGRESSION RESULTS DEPENDENT VARIABLE: Log

GDP

VARIABLE COEEFICIENT STD.ERROR T-STATISTIC PROBABILITY

α1 29.544** 2.5872 9.8816 0.0003 LogGini -17.732** 1.7972 -8.9601 0.0001

R-Sq. Adjusted 0.89

Durbin- Watson 0.7331

Prob. (F-Stat.) 0

**significant at 1 % level; *significant at 5 % level

Table 9.5 REGRESSION RESULTS ON THE DATA

REGRESSION RESULTS ON THE DATA

DEPENDENT VARIABLE: Log LogGini

VARIABLE COEEFICIENT STD.ERROR T-STATISTIC PROBABILITY

α2 1.21** 0.00018 845.932 0 DlogCPI 0.016 0.142 0 0.645

R-Sq. Adjusted 0.029

Durbin- Watson 0.212

Prob. (F-Stat.) 0.112

**significant at 1 % level; *significant at 5 % level

Following the first stage, estimated residuals, µ t-1 and et-1, are utilized for the

analysis of long term co-integration of the variables. OLS is used to estimate

the coefficients in equation (3) and (4). A negative and significant

coefficient associated with the estimated residuals suggests that there exist

a long-term co-integrated movement among variables.

Table 9.6 presents the regression results of equation (3) and (4). In the

equations, α3 , α4 are the constant terms and µ t-1, et-1are the estimated

residuals of equations (1) and (2) at time t-1 respectively.

DLogGDPt = α3 + β3 DLogGinit + β4 µ t-1 (3)

DLogGinit = α4 + β5 Dinflatet + β6 et-1 (4)

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Table 9.6 REGRESSION RESULTS USING ERROR CORRECTION MODEL ON THE DATA DEPENDENT VARIABLE: DlogGDP

ERROR CORRECTION MODEL

VARIABLE COEEFICIENT STD.ERROR T-STATISTIC PROBABILITY

DlogGini -6.215 2.2671 -4.4669 0.003

µt-1 -0.481 0.4761 -1.9937 0.0018

R.Sq. Adjusted 0.4313

Durbin-Watson 1.8169

Prob. (F-Stat.) 0.0015

**significant at 1 % level; * significant at % level

Table 9.7 REGRESSION RESULTS USING ERROR CORRECTION MODEL ON THE DATA DEPENDENT VARIABLE: DlogGini

As the regression results suggests that coefficients of both DLogGini and ut-

1 are negative and significant at 5% level of significance. This explains that

GDP and Gini coefficient are co-integrated with each other. Similarly, On

the other hand, the regression result of equation (4) is unable to provide

evidence on the existence of co-integration between inflation and Gini

coefficient.

To conclude, the empirical results suggest that there exists a long-term co-

integration between economic growth and income inequality. These

findings agree with previous available analysis (see (Perotti, 1993) and

(Alesina & Roderick, 1994)). In other words, unequal distribution of income

impedes economic growth. Moreover, there exists no evidence that

suggests, income distribution has any linkages with inflation in India.

Although some (cross-country) studies suggest that there exists a

ERROR CORRECTION MODEL VARIABLE COEEFICIENT STD.ERROR T-STATISTIC PROBABILITY

Dinflate 0.057 0.1171 0.8183 0.512

e t-1 -0.367 0.1513 -1.9901 0.0871

R.Sq. Adjusted 0.1268

Durbin-Watson 2.5813

Prob. (F-Stat.) 0.1201

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relationship between inflation and income distribution (Li, 2002), but

empirical results on India do not provide evidences on such relationship.

This Chapter examines the relation among Inflation, Income

Distribution and Economic Growth in India. Empirical results suggest that

any rise in inequality impedes growth. Moreover, there is no empirical

evidence to support that inflation is related to income distribution in India.

This conclusion agrees with previous study from Ahn (1997). In his study,

empirical evidences show that there is no relation between increases in

wholesale price index and income distribution. Nevertheless, the rate of

increase in immovable property price degrades distribution of income. As

per CSO Estimates, the average increase in personal disposable income of

India is around 11% in the past twenty years. When compared with the rate

of inflation rate, which is somewhere around 2% annually in India, inflation is

unlikely to disrupt the income of Indian. Therefore, inflation does not affect

income distribution in the case of India.

