GOVERNMENT EXPENDITURE AND ECONOMIC

GROWTH IN BHUTAN, 1985-2015: A DISAGGREGATED

ANALYSIS

BY

MR. BAL BDR. KHARKA

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF ECONOMICS

(INTERNATIONAL PROGRAM)

FACULTY OF ECONOMICS

THAMMASAT UNIVERSITY

ACADEMIC YEAR 2016

COPYRIGHT OF THAMMASAT UNIVERSITY

GOVERNMENT EXPENDITURE AND ECONOMIC

GROWTH IN BHUTAN, 1985-2015: A DISAGGREGATED

ANALYSIS

BY

MR. BAL BDR. KHARKA

A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF ECONOMICS

(INTERNATIONAL PROGRAM)

FACULTY OF ECONOMICS

THAMMASAT UNIVERSITY

ACADEMIC YEAR 2016

COPYRIGHT OF THAMMASAT UNIVERSITY

(1)

ABSTRACT

This thesis explores the effects of seven economic components of

government expenditure, namely, total expenditure, capital expenditure, current

expenditure, expenditure on agriculture and forest, information and communication,

economic affair and foreign affair on real GDP growth in Bhutan over the period 1985-

2015. In particular, it studies the effect of components of public expenditures that

contributes on a GDP growth in Bhutan. This research analyzed the impact of public

expenditure components on real GDP growth using annual data. We use Cointegration

and Error Correction Model (ECM) methods to examine long run and short run effects

on real GDP growth.

The empirical result showed that the total government expenditure,

capital expenditure, current expenditure, expenditure on agriculture and forest and

expenditure on information and communication are positive and statistically

significantly associated with the real GDP growth in the long run. The composition of

government spending on economic services showed positive but statistically

insignificant relationship with the real GDP growth. On contrary, government spending

on foreign affair has significantly adverse impression on the real GDP growth in the

long run. On the other hand ECM results revealed insignificant association between

expenditure and real GDP. However, ECM term in the GDP growth equation. It entails

that the real GDP will converge to long run equilibrium path when there is short run

deviation.

These research generalize the policy implication that the expenditure on

agriculture and forest and information and communication remains the most preferable

sector of the government to increase its expenditure within the economy.

Keywords: GDP, Government spending, Cointegration, ECM, and Bhutan

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ACKNOWLEDGEMENTS

First and foremost, my sincere thanks goes to the Ministry of Education,

Royal Government of Bhutan for giving me the opportunity to study master degree in

Thailand. And to TICA, I owe my genuine appreciation for providing me with all kind

of support including moral, spiritual and financial matters during the course of my

study.

Secondly, this thesis would not be successful without proper guidance from

my advisor, Dr. Chaleampong Kongcharoen. I would like to thank my advisor for his

constructive recommendations, suggestions, criticisms and advices which are

invaluable to complete this thesis. I also like to acknowledge my chairperson (Prof. Dr.

Pawin Siriprapanukul) and my external committee (Prof. Dr. Sumanee

Suppakomkosai) for all their support and guide to complete my research. I also

indebted to them for acquiescent to commit their precious time and for being so patient

with me all the time.

Thirdly, I exceptionally gratified to my Family, Parents, and Relatives who

have had encouraged and supported me for past two years until I completed my study.

I further acknowledge the support provided by Mr. Udhim Subba (Vice Principal) and

Mr. Jigme Dorji (Teacher) for making this thesis possible.

Last, but certainly not the least, I must thank our international program

coordinator Miss Wannah Vejbrahm. Without her support and encouragement, I would

not have accomplished my study productively within the prescribe time.

Mr. Bal Bdr. Kharka

Thammasat University

April, 2017

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TABLE OF CONTENT

PAGE

ABSTRACT ……………………………………………..……………….......… (1)

ACKNOWLEDGEMENTS …………………………………………….......…. (2)

TABLE OF CONTENT ………………………….…..……………..………........ (3)

LIST OF TABLES …………………………………………….…………......… (6)

LIST OF FIGURES ………………………………………………………....…. (7)