Suggestion for Policy Implication:

Anti-Inflationary measures

After discussing efficacy, interdependence and limitations of monetary

and fiscal policies in Part-A and the use of several monetary and fiscal

policy measures adopted by the Government and the RBI to contain

Inflation, it is appropriate to sum up the chapter with a consequential

debate of few policy formulation in the background of the main discussion

of the issue under the present study which emanate the in the current

process. The nature and justification of a policy measure can only be

obtained from the theoretical mechanism that relates changes in the

policy instruments and its effects on Inflation.

The previous discussion in the part A brings forth the fact state of

inflation in Indian economy has been chronic ailment and the public views

275

about inflation is, that it would seldom improve. Hence the excess pace of

Inflation in India could be characterized by number of factors.

Not only money supply growing at an accelerating rate unrelated to the

growth of output causes inflationary rise in prices but the forced pace

structural changes taking place during the inflation of subsequent Five Year

Plans in the face of the basic rigidities related with inelasticity‘s of agri

production as well as instability of export earnings resulting in increasing

pressures on balance of payments (current account) coupled with rising

credit supply expectations and increasing size of budgetary deficit,

growing incidence of black money operations, the large opportunities for

corruptions and source of informal competition also exploit the inflationary

climate and aggravates the crisis in the process.

The above inflationary situation not only needs reduction in

aggregate demand to match it with supply but also requires a balance

between demand for and supply of basic wage goods. It, therefore, calls

for a judicious mixture of policy instruments aimed at augmenting supplies

simultaneously controlling demand and dealing firmly with anti-social

elements and institutional forces that exploits the inflationary climate

precipitating the crisis in the process. No amount of economic logic or

social concern can bring desired results unless a vigorous attempt is made

to eliminate corruption and nepotism at various levels and the most

stringent action taken against violators of price control measures, black

marketers and tax evaders. Inflation fighting kit in our conditions, therefore,

requires not only a proper mix of monetary and fiscal policies, but also

income policy regulation, balance of payments, administrative including

direct physical controls, planning and above all a wage-goods production-

oriented strategy which can satisfy the mass demand of vast majority of

population who are below the margin of subsistence or are poor. No anti-

inflationary policy can, therefore, fetch the desired results unless the

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production and distributional shortcomings of wage goods are sternly dealt

with.

Thus the success and effectiveness of an appropriate policy mix depends

Upon a number of coincidence such as (i) the size of the appropriate

response co-efficient; (ii) the time required for a policy change to work itself

out fully; (iii) how best to minimize the undesirable side-effect; and (iv) the

administrative feasibility as well as the necessary political will to fight an all-

out war on inflation.

Inflation, therefore, has to be fought resolutely and on all fronts in a timely

manner with an intelligent use and determined implementation of all the

instruments available from the twin angle reducing aggregate money

demand and increasing aggregate real supplies and thus enable the

economy to progress with relative stability towards economic growth and

social justice.

The following package of measures which contains the essentials of the

framework of policy against inflation may be suggested in the light of

institutional characteristics of Indian economy and the structural changes.

Monetary Policy

As we have observed in the last section of the chapter that the real and

most conspicuous factors behind the increase in the supply of money have

been the borrowing of the Central Government as well as the overdrafts of

the State Governments from the Reserve Bank or deficit financing by the

Government of India .This does not liquidate itself overtime but has been

keeping one increasing the stock of money and adding to its multiplier

effect. What is required is the enunciation and implementation of a proper

credit planning on the part of Reserve bank by limiting the expansion of

currency both on Central Government account and the States overdraft to

a level that would keep pace with growth in real output. At the same time,

from macro level perspective of maintenance of stability in the level of

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prices, a substantial reduction in the proportion of bank credit for financing

private sector has also to be laid down and the Reserve Bank must also

Indicate micro level opportunities for substitute ant-inflationary financing so

that the micro limits must be encased in a micro ceiling of permissible

increase in money supply in each season in the light of the goal of

obtaining and ensuring price stability. This implies a reduction of credit in

each short period in the light of the knowledge of the initial endowment

and potential of different industries for fulfilling needs of social priority not

only with a view to make credit containment process less harsh on small

firms as against big firms but also to prevent he use of short term credit for

long term purposes and also to make the firms more sensitive to the interest

rate adjustments.

But it is not enough that money supply is reduced and that the rate of

growth of money supply is kept within a ceiling. Care has also to be taken

to deal with the problem of black money which is outside the control of

Reserve Bank or the Finance Ministry and yet has potent effects of an

inflationary character. A massive operation against the system which has

led to the emergence of the black sector must be concluded because the

organized financial markets have become a sieve for flow of funds,

relatively cheaply, to the black sector. It is, therefore, necessary to pay

great attention towards the containment of bank credit and for the

scrutiny of the process by which funds are funneled at relatively lower

interest rates. Thus the strategy for containing inflation in respect of

monetary policy has to be formulated not only to reduce the stock of

money but also to plan to keep the rate of growth of the stock of money

within feasible limit of the rate of growth of production of wage goods so

that the existing capacity of wage-goods may be expanded and the

availability of stocks in each short period is permitted to the highest extent

possible. In framing such policy, the following considerations are the

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relevant and should be the guideline of a proper credit planning: (i) the

growing stock of money must be reduced, (ii)must be limited to the rate of

growth of production of wage goods must be maximized , and rate of

growth of money stock must be limited to the rate of growth of production

of wage good, and (iii) the rate oil growth of production of wage goods

must be maximized, given the saving fund, by reallocations of the pattern

of savings and investments.

Taking above aspects into considerations, a large number of economists

favored fixing a ceiling for annual average growth rate in money supply at

5 per cent. In fact, if the level of prices is to be kept reasonably stable, a

provision has to be made for a ceiling on growth rate in money supply,

somewhat in excess of the growth rate in real output and of the index of

supply of essential commodities based on the experience in recent past. If

the annual average ceiling rate of money supply is fixed on 5 per cent over

a successive period of five years, the fixed ceiling rate would require that

over the five years the aggregate money supply should not exceed 25 per

cent. In the initial year, if money supply has been augmented by more than

what would have been required over the five year period, the Authorities

would have to construct money supply in the subsequent period. Thus, the

ceiling rate has an advantage over the rigid year by year fixed rate, since it

permits room for seasonal variations in activity in demand for money,

contingency factors like the drain on currency into and out of hoards,

variations in hot money inflows, adjustments for sectoral recessions and

such other factors which may be helping to promote monetization. At the

same time, Government sector and the industrial commercial sector would

be in a position to know roughly, how much credit they can expect from

the banking sector during five years and will work within that limit and also

tap other sources of liquidity and finances. Thus, the fixed ceiling rate will

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not only promote the best use of available resources but also establish the

prospect of continued price stability.

In order to ensure that the fixed monetary growth rule over a successive

periods of five years is run on sound lines, it is necessary to implement the

long pending demand of a large number of economists regarding the

constitution of a national credit council under the joint aegis of the Reserve

Bank and the finanace ministry including representatives of industrial and

labour organizations. The council should meet twice year, once prior to the

budget, and another after the central budget to work out the broad

guidelines to an ex-ante qualitative credit target for the economy as a

whole in the light of the budgets and the process of growth of time

liabilities, exchange reserves, etc. along with only, indication of five year

sequence of credit targets.

On the whole, there should be clear understanding on its part of the

multiplier effects resulting from the increase in money supply in respect of

deficit financing by the finance ministry and that of the secular growth of

the money stock by the reserve bank. It is only by such a combined

monetary discipline by the reserve bank and the finance ministry that

country can avoid inflationary additions to the stock of money supply and

thus keep aggregate demand from increasing at a pace in excess of the

growth rate in real output.

Fiscal Policy

Fiscal policy consists of both the budgetary and non-budgetary measures.

The budgetary measures are associated with the scale and pattern of

expenditure, on the other Hand, and the method of resource mobilization

or resource procurement to match the expenditures on the other. If there is

gap between capital expenditure and non inflationary capital receipts,

plus surplus from the revenue account, the budgetary deficit normally

appears. To overcome budgetary deficit, the choice before the Fiscal

280

Authorities is between either of reducing the scale of expenditure of

augmenting the non inflationary sources of revenue; or very often the

solution is action on both the fronts. Unfortunates in countries like India, the

Fiscal Authorities have never recognize the limits of budgetary deficits nor

can successfully augment the sources of non inflationary receipts on

revenue and capital accounts. As such, the budgetary deficits have been

going on increasing year by year only with an option to bridge up the gap

through the larger borrowing from the Reserve Bank and the commercial

banks and other financial institutions. The entire process has given birth to

an element of inflexibility to the stock of money and the prospect of

growing inflationary condition by ever expanding the size of money stock.