CHAPTER

1. INTRODUCTION …………………………...……………………….……1

1.1 Background of the study ……………………………………….……1

1.2 An overview of Bhutanese Economy …….............................................3

1.3 Gross Domestic Product by broad economic sectors………..................7

1.4 Annual GDP and economic growth rate of Bhutan………………...... 11

1.5 Trends and compositions of government expenditure in Bhutan…... 12

1.6 Composition of government spending by agencies (Ministry)…...... 14

1.7 Statement of the problem………………………................................. 16

1.8 Objectives of the Study ……………………………………….......... 17

1.9 Limitations, scope and organization of the research............................ 17

2. REVIEW OF LITERATURE …………………..………………….….. 19

2.1 Theories explaining the relationship between public expenditure

and economic growth …………………………..........………………... 19

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PAGE

2.2.1 Keynesian theory ………………………………………....…20

2.1.2 Classical theory……………………………………….……...22

2.1.3 The Neo-classical theory ………………………………….....23

2.1.4 Endogenous growth theory…………………………………...24

2.2 Review on past Empirical Studies…………………………………....25

3. RESEARCH DESIGN AND METHODOLOGY …..……………...….. 31

3.1 Theoretical Framework …………………………………….…...….. 31

3.1 The Econometric model and Estimation Techniques………..…...….. 34

3.1 Time Series Properties of the Data…………………………….....….. 37

3.3.1 Estimation issues……………………………………............... 37

3.3.2 Testing for Unit Roots………………………………............... 37

3.3.3 Error Correction Model………………………………............... 38

3.1 Data ……………………………………………………...……...….. 39

3.1 Definition and measurement of variables……………..………...….. 39

3.1 Working hypothesis ………………………………………………....41

4. RESULTS AND DISCUSSIONS..................................................................42

4.1 Descriptive study …………………….…………………………….....42

4.2 Descriptive Statistics……………………………………………….... 50

4.3 Diagnostic Testing... ………………..……………………….............. 52

4.3.1 Correlation Test……………………………………….............. 52

4.3.2 Multicollinearity Test ……………… ………..……….............. 54

4.4 Long run relationship and short run Adjustment ……………........... 55

4.4.1 Unit Root Test…………………………………………............. 55

4.4.2 Co-integration ………………………………..……….............. 56

4.4.3 Long run relationship estimation ……...……………………… 56

4.4.4 Short run adjustment ………..…………………………........... 62

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PAGE

5. CONCLUSIONS AND RECOMMENDATIONS ……………….……68

5.1 Conclusion ………………………………………………………...68

5.2 Policy Recommendations ..........................................................…...70

5.3 Suggestions for future research …………………………………..71

REFERENCES …………………………………………………………………72

APPENDICES ………………………………………………………………….80

A. Estimated result with different specification ……………………………….80

BIOGRAPHY…………………………………………………………………….86

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LIST OF TABLES

TABLES PAGE

1.2.1 Budget Summary of Overall Financial Position for the last five years….....6

1.3.1 Aggregate Outputs of national income ……………………………….......8

1.5.1 Classification of government expenditure by Ministry…………………....15

4.1 Descriptive Statistics…………….……………………………………….…..51

4.2 Model 1: Pair-wise Correlation Matrix………………………………………52

4.3 Model 2: Pair-wise Correlation Matrix……………………………………....53

4.4 Variance Inflation factor ….............................................................................54

4.5 Result of Unit Root Test…..............................................................................55

4.6 Residual Based Test for Co-integration (Stationary Test) …………………..56

4.7 Model 1: Long Run Estimation Result......……………………………….…..57

4.8 Model 2: Long Run Estimation Result......………………………….………..60

4.9 Model 1A: Short Run Estimation Result....…………………………….…….63

4.10 Model 1B: Short Run Estimation Result...…………………….…………....64

4.11 Model 1C: Short Run Estimation Result...………………….………………65

4.12 Model 2: Short Run Estimation Result...……………………….………...…66

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LIST OF FIGURES

FIGURES PAGE

1.3.1 Share of different Sectors to GDP ……………….………….…………….10

1.4.1 Overview of Annual GDP and Economic Growth in Bhutan …....................11

1.5.1 Trend of public expenditure growth in Bhutan .....................................…...13

4.1.1 Real Total Expenditure and real GDP of Bhutan, 1985-2015.........................42

4.1.2 Real capital expenditure and real GDP of Bhutan, 1985-2015.......................43

4.1.3 Real current expenditure and real GD of Bhutan, 1985-2015….....................44

4.1.4 Real agriculture expenditure and real GD of Bhutan, 1985-2015............…...45

4.1.5 Real information expenditure and real GD of Bhutan, 1985-2015.…….…...46

4.1.6 Real economic affair expenditure and real GD of Bhutan, 1985-2015….…..47

4.1.7 Real foreign affair expenditure and real GDP of Bhutan, 1985-2015...….....48

4.1.8 Real gross capital formation and real GDP of Bhutan, 1985-2015.…..….….49

4.1.9 Trend of real tourism revenue and real GDP of Bhutan, 1985-2015…..……50

1

CHAPTER 1

INTRODUCTION

1.1 Background of the study

The relationship between public expenditure and economic growth has

been a long-standing debate in public economic literature. Foundation with Robert Solo

and Trevor Swan, the Neo-Classical economists initiated to investigate how economies

grows (Harberger, 1978). Keynesian economists proposed the government role through

the budget management on the economy. Barro (1990) stated that only the productive

expenditures, such as public investments, can have a significant impact on economic

growth. However, government consumption expenditures would have adverse effects

on growth. Therefore, many developing countries have implemented the public

expenditure as a measure to promote economic prosperity. Moreover, researchers have

focused on the composition of public expenditure on the country’s growth. They

believed that spending on some sectors or types have a greater effect on growth than

the others (Olabisi & Oloni, 2012). Therefore, government expenditure is expected to

bring better economic growth by reducing adverse effects of market failure on economy

and by reducing unproductive use of public funds.

The relationship between economic growth and components of

government expenditure is a critical subject of analysis as these two are related (Stiglitz,

1998). Effective use of nation’s resources for enrichment of both human capital and

physical infrastructures would lead to improve productivity and income, so escalating

the choice for both private and public expenditure prospects (World Bank, 2007). Al-

Yousif (2000) and Abdullah (2000) viewed that enlargement of government

expenditure adds greatly on growth. Keynesian view also suggested that increasing

government expenditure leads to an expansion of outputs, which rises total demand

resulting to an increase in real GDP.

The economic growth based on mercantilism theory that sustenance

government participation in the economy was owing to externalities, failures of the

market and public goods as stated in some reported literature of development. Some

2

economists have seen that a rise in government expenditure can be an effective tool to

spur aggregate demand for a stagnant economy and to bring about crowd-in effects on

the private sector. This is consistent with Keynesian view that the government spending

can positively impact economic growth when the government borrow from the private

sector and inject back through various spending plans.

In general, government has to perform two major functions; country

security and supplies of some public good and services. Security function helps to

reduce the risk of crime, corruption, protect life and property and the country as a whole

from external violence. The second functions encompass roads, defense, health,

education, construction, hydropower, relation, etc. The general view is that expansion

of government expenditure on education, health, agriculture and advancement of

infrastructure improve growth. Ranjan et al. (2008) established that expansion of

government expenditure has significant positive effects on economic growth. Likewise,

a dynamic and resourceful primary sector would empower a nation to nourish its

population, solve unemployment problems, receive external currency and provide fresh

materials for businesses and productions (Mapfumo, Mushunje & Chidoko, 2012).