A vigorous anti inflationary budget and non budgetary measures therefore,

not only requires the eschewal of gap but also the achievement of a

sizeable surplus.

In such context, an attack against inflation through fiscal policy measures

has to be implemented together with monetary measures in timely and

systematic manner so that not only it can recognize the limits of budgetary

deficit on the part of Central and State Governments by recognizing the

multiplier effects of high powered money as well as the need for reducing

necessary and uneconomic public expenditure but also take into account

the inbuilt inflationary element in the present structure and the level of

taxation along with stringent action to unearth the growing incidence of

black money. Hence, a multi pronged action in the sphere of fiscal policy is

needed from the point of view of reducing the scale of expenditure and of

augmenting non inflationary sources of revenue or an appropriate action

on both the fronts.

To avoid inflationary conditions and to restore the proper health of

economy, the following package of measures in the sphere of fiscal policy

must be taken into consideration which includes: (i) a well thought out

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expenditure policy, (ii) simplification of tax structure and other measures to

unearth black money.

(i) A well thought out expenditure policy

It is necessary to take steps to plan for a well thought-out expenditure

policy and to improve the utilization of resources in the best possible

manner so as to avoid growing incidence of inflation. The objective here is

not so much to abandon programs but rephrase them in a systematic

manner so that large budgetary deficit can be minimized or avoided in the

interest of stability and growth.

To work out such a policy, the following principle of expenditure may be

suggested:

a) Reduction in expenditure must be examined from the point of view of

its impact on current basic production and in the creation of new basic

capacity. This implies a cut in expenditure on administration and

expenditure on non productive usage like expenditure on large size of

ministries at the centre and various states, frills, display, ostentation,

prestige and other forms of conspicuous consumption which can be

reduced considerably without affecting efficiency in administration. At

the same time, there is also scope for a substantial reduction in various

types of subsidies which do not serve a definite fiscal purpose in

achieving crucial socio-economic goals. A system of tightening of

repayment procedures in regard to loan to third parties, on the one

hand, and the upward revision in interest rates, on the other, can help

in this direction.

b) Although inflationary fiscal sources must be created for financing relief

operations under natural calamities like drought floods and famines.

Assistance towards financing such natural calamities may be created

by imposing an emergency surcharge on addition to incomes

accruing to non fixed income groups and individuals for a temporary

282

period in order to avoid misuse of facility, it is necessary to lay down

principles and guidelines for such outlays.

c) Allocation of resources in the scheme of production of those materials

and goods must get priority which are in short supply so that a specific

commodity demand impact on the supplies in food and other wage

goods may be minimized.

d) Instead of large number of incomplete and non-immediately

completable scheme, it is better to have a number of programmes

wholly completed within a given period of time from nation‘s point of

interest. Moreover it is beneficial to have always categorized lists of

projects from the angle of dispensability and postponablity during the

periods of severe inflationary circumstances.

e) Profit from the established PSU‘s must be augmented by radically

transposing them towards a sense of social commitment.

f) For the purpose of raising capital expenditure external borrowings must

be promoted for long term projects with preplanned repayment

structure for the same, so that interest repayment and installment could

be paid back from the receipt of the same projects within specified

period of time.

ii). Simplified Tax Structure and measures to control Black Money

Motives

The overall framework of taxation in Indian economic scenario needs

radical appraisal to war on inflation as well as no incentive effect on saving

and production. The instruments of tax ations, therefore has to be

effectively used to create maximum disincentives against luxury and non

functional consumption on the part of both the individual and the firms so

as to siphon excess demand on scarce commodities. But until and unless

the high rising tax evasion is effectively curbed by suitable distribution

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effects of inflation which has been favoring the receivers of unaccounted

money and assets who are the predominant beneficiaries of inflation is

unlikely to be curbed or even maximum incentives could rarely be

encouraged.

The specific cause of tax evasion, creation of black money and its

proliferation have been the present structure of taxation, economy, of

shortages and consequent controls and licenses, donations to political

parties, corrupt business practices, strident increases in government and

public sector spending general deterioration in moral standards, growing

incidence of inflation, ineffective and weak deterrence in the

Enforcement of tax laws etc.

Several packages of measure to unearth tax evasion and unaccounted

money have been suggested by various committees and economist in light

of the above causes which are discussed way forward.

1. Tax Simplification Structure

Among the measure to fight tax evasion tax on company profits, personal

income tax, wealth tax, stamp duties and estate duty should be reduced

substantially. Similarly, periodical upward revisions of tax exemption level,

allowances and tax brackets to neutralize the impact of inflation. There

require a suitable adjustment in the exchange value of the rupee and

easing of exchange control as one of the measures for discouraging tax

evasion although the real problem is that even the modest rates of

taxations as obtained today, those in high income brackets and are the

dominant beneficiaries of inflation do not want to pay taxes and rather like

to evade on a massive scale. Obviously, the government has to take some

strong measures which should be keen to realize tax revenue from

individual who fall in top income range, these should include the following:

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i. Search agencies should be allotted check and seizure operations

should be undertaken continuously with higher discrimination and

heavy penalties so that costs and risks involved in tax evasion become

prohibitive and a fear psychosis may develop among the tax evaders.

ii. Every voter must be should be allotted permanent income tax account

number supplemented by the central taxes pass books containing

detailed information about assessed income and the various sources of

income and wealth and the transfers effected in the form of gifts,

purchases or sale of real estate, plant and equipment.

iii. To promote integrity among senior officials, there should be a system of

reward and punishment and a significant level of remuneration for

senior officials should fix than that existing at present level.

2. Decontrol and reduced license

Besides simplification of tax structure, steps should be taken to minimize

controls and licenses so that these should be confined to only essential

purposes and could not be administered effectively with less harassment to

the public in other words to avoid cumulative black markets and resulting

reinforcement of inflationary pressures there should be a shifting from

discretionary controls which would not only rationalize the system but also

support them with an effective system of distribution.

3. Initiation of national fund

There should be no question regarding black money sources which would

be invested against debentures with the maturity period of more than 10 to

12 years and carrying an interest rte of 7 per cent. There should be a value

of debentures and interest thereon would be subject to wealth tax and

income tax but exempt from gift tax. There would be some better schemes

of demonetization to unearth black money because the net effect of

demonetization to destroy the black incomes would be too insignificant in

the face of huge parallel economy operated with unaccounted incomes.

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4. Accountability Fixation on Real Estate Transaction

The most important sector where black income is generally invested is the

real estate transactions. It is therefore necessary to set up cooperation in

each state and union territory through which all the private buyers and

sellers will have to transact for legalization of their urbanproperty

transactions which will not only know the quantum of capital gains

accruing from those transactions but will provide an opportunity to the

state to tax these capital gains appropriately .

Income Policy Regulation

The primary objective of an income policy is to ensure that rate of growth

of wages or income is not higher than the rate of growth of productivity

because any upward revision of wages and salaries unrelated with overall

increase in productivity leads to generation of inflationary pressure in the

economy. In this situation where the demand for wage increments

become generalized there is a tendency for administered price increases,

credit expansion, monetization of liquid assets, expanded budget deficit,

expansion of money supply which invariably leads to inflationary pressure in

the economy. It is therefore necessary that an upward revision of wages

not to be allowed from from the micro angle of sectoral productivity

improvement in case of severe inflation but should be look upon from a

micro angle or an aggregate point of view to the extent of average

productivity improvement in the economy so as to limit the rate of such

micro increment in wages not more than national average of productivity

improvement. One of the important improvements which could be

suggested towards the attainment of this end is to require a prior sanction

from a national board for every micro level wage or salary increment.

Income policy therefore has an efficiency aspect as well as equity aspect.

Wage increases and gains in productivity improvements are to be looked

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upon from this twin angle. But it is not possible to introduce fundamental

changes in the structure of wages and salaries, profits and dividends during

an anti inflationary program for both the angles.

Food Production

As food constitutes main wage goods an increase in food production in

relation to increase in demand in the major and permanent remedy for

dealing with food prices and therefore the general price level. While this

essentially a long term solution it is possible to bring about some some

increase in food production by short term measures. This requires not only

public investment in quick maturing irrigation projects as well as fuller

utilization of irrigation potential already created and the completion of

projects underway but also expansion of capacity and output in industries

related to fertilizers, pesticides and agricultural implements. Thus as the high

income elasticity of demand for food has been putting an upward

pressures on food prices and therefore on general price level, it is necessary

to allocate additional plan outlays as much as economy can viably

absorb, for the irrigation projects, flood control, soil management and

fertilizer expansion so as to eliminate shortages of agricultural commodities

in regard to both the food and non food items which have been the

potential source of inflation in our conditions.