In reality, many emerging economics of developing countries, the

required expenditure always exceeds the available resources. Huge amount of funds is

spent on defense, administration, development, religion, relation, welfare project and

various other relief operations. Indeed, the position is made worse by limiting the option

of raising additional revenue nationally. Bhutan is one of them. These countries also

have large number of informal sectors to get fund but they lack effective instrument of

collecting taxes. High taxes and borrowing to finance public services may however,

impose excessive burden on individuals and private sector thus decreasing the

incentives to save and invest. At the same time, change in fiscal policy in this regard is

considered as disincentives for private investment growth. On the other hand, the

volume of debt of these nations is also very little and outside borrowing is least

attractive. The best way for the policy maker or government in general, involves

prioritizing government expenditure to the most important sectors of the economy.

Bhutan as a newly evolving economy in the world, the action of

government is significant in scope and significance to accelerate economic growth.

Mostly government’s fiscal policy includes taxation, government expenditure,

3

correcting market failure and providing varieties of public goods such as roads and

bridges, security of a nation and street lighting have become fundamental instruments

of economic growth of a nation. Of the various policy tools, this study concentrates on

government expenditures which are the essential instruments for economic growth. To

this fact, there is neither a general consensus nor consistent evidence found regarding

the meaningful relationship between government expenditures and economic growth

(Chipaumire, Ngirande & Ruswal, 2014). Bhutan has mixed economic performance

since the start of first five year plan in 1961 and this study will focus on the role of

government in term of allocation of its resources on an economy.

1.2 An overview of Bhutanese Economy

Bhutan’s economy is largely based on hydropower, agriculture and

forestry which provide the main livelihood for more than 55% of the total population

at present time. Till the beginning of first five year expansion plan in the nation, the

economic actions were essentially undertaken in classical way. The economic

transactions were made through batter form and taxes were being composed in the form

of kind and human force. The people were to send certain slice of their agricultural,

forest and livestock produce to government and obligatory to provide services of labour

to accomplish national expansion accomplishments.

Today, India contributes largely on Bhutanese economy through trade

and monetary relation, financial assistance, and laborers for development project such

as hydropower and road construction. Moreover, productions in the industrial sectors

are of cottage type. Hydropower potential and Bhutan’s attraction to tourists are main

source income in Bhutan. On an average, the hydropower sector contributes around

45% of its gross revenue to the government. This contribution accounts for about 30%

of the government’s total domestic revenue. However, the government has made some

progress in expanding the country’s productive base by improving social welfares.

Model education, infrastructure development, environmental programs are underway

with support from various multilateral development organizations. Multilateral

development organizations administer generally environmental, social and educational

4

programs. In addition, major investments in the hydropower sector, construction

sectors, training and basic by the government and development partners have critically

contributed to the overall progress of the economy. Eventually, the size and allocation

of government expenditure have transformed remarkably over the last three decades.

The state of public finance management is a matter of serious concern

as government expenditure is increasing faster than available income and external

revenue. Bhutan continues to make momentous and continuous improvement in

achieving the Millennium Development Goals, achievement of vision 20201 and

Bhutan’s goals of green socio-economic development and vision of self-reliance. The

MDGs concerning to poverty elimination, improvement in educational, maternal and

child health, high-risk diseases and environmental sustainability are the main

challenges discussed in any plan period.

Since the commencement of first five year plan and inaugural of the

economy to the external world, Bhutan would able to uphold an increasing trend of

investment. The investment rate in Bhutan has rose from 32% of GDP in the 1980s to

56% in 2015. According to World Bank, Bhutan’s gross domestic saving as a

percentage of GDP was 27.6% as of 2015. Its maximum rate over the past 36 years was

recorded 43.7% in 2012, while its lowest value was – 0.5 in 1981. Even if there was an

upward saving trend, the savings were always insufficient to finance the volume of

required investment, i.e. existence of investment saving gap which made Bhutan to rely

gradually on outside resources to finance its capital budget. In general, major cause of

widened gap in saving-investment is the result of huge budget discrepancies incurred

by the government. Meanwhile, government continues to depend greatly on overseas

grants to finance its gap. Grants finance was around 36% of the total spending in the

fiscal year 2012-2013. The total outstanding public debt as a percentage of gross

domestic product (GDP) was 98.3% as of 30th June, 2015 (National Budget Report,

2015). This is because capital expenditure remains dependent on external financing.

While current expenditure was fully meet through domestic revenues in the medium

term. ODA or grants remains a necessary development input to Bhutan’s aspiration of

1 See Bhutan 2020 guide book

5

Gross National Happiness in the near future. However, all these achievements and

progression have been guided by many important documents like seasonal papers,

Bhutan vision 2020, Mid-term plans, Gross National Happiness guidelines and the

constitution of kingdom of Bhutan for its smooth development.

In every fiscal year, as prerequisite by Public Finance Act, 2007,

Ministry of Finance is accountable for total administration of financial supervision

through effective and efficient use of public resources. As commanded for maintaining

healthy fiscal and macroeconomics policies, Ministry of Finance coordinates, organizes

and publish government financial statistics. Publication of the Budget and

Appropriation Bill are done after it has been passed by the Parliament. The outline of

the presentation contains four types of budget summary namely Resources, Outlay

(capital and current)2, Fiscal Balance and Financing. These budget estimates are

presented by Ministry of Finance taking into consideration the total government

expenditure ceiling. The statement of budget is made and presented according to the

rule and regulation prescribed in Public Finance Act of Bhutan 2007. The fiscal frame

work of government for last five fiscal years is shown in table 1.2.1.

2 As mandated by the constitution and the fiscal policy of the

government, the current expenditure is fully financed from the domestic revenue.

6

Table 1.2.1

Budget Summary of Overall Financial Position for the Last 5 Years

Figures in Millions Nu3.