Industrial Production

From the point of view of industries which are directly and indirectly

involved in production of wage goods, like food products, oil, salts etc. are

of fundamental importance and the immediate need is to strengthen and

increase the expansion of capacity and output of these industries in order

to contain pressure on limited supplies and, therefore , on prices.

The second category comprises those industries which are intrinsically

related to expansion potential of the wage-goods, such as, building and

construction materials, agricultural implements, fertilizers, related

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chemicals, pesticides. These industries are also to be given top priority for

building crucial infra base of wage goods subsystem from the long run

point of view.

The industries which come under third order category are those related to

export expansions which are not only necessary for increasing earnings but

also to create adequate employment in the economy. In this sphere, the

right type of import substituting industries which can be viable, efficient and

internationally competitive without subsidies, in the given time period, has

to be chosen, so that the twin goals of self reliance through import

substitution do not in their wake generate a rising tendency in the prices

essential commodities. There is a good and expanding market of India‘s

luxury goods in the abroad. A fast expansion in some of these lines may

help in increasing export earning, provided care has to be taken to restrain

domestic consumption of such goods.

The basic solution to augment industrial production in these industries and

to overcome the inflationary potential in the economy lies in the

maintenance of the optimum inventory levels, better utilization of capacity,

improving the climate for industrial peace, proper incentive and better

factory lay out, etc. unless, these efficiency augmentation measures are

adopted by all types of Indian industries sincerely, especially the public

sector, which have become notorious on this score and the lessons of the

persistent short falls in power output in the past are properly leant, it is not

possible to overcome the shortfall in industrial production which has been

the potential source of inflation.

Public Distribution System

Augmentation of production of essential wage goods and crucial input

relevant to wage goods in the sphere of both the agricultural and industry

would not be enough to contain inflation unless distributional shortcomings

of the public distribution system are effectively dealt with.

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The area of operation of the public distribution system should

centre on:

a) The maintenance and building of buffer stocks by improving and

strengthening the existing system of the procurement;

b) The distribution of essential commodities out of stock to consumers in

such a manner so as to assure stability in per capita supply throughout

the year; and

c) The maintence of balance in relative prices through countervailing sale

and purchase operations. To minimize mal distribution and to augment

flexibility in supply position of the existing public distribution system, the

following measures may be taken into consideration:

i. To avoid Inflationary pressure and to build up a substantial buffer stock

with the public distribution system what is required is to fix

procurement prices realistically taking into consideration the rise in

the cost of inputs, prices and the volume of buffer stock at the

disposal of the government . while support price should be taken into

account changes in technology and in costs of inputs and should be

announced well before the sowing season, procurement prices must

take into account the volume of existing stocks with government

together with a possible estimate of the government harvest, not just

on a global basis, but on estimates of the expected harvest, not only

on a world level, but on estimates of different agro climatic regions

and sub-regions, so as to fulfill the procurement target efficiently.

Furthermore, a part of the procurement should be strengthened by a

system of uniform and compulsory levy.

ii. In spite of offering greater amount of procurement prices, the same

objective could be reached by offering to agro inputs like fertilizers,

related chemicals and pesticides at reasonable prices. Such a tie-up

between procurement and input supply would not only help in

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restraining output prices, but also provide incentives for increased

production.

iii. In order to abstain from the pressure on limited supply and, therefore

on prices, the estimates of distribution of the aggregate stocks in

different states has to be planned for each agricultural season. At the

same time, decentralized buffer stocks should be centered and

develop within each state to fulfill the requirement of the distribution

network. It is also necessary to create and strengthen the consumer‘s

resistance movements particularly in regard to conventional

necessities.

It should be obligation of each state government to

provide minimum required stock at a general rate in the overall economy

under the running scheme of public distribution system in order to contain

pressures on limited supply at the open market.

The Plan

In large Indian economy where the huge majority of population survives on

the line of poverty, planning should be base on socially desirable pattern of

production. It is bound to create a pressure on limited supply and therefore

on the prices itself. Hence there emerges a dire need for fundamental

modification in planning technique for the betterment of wage goods

model, which is only feasible only available alternative for the greater

balance in the economy, and for solving the acute problem of poverty in

strengthening the economic base of Indian economy.

The entire planning effort therefore requires a modification in the

investment pattern which should be conceived in the form of three ties of

brackets of investment in the following order:

1. The first tier should involve the investment in both the sectors viz. Public

& Private, in respect of expansion of output levels and underutilized

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capacity under full use in the wage goods sub system and of the

predominantly export oriented lines.