Items 2010/11 2011/12 2012/13 2013/14 2014/15

Total Resources 30,990.7 28,171.76 32,646.36 30,656.12 36231.05

Domestic Revenue 15,638.4 17,458.80 20,354.46 21,101.61 25141.03

i. Tax 9,655.78 11,593.49 14,676.93 15,403.12 18387.34

ii. non-tax 5,982.65 5,865.311 5,677.533 5,698.573 6753.70

Grants 11,118.9 10,497.73 12,501.52 9,562.636 9955.02

i. India 7,306.39 7,882.77 9,003.442 4,693.402 2125

ii. others 3,812.49 2,614.96 3,498.078 4,869.234 52.50

Other Receipts 4,233.37 215.235 (209.627) (8.210) 1135.01

Outlay 29,888.9 29,842.45 33,688.01 34,900.81 34334.26

Total Expenditures 25,831.8 29,521.92 34,842.76 36,527.82 36475.85

i. Current 12,902.6 14,735.08 16,705.65 18,096.55 21032.04

ii. Capital 12,929.1 14,786.85 18,137.12 18,431.26 15443.81

Net Lending (400.37) (906.605) (1,036.57) (739.889) (2552.8)

Advance/ suspense 334.728 1,227.133 (118.180) (887.117) 411.156

Fiscal balance 1,101.69 (1,670.69) (1,041.65) (4,244.69) 1896.80

Financing (1,101.7) 1,670.69 1,041.654 4,244.692 (1896.8)

Net Borrowing 81.986 293.970 (1,007.15) 492.306 (1086.4)

Borrowing 2,817.51 3,110.01 6,212.866 16,463.46 1685.27

Repayments 2,735.53 2,816.04 7,220.013 15,971.15 2771.68

Resource Gap 1,183.67 (1,376.72) (2,048.80) (3,752.39) 810.39

Source: Annual Financial Statement (AFS), Bhutan

The fiscal year 2014-15 ended with a fiscal surplus of Nu. 1896.80

million (1.5% 0f GDP) comparing to fiscal deficit of Nu.4244.69 in the previous FY.

The total resource realized was Nu.36231.05 million as against the total outlay of Nu

3 Ngultrum (Nu.) is the name of Bhutanese Domestic currency

7

34334.26 million for the fiscal year. The total expenditure during the FY 2014-2015

was Nu 36475.85 million which is about 29% of the GDP. The overall expenditure

increased by 5.4% from the previous FY due to the increase in the current expenditure.

The realized domestic revenue for the FY 2014-15 was Nu 25141.030 million (20.1%

of GDP) which is an increase of 8.2% from the previous FY constituting Nu.18387.32

of tax revenue. The increase in domestic revenue was mainly contributed by tax

measures introduced by the government during the fiscal year.

1.3 Gross Domestics Product by Broad Economic Sectors

The economic growth experienced in the last two and half decades has

brought about significant quantitative and qualitative changes in every sphere of human

activity; the primary sector, the secondary sector and the service sector. Primary sector

embraces Crops, Livestock and Forestry activities. Secondary sector embraces

manufacturing, electricity, water supply, and construction. Service sector embraces

hotels, restaurants, whole sale trade, retail trade, finance, insurance, transport and

communication, real estate, etc. Faster growth in Bhutan is escorted by an improvement

of productivity of the factors of production. Increased per capita capital stock,

technological improvement, an increase in the education achievements and health

standards have contributed with substantial rise in the productivity of labour in

particular and other factors in general.

Household consumption expenditure remained the principle constituent

of GDP growth in the 1980s accounting for nearly 85 percentage, subsequently

decreased to 43.3% in 2012. From being consumption-led economy, the growth is now

largely driven by capital expenditure. Capital accumulation was around 10.7% in 1980

but now it contributes more than half to the share to GDP growth amounting to 57.7%.

Thus, Government expenditure is a key constituent of national total income as seen the

expenditure method to measuring national outputs. This tells us that government

expenditure is a key element of the magnitude of the economy and economic growth.

For more detail see Bhutan’s national income aggregate presented in the table 1.3.1

below

8

Table 1.3.1

Aggregate Outputs of National Income.

Figures in Million Nu.

Year Consumption Investment Government X-M

Private Public

1980 768.78 248.40 86.61 248.36 -197.75

1982 910.33 316.93 192.85 294.09 -390.82

1983 1234.12 411.16 250.15 398.69 -473.45

1985 1562.92 502.78 431.50 504.91 -614.63

1986 1605.83 361.48 680.08 518.77 -518.10

1987 1765.49 395.19 800.71 570.35 -98.52

1989 2449.28 506.05 950.17 791.26 -274.02

1990 2643.50 715.93 836.35 854.00 -267.00

1993 3791.00 1794.50 1575.58 1178.50 -898.40

1995 3977.00 2708.12 1710.81 1773.00 -477.70

1998 8646.00 3085.51 3029.97 3039.00 -2537.90

2000 9415.96 6785.52 3080.14 4330.96 -3732.11

2001 10281.28 9802.00 3564.38 4841.13 -4824.54

2002 11415.07 11709.19 4095.70 5390.43 -6645.85

2003 12994.88 14258.22 2647.95 5919.54 -7330.20

2004 13806.72 16927.44 3235.99 6649.72 -9915.72

2005 14586.17 15131.55 3669.72 7911.51 -9460.87

2006 15553.70 13682.56 5189.53 8644.25 -1935.42

2007 19372.88 9619.55 6302.45 9454.77 -1150.83

2008 21761.78 16150.76 6729.17 10372.57 -5019.45

2009 27202.22 21231.70 7038.24 13082.07 -10715.53

2010 31752.11 33986.68 10373.30 14487.85 -20501.25

2011 34927.33 46124.75 11660.59 17047.84 -24874.52

2012 42690.24 50256.60 15996.22 18691.15 -23693.89

2013 53362.80 36275.41 13070.39 18274.46 -22988.64

2014 55486.02 58106.60 11802.84 20194.04 -25168.39

Source: National Statistical Bureau, Bhutan

9

In 2014, the structure of Bhutan’s economy was mainly contributed by

private investment and household consumption (see table 1.3.1). The total export

mainly relied on agricultural products and accompanied by electricity in the recent time.

Despite being agriculture-centered, the Bhutanese economy has

increasingly been dominated by secondary and service sectors over the decades.

Economy has experienced vast structural changes that are usually considered to be a

major feature of modern economic growth; a shift of economic undertakings from the

primary sector to the secondary and service sectors activities. According to United

Nations analysts, such shift in the economy is principally due to significant growth in

the hydropower and construction sectors that have not yet been accompanied by

dynamic growth and progresses in the manufacturing and industrial based sectors in the

country. In particular, the expansion of hydro-power projects has become powerful

driver of economic growth and is now main source of income, accounting for about

one-fifth of GDP in Bhutan and about 30 percent of total government revenues

(International Monetary Fund 2014).

The service sector, especially tourism sector, is also the key source of

economic growth in Bhutan. In 2014, the number of tourists visited Bhutan was around

155,121 with the gross earning of USD 71.04 million. International arrival make up

37.09% while regional arrivals constitute 62.91%. These achievements of

transformation was mainly due to modernization and globalization of the Bhutanese

economy. However, government on its cautious expansion of the tourism, encourages

only environmental friendly tourists.

Furthermore, GDP estimates at three broad aggregate levels: Primary,

Secondary and service sector is presented in figure 1.3.1. The contribution of each of

the sectors varied greatly over the years.

10

Figure 1.3.1

Share of different sectors to GDP

Source: Author’s computation, data from NSB4

Notice in the above figure, in 1991, the contribution of primary sector

was 40.9% to the share of GDP which was declined to 16.77% in 2014. On the other

hand, the growth of primary sector was recorded 2.37% higher over the previous year

in 2014. With the decline in the share of primary sector over the year, the share of

secondary and service sectors increased steadily from 30.6% and 28.8% in 1991 to

about 40.55% and 42.68% respectively in 2014. In fact, the contribution of service

sector was recorded as highest to the share of GDP in recent times. These contributions

comprised mainly of tourism and services related to tourism. Its share stood at 42.68%

of the GDP in 2014 as compared to 41.55% in 2013. Passing over the decades has seen

bigger range of structural dynamism. These changes is notably contributed by an

upsurge in the adeptness of utilizing the existing resources, an increase in the quantity

of existing resources and technological advancement and innovation.

4 NSB stand for National Statistical Bureau of Bhutan

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

50.0

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Per

cen

tage

sh

are

to G

DP

YearPrimary Sectors Secondary sectors Service Sectors

11

1.4 Annual GDP and economic Growth rate in Bhutan

Bhutan’s economic growth over the past three decades has averaged

more than a remarkable 7.0% until 2010 after which there was a decline in economic

growth, hitting a minimum of 2.14 percent in the fiscal year 2012-2013. However, the

economic growth was not consistent over the year. This challenges is due to High

trading costs lead to difficulties in diversifying the narrow economic base. Of the total

GDP, 27% is trade deficits and most of the export is hydropower.

The figure 1.4.1 depicts clearly that the annual real GDP was Nu

59240.01 million in the year 2015. The Gross Domestic Product worth of Bhutan

constitutes less than 0.01 percent of the global economy. Bhutan GDP averaged 0.67

Billion US dollars between 1990s and 2014, attaining to USD 873.22 million (Nominal

GDP=Nu.125880 million, 2015) in the year 2015 and USD 0.14 billion recorded in

1980 (World Bank).

Figure 1.4.1

Overview of annual GDP and economic growth in Bhutan

Figures in Million Nu.

Source: Author’s computation, data collected from NSB

0

10000

20000

30000

40000

50000

60000

70000

-5

0

5

10

15

20

25

30

35

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Rea

l GD

P (

Mill

ion

s N

u.)

Eco

no

mic

Gro

wth

YearEconomic Growth (G%) Real GDP

12

Given a small size of the market and limited natural resource base,

Bhutan’s economic growth has primarily been driven by hydroelectricity, construction

and tourism sectors. Bhutan was identified as the second fastest-growing economy in

the world in 2007 (World Bank, 2007). This was mainly due to the commissioning of

the gigantic Tala Hydroelectric Power Station. The variance in growth rate over the

year was due to the high proportion of economic output pertaining to the hydropower

sector. And also the volatility of output in Bhutan is the result of highly non-diversified

economy that is comprised largely of the capital-intensive. Foreign direct investment is

not yet officially operationalized. Therefore, complicated controls and ambiguous

policies on industrial licensing, trade and commerce, migrant labour, and finance

continue to hinder foreign investment strategies and economic growth in general.

1.5 Trends and Composition of Government Expenditure in Bhutan.

The system of modern public finance in Bhutan is of very recent origin.

Ministry of Finance presented the first budget on contemporary lines in 1971. It was

called the Civil Budget as it covered the needs of the Ministry of Finance, Home affairs

and Agriculture and so on. The requirements of development oriented Ministries like

Communication and information, Trade and Industry, Foreign Affair were provided

under a separate development budget administered first by the Development Secretariat

and then by its successor, the Planning Commission. With the commencement of the

First Five Year Plan in 1961, the classification of the government budget into Civil and

Development was replaced by the concept of Maintenance and Development

Expenditures. Maintenance or Current Expenditures reflected mostly the current or

consumption expenditures of the government while development expenditures were

identified largely with the expenditures of the government on fixed capital formation.

The Royal Government of Bhutan has given almost equal priority to both capital and

recurrent expenditures in terms of budget allocation. Free education system, health care

facilities and frequent increase of civil servant salaries made current expenditure rise

up faster and because of rugged mountains dominated the terrain, made building of

roads and other infrastructure difficult. While planning its total expenditure, each sector

13

of the economy, depending on requirements, receives their own share of money.

Mostly, current expenditure of the country was meet through domestic revenue and

capital expenditure from external sources.