2. The second tier should comprise investment in crucial infra sphere which

are intrinsically associated with the expansion potential of the wage

goods. Sub system and of the export sector, and

3. The third tier should contain investment in significant heavy industry lines

needed for modernizing the technological base of India.

Hence, from the forgoing discussion, it emerges that the problem of

inflation in our conditions needs to be tackled from the twin angle of

reducing aggregate money demand and increasing aggregate real

supplies. But a complete avoidance of inflation in the face of deep

rooted corruption in social and institutional framework in the absence of

reliable information about relevant response coefficient as well as

during the process of development is nodoubt a complex issue.

Although, reasonable price stability could be reached, provided there

exists a determination on the part of Government and Public in this

direction. There should not be feeling of helplessness regarding

controlling inflation. At the same time, as previously mentioned, that

inflation could not be kept under the check by meager measures. What

is required is action from all the fronts, with a wise, courageous and

timely lead by the authorities and the Government and utmost

cooperation from all the sections of the society, which would enable

the economy to progress with relative stability towards economic

growth and social justice.

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Suggested measures for equitable Income Distribution

Action for Equitable Income Distribution

The status of economic performance in developing economies round the

world, good as it is in terms of growth has been unsatisfactory in terms of

social justice. Indeed, growth, either planned or unplanned, has only made

things worse. Since there is apparently no simple way of changing things for

the better, some radical reorientation of both ends and means are

desirable.

With respect to ends, the minimum short time goal which is considered

desirable acceptable from the point of view of social justice is to augment

the average income of the bottom quintile at least near to the average

income of India as whole. On an overall basis, development planning has

insisted economic criteria for selection between plan and project options,

creating sizeable contribution to the growth rate GNP per capita. Even

then this criterion is tantamount to providing an equal weightage to all

value of income. Since, on an average, the top quintile of the population

possess almost 50 per cent of the overall income where as the bottom

quintile gets only 5 per cent, any increase in the income of the rich are

strongly allotted more than the ten times weightage per capita than the

increase in income for the poor. This requires a more egalitarian planning

approach.

Hollis chenery(1975), favored an approach, that is, to weight the

percentage income improvement on a per capita basis: thus, with current

income shares, a unit increase in income of the poorest quintile must be

approved ten times weightage of the same increase in the income of the

Top quintile. Other approaches may involve weighting of the income, utility

or such elements of welfare as education, health, housing and jobs. For any

such approach, surely, interpersonal comparisons are desirable. These

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comparisons are easily mange, in spite of their allergies to economic

thinkers; in fact, they are implicit on an overall governmental taxation and

expenditure policies, as well as in the use of income itself as a measure of

welfare.

A reorientation of planning target towards achieving greater equality is not

sufficient. We need, not only fresh targets but also new instruments for

achieving them, new institutions to supplement the market and non market

agencies that have served the rich so well and the poor so badly.

Piecemeal policies could rarely benefit the poor significantly unless

accompanied by basic institutional reforms.

Planning institutional reforms involves a thorough knowledge of social and

institutional settings as well as of the complex interrelational linkages

between society, bureaucracy and the economy. The planners must

explicitly involve interactions among all these items. The results of Adelmen

and Morris(1974) suggests that four interaction processes specifically

needed to be incorporated: i). How economic models lead to modify in

social structures.

ii). How social transformations affects the economy and how they generate

pressures on the political system for the anticipation of special interests and

for a share in the benefits of modernization.

iii). How the political system translates these pressure into public policies

iv). How these public policies affect the strategy and the processes of

economic modernization. Only by closing the analytic circle, could

planners take account of the totality of the indirect effects of a given plan

and guard against the possibility with respect to income distribution that

the indirect effects would overweight the direct effects and reverse their

intended direction.

Development planning must possess three characteristics if it is willing to

increase the income equality. First, it must focus on the question, who

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benefits? This requires careful monitoring of the micro effects of planning

policies. Neither aggregative model nor conventional regional or sectoral;

models offer a fine enough description of economic behavior to permit a

useful analysis of their distributional effects. New planning approaches and

mechanism will have to be devised for this purpose.