The trend and composition of public expenditure as total expenditure,

capital expenditure and current expenditure are presented in figure 1.5.1. These

expenditure are based on constant price.

Figure 1.5.1:

Trend of Public Expenditure Growth in Bhutan

Source: Author’s computation

From figure 1.5.1, the total public expenditure displayed an increasing

trend in most of the year since 1985, by the year 2008, the amount of total public

expenditure expanded more than four times. In 1985 it was Nu.3498 million. In 2015

the expenditure folded 8 times higher than 1985. The budget for 2013-14 projected a

decline of nearly 9% in nominal spending compared with the revised budget for the

0

5000

10000

15000

20000

25000

30000

35000

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Go

vern

men

t Ex

pen

dit

ure

s

Year

Figure in millions Nu.

Capital Expenditure Current Expenditure Total Expenditure

14

previous fiscal year, 2012-13. This is because of the shortage of rupees (Indian currency

reserve). The government has tightened the country's expenditures to bring it in line

with the available resources. Another reason is the slow start of the budget year

following elections, the change of leadership, and delays in foreign grant

disbursements.

The link between planning, allocation and policy of public resources has

been strengthened through the Medium Term Review expenditure framework (MTR).

The purpose of the Medium Term Review assess the improvement of Plan in the first

two fiscal years of the five years plan period and identify issues that are likely to hamper

the successful implementation of the plan. This is intended at providing opportunities

for next three years of the plan period to use resources efficiently.

1.5 Composition of Government Spending by Agencies (Ministry)

With the infusion of modern financial system, government have created

different departments (Ministries) to look after different sectors of an economy. It has

eight Ministries until 1999 and created two additional ministries, totaling to 10

ministries in fiscal year 2000. The old Health and Education Ministry was segregated

into two different ministries, which makes two additional Ministry, namely, Ministry

of Health and Ministry of Education. Furthermore, Ministry of Labour and Human

resource and Ministry of Work and Human Settlement were additional new ministries

created making 10 ministry at present. So, today there are 10 Ministries in Bhutan to

receive their share of budget every year. All these 10 ministries (departments) receives

their own share of fund depending on request with maximum ceilings.

These departments (Ministries) are important components of public

expenditures allocations, which reveals public spending priorities. The public

expenditure strategies in Bhutan has focused their efforts on the affordability of the

current levels of public expenditure in which less emphasis has been given to where the

public fund is actually invested.

15

The government still faced big challenges in making a good choice

regarding the composition of its expenditure allocation in each sectors of Ministries.

However, each departments gets its annual budgets depending on availability of

resources and its priorities.

The table below gives quick glimpse of the allocation of public

expenditure by Ministries for the year 2010 to 2015.

Table 1.5.1

Classification of government expenditure by agencies (Ministry)

Figures in millions Nu.

Ministries (Agencies) 2015 2014 2013 2012 2011 2010

Agriculture and Forest 2737.2 2600.6 2570.3 2082.6 1787.3 1788.3

Infor. and Communication 917.62 698.3 1324.5 1583.6 1182.9 518.4

Economic Affairs 794.09 701.6 774.2 869.1 1890.3 1048.2

Foreign Affairs 555.8 566.7 537.9 639.6 416.2 353.2

Home and culture 2141.4 1765.1 1914.2 1957.9 1580 1305.4

Education 1798.7 886.8 1312.3 1124.1 729.1 798.5

Health 1526.4 1443.8 1799.8 1674 1422.4 1357.1

Finance 6180.6 7973.8 5829.8 4946.8 3928 3787.3

Works and Human

settlement

4273.1 4027 4664.7 4072.6 2776.6 3135.7

Labour and Human

Resource

515.4 427.6 421.9 465 343.6 324.6

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

Table 1.5.1 shows the division of public expenditure amongst different

departments (Ministries). Expenditure data shows that Bhutan allocate a relatively

larger proportion of its available resources on Ministry of Finance, Work and Human

Settlement, Agriculture and Education. Economic Affair and Foreign Affair

expenditures amongst all departments show relatively smaller proportion of resource

allocation. Ministry of finance received highest spending since it deals with debt

16

management, civil servant salaries and so on. As mentioned earlier, the fall in

expenditure share in 2014 for some departments as compared to 2013 was due to

election and delay in received of external budget such as grants. In general, economic

and public services have been given the highest priority. This area includes agriculture,

housing and community, mining and manufacturing, communication, energy and road.

Similarly, social service such as health and education also receives huge share of

expenditure. This disbursement of revenue is organized in accordance with public fiscal

policy on the grounds of equity verses efficiency to achieve desired target.

1.7 Statement of the problem

The impact of public expenditures on economic growth needs to be

considered in newly emerging countries, especially in those countries anguish from

high poverty, unemployment, humble exploitation of existing resources, and the

hastened rates in budget deficit as a percent of the GDP’s of these countries. Bhutan is

one of them. Bhutan continuously suffer from a negative fiscal balance in the general

budget and a decline in the balance of payments, which confines its ability to stimulate

economic growth and delays critical development investment and the full achievement

of Millennium Development Goals and Bhutan’s vision of 2020 goals. The fiscal deficit

widened significantly in the fiscal year 2010/2011 reaching 4.8% of GDP, compared to

a surplus of about 1.7% in the fiscal year 2009/2010. This was mainly because of an

escalation in capital spending on infrastructure set-up coupled with sluggish in

revenues. The total outstanding public debt (internal and external) as of 30th June 2014

was accounting for 98.3% of GDP.

Nonetheless, Public expenditure in Bhutan has grown tremendously

over the years despite the government efforts to rationalize expenditure through

downsizing and other budgeting measures. Unfortunately, increasing expenditure has

not transformed into dynamic growth and development, as Bhutan is still a least

developed country (UNCTAD, 2014). As a result, the government is faced with hard

choices when undertaking public expenditure cuts since the question of which

departments of public expenditure should be reduced; whether Culture, Education,

17

Infrastructure or Agriculture depends on the role of these agencies to growth. Thus,

there is a cause of concern to policy makers on the implications of such expenditure

cuts to economic growth. Consequently, this research try to inspect the different

components of public spending in Bhutan and how they influence economic growth.

The finding from this paper will help the planner or the policy makers in prioritizing

most scared and limited public resources so as to achieve optimal economic growth

through budget rationalization.

1.8 Objectives of the study

The main objective of this study is to investigate the impact of public

expenditure on economic growth in Bhutan, focusing on the various components of

government spending. Specifically, the study seeks to answer following two questions:

1. What is the relationship between public spending and the economic

growth in Bhutan?

2. What are the most important components of public spending that

contributes on an economic growth in Bhutan?

1.9 Limitations, Scope and Organization of the research

This research have many shortcomings. One of the main limitation is the

reshuffle of Ministries in the fiscal year 20005, so collecting relevant data and choosing

main components or sectors in the study introduced big hurdles. Owing to the limited

availability of data, we could not include the most important sectors such as education

and health. The other obstacle is that no studies has conducted so far in relation to real

GDP growth and government expenditure in Bhutan. Therefore, referencing the

relevant literature posed further challenge. Thus, the study mostly used annual

documents like national statistical year books, seasonal papers besides many other

international journals and books.

5 See section 1.5 for more details.

18

Considering the limitations mentioned above, the study will focus on the

main four components of government spending which are Agriculture and Forestry,

Information and Communication, Economic Affairs and Foreign Affairs. This research

is ordered into five different chapters. The theoretical and empirical literature is

reviewed in the next chapter. Research design and methodology is outline in the chapter

three. Chapter four comprises of analysis and discussion of the finding. Conclusion and

recommendation are shown in chapter five.

19

CHAPTER 2

LITERATURE REVIEW

2.1 Theories explaining the relationship between public expenditure

and economic growth

There exists an extensive disagreement among planners regarding the

impact of increase in public spending on achieving economic growth. Government

expenditure includes all kinds of government consumptions, investments and transfer

payments made by a nation. Government spending can be financed by taxes,

government borrowing and foreign aids. Every country around the world tries to

maximize GDP growth rate by increasing government spending.

The issue of economics is best explained by Adam Smith in his book

“Wealth of Nation”, his incredible book published in 1976. Only examining the

economic growth can assist in identifying the cause why some countries are prosperous

and others poor. Many growth theories of deal with the long-run movements of an

economy (Branson, 2002). It states the features which affects economic growth over

time and analyzes the factors that permit some nations to grow very quickly, few gently

and others remain stagnant. In general, in many developing countries, national spending

has maintained a very crucial part in sinking district gaps through use of social services

activities, development of infrastructural amenities in connection to road and

telecommunication services, growth of commerce, health, education, training and so

on.

There are many well-known economic theories which elucidate the

impact of public expenditure on economic growth which also provides a solution in

order to redistribute available income or resources on most productive sectors.

20

2.1.1 Keynesian Theory

In the nineteenth century, economists commonly advocated a nation

with minimal economic function. This was a reaction to failures in the eighteenth

century due to heavy government alterations (Schuknecht, 1995). At the end of world

war 1, the perception about the function of government has changed quickly due to the

great influence of J.M Keynes who argue that the government still had many things to

do which were not yet been done.

The early step of the Keynesian uprising took place in the years after the

publication of Keynes' General Theory in 1936. The theory was based on spending in

the economy and its effects on output and inflation. Its analysis arrives at the conclusion

that aggregate demand managing procedures can be employed to boost economic

performance as demand is a prerequisite for growth. Harrod and Domar are the first to

develop macroeconomic model to formally analyze the problem of growth. Their

growth equation is the dominant model in the Keynesian framework which gives some

intuitions into the dynamics of growth. The model states that investment, saving,

technical progress and population growth as the main foundations of growth but

production is obtained only by means of labour and physical capital. So they focus in

goods market which assumes saving is identical to preferred investment.

The New Keynesian models argue that an expansion in government

expenditure increases demand and thus creates more economic activity that is output

through multiplier effect. He believes that aggregate demand is influenced by a host of

economic decisions, public and private and sometimes works both intermittently

(Blinder, 1986). This theory also suggests that fluctuations in total outputs, whether

expected/unexpected, have its paramount short period consequence on real income and

occupation (Blinder, 1988). Hence, an increase in the government expenditure is likely

to reduce unemployment and lead to increase profitability and investment through

multiplier effects on aggregated demand (Urban & Nordensvard, 2013). Subsequently,

Keynesian hypothesis is just opposite to the classical economist’s view in relation to

government expenditure and economic growth. The classical economists argue that

only final output will boost when there is an expansion in government spending. They

found that total expenditure as destabilizing mechanism on the development of an

output rather than dynamic force of economic growth as the Keynesian economists have

21

proposed. On other hand, Classical economists view in invisible hand to initiate full

employment equilibrium in the economy. Also they believe in government intervention

in the economy is not required because of the assumption that the invisible hand is the

best guide for the economy.

The new Keynesian models also argue that increase in government

expenditure will lift total output through crowding in effect. In contrary, increase in

government spending may also result in crowding out of private sector but if

government cut expenditure there may be decrease in private investment (Mudaki &

Masaviru, 2012). Keynes (1964) suggested that government expenditure should create

employment opportunities and exploit resource capital that has been underutilized

during the time when an economy is in a recession with high level of unemployment of

labor and capital. He believes that a severe down turn in economic activities may never

come to end if there is no government intervention. (Mitchell, 2005) stated that

government can improve economic declines by borrowing money from the private firm

and then returning the money to the private sector through various spending programs.

Barro (1990) argued that increase in expenditure will enhance output growth in the long

run. He demonstrated using Cobb-Douglas framework and viewed that government

expenditure has both steady state growth and output growth. Thus, it is clear that the

Keynesian views that public consumption affect the economy positively while the

classical economists assert that the effect is temporary since long run adjustment of

prices lead to optimal output and employment levels (Ocran, 2009).