Secondly, full account must be taken of the interdependencies within the

economic system. The income distribution is determined by an interaction

among what is consumed, all modified by the social and institutional

structure of the nation. Partial equilibrium approaches focusing on one of

these factors cannot give adequate guidance to the formation of

distribution oriented development strategies, since they inevitably ignore

secondary and higher order effects. Lastly, planning models should be

dynamic. The inter generational transmission of wealth and skills, and of

access of their acquisition plays a fundamental role in shaping patterns of

income distribution overtime and has significant social equity implications

for any given income distribution.

It may be concluded that we must recognize the need for uplifting the

world‘s underprivileged people and the business cannot be allowed to

continue as in past. The experience shows that development policies that

ought in principle to have made for a more equitable distribution of

income have served merely a additional instruments for increasing wealth

and power of existing elites. The policy instruments in the standard of living

of the poor require a basic orientation in development strategies. Key to

curbing inequalities lies really in accelerating the pace of human resource

development, controlling population and having an effective safety net

programme for the poor. Democratic institutions must also be strengthened

so that poor can raise their voice more effectively. In fact, the only

acceptable strategy for the decades ahead is development of the

people, by the people and for the people. Without new institutions and

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policies specifically designed to improve the lot of poor, there is no realistic

chance for social justice3 in the developing world in this mean time.

Special policies for protecting the poor warrant attention in view of

structural adjustments programmes initiated by various developing

economies under the current regime of liberalization, globalization and

privatization. Globalization affects social policy both at the normative level

in a more practical way, by setting constraints that social policy must be

attentive to. Adhesion to international conventions and responses to an

international discourse on social rights permeates domestic politics and

affect special policy. A study by Lundenberg and Milanovic (2001) found

that globalization has in fact widened the gap between the rich and the

poor economies, which is highly undesirable from the equity perspective.

Jha (2000) studied the Indian case and found that have added to the

woes of the poor. Although poverty has declined marginally but urban

inequalities have risen sharply.

These studies highlight the growing importance of social policy in inequality

reduction. These also pinpoint to the growing need for governmental

interventions in the present scenario, as the private sector basically is

efficiency oriented in its approach and has no humanitarian concerns.

Government should also not allow the developed economies to flood their

markets to dump cheaper products. Indigenous industries and agriculture

have to be protected under the changing international perspective since

rules of the game are not favorable to the smaller players because these

have been devised by the big brothers and hence just serve their ulterior

motives.

On the basis of present study it may be concluded that developing

economies do needed to initiate an equity efficiently programmed to

narrow down the widening wedge between rich and poor. Such an equity

efficiency program should:

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i. Promote fast and sustainable growth that benefit the poor and reduces

inequality.

ii. Strengthen the participation of poor people in political processes and local

decision making.

iii. Reduce vulnerability to economic shocks, natural disasters ill health, and

violence- as poor often hit hard by such factors.

iv. Invest in people through education, healthcare and basic social services-as

human resource development is equity ensuring in its total effect.

v. Promote gender equity and eliminate other types of social exclusion.

vi. Forge effective partnerships between civil society, governments and

international agencies.

vii. Encourage public discussion of the goals of development planning and the

means to achieving them.

viii. Encourage coordination among the poor, so that they become more

articulate about their needs.

ix. Devise policies to curtail the rapid growth of population.

x. Bring structural changes in the economy, which are more commensurate

with larger growth of services sector as growth of this sector has negative

effect on poverty and inequality.

xi. Develop well thought out safety net programs and to ensure that benefits

are not only appropriate by the non target groups.

xii. Devise effective tax structure which is moderately progressive, so that it

should be equity oriented but at the same time should nullify the

disincentive effects associated with a progressive tax structure.

xiii. Implement land reforms along with certain other special measures, which

ensure that the productivity of the redistributed land should remain intact.

These measures may include financial support for providing access to poor

farmers to new technology, high yield variety seeds, fertilizers, etc.

xiv. Ensure that the agriculture terms of trade do not deteriorate.

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xv. Encourage greater urbanization policies as it reduces the gap between the

rich and the poor.

xvi. Promote larger share of the manufactured exports in total exports of the

country.

xvii. Generate more employment outside the agricultural setup in rural areas via

public works programs and other construction works.

xviii. Protect indigenous agriculture and industry from foreign competition under

the current regime of liberalization, privatization and globalization.

Adaptation of such policies simultaneously can, not only, help the

underdeveloped country like India to tide over the grim problems of

poverty and inequality, but can also help in enlarging the size of the

national cake.