Keynesian theory also states that spending of the government would

contribute immensely on economic growth. So, an increase in the government final

expenditure is likely to result in an up rise in employment, investment and productivity.

It means that government spending supplements increase in final outputs, escalating

that an additional output depended on expenditure multipliers effects. On the other

hand, opponents of this view stipulate that government consumption expenditure give

less room for private investor and adversely effects the short run growth and reduces

innovations in the long period (Diamond, 1989). Therefore, in Keynesian theory,

government expenditure is necessary to enhance economic growth. However,

Motivated by private sector and political parties, the government may misallocate

available limited public resources.

22

2.1.2 Classical Growth Theory

The groundwork of classical economics was laid by Smith (1723-1790) and

later evolved to its complete body in the nineteenth century. Featuring the process of

economic growth was the main idea in the work of the classical writers namely, Adam

Smith, Ricardo, and Malthus. Accordingly, it was felt the objectives of analysis to

identify the forces in the nation that promoted or deterred the economic development

and to provide a basis for policy and action to influence those forces (Harries, 1975).

The conventional theories of Smith and Malthus outline economic growth in terms of

immobile properties and growing populace. The supply of free land will ultimately

finish with an increasing number of population in case of absence of technological

changes. When available land became little to work then the marginal product of each

worker will also become lesser which will entail the decline in the reservation of real

wage. Malthusian equilibrium arises if real wages declines to the lower level, below

which the supply of labor will not produce outputs by itself. However, classical theorists

fail to consider the reality that technological change has retained economic

development continuing in industrial countries by persistently increasing the

productivity of labour onward (Samuelson & Nordhaus, 1989). In fact, the foundation

for classical growth model was laid by Adam Smith. He is one of the first economists

to develop a supply side driven growth model as a function of,

Y = f (L, K, R)

Where Y, L, K and R were output growth, labour supply, capital employed and land

respectively. Hence, the growth of output is the function of growth of land, labour and

capital and increase in overall productivity as highlighted below:

𝑔𝑌 = 𝑓(𝑔𝑃, 𝑔𝐾, 𝑔𝐿 , 𝑔𝑅),

Where small ‘g’ refers to the growth rate of all individual factors of production. In line

with this reasoning, Smith claimed that growth was self-enforcing as it demonstrates

increasing returns to scale. He explained economic growth endogenously, admitting

that the speed of output growth be contingent on the decisions and actions of every

23

agent with regard to saving-investment behaviors and innovations. Subsequently,

special focus is placed on the endogenous creation of new knowledge. New knowledge

and labour power is regarded as goods, which is in the long period tending to become

public goods. Diminishing returns to scale due to limited natural resources was

compensated by the increase in productivity due to the division of labor and

specialization.

To sum up, the conventional economists believed in an unseen hand, self-

interest, and a self-regulating economic system, as well as in the growth of monetary

institutions, capital accumulation and free trade. They also believed in division of labor and

specialization, the law of diminishing returns, and the ability of the economy to self-adjust

in a laissez-faire system lacking of government intervention. Malthus provided a new

dimension to Smith’s doctrine of growth by incorporating issues of population growth.

Classical economics logically leads to the creation of a capitalistic economic system.

2.1.3. The Neo-Classical growth model

The Neo-Classical growth theory is an economic theory that outlines

how a steady economic growth rate can be achieved. The theory suggests that

technological innovation takes central power on nation’s economy. It state that

economic growth will not have continuous progresses without better technology. In the

neo-classical theories, growth is measured in three different ways; increase in capital,

labour supply and productivity.

Robert Solow and TW Swan added labour in the production and capital

to output ratios are not fixed as they are like in Harrod function. According to Solow

model saving and growth of population rates are three central components of economic

growth. The function state that higher degree of investment leads to addition of higher

capital and output per individual worker. However, huge population growth creates

adverse effect on economic growth. It is because a higher fraction of saving in the

economy with high population growth has to maintain constant capital and labor ratio.

Hence in the absence of technological innovation and changes, an increase in capital

per each worker would not correspond to relative increase in output per worker because

of diminishing returns. Hence adding capital would diminishes the rate of return on

capital.

24

The main idea of Solow model is that the accumulation of physical

capital cannot account big growth in output per person over a time. The model

anticipated technological innovation and changes to grow at constant ‘steady state’

output growth. Other prediction of the model is that the growth may experience before

steady state output because growth slowdown and ceases as they approach to steady

state. This suggests that least developed countries with a lower value of capital and

output grow faster than rich countries and consequently the poor countries tend to catch

up with the rich countries.

In the Solow growth model, if an expansionary fiscal policy is continued

to adapt then the long-term consequences of growth may be a lower level of steady state

GDP. The intuition behind is that the government in budget deficit drives a wedge

between private saving and investment, as the government collects part of private

saving to finance the deficit. When this end up in lower saving being available for

private investment then it will lead to lower capital stock accumulation and lower steady

state GDP growth. Nonetheless, if government runs in deficit balance in order to finance

public investment on infrastructure and amenities, the negative effects could be reduced

on steady state income (Leach, 2002)

2.1.4 Endogenous Growth

Most endogenous growth models, principally the AK model and Lucas

(1988) model, stated that the higher domestic investment rate exerts a positive effect on

the economic growth rate in the long run. The endogenous growth model suggests that

economic growth is generated from within a system as a direct result of internal

mechanism. In brief, the theory state that the improvement of a country's human

resources will lead to economic growth by innovating new systems of technology and

efficient means of production. Additionally, Endogenous Growth model provides the

fact that to rise productivity; the work force must persistently be improved with

abundant inputs such like physical, human and knowledge capital. Thus, growth is

pushed by the capital accumulation and it is the outcome of private investment. The

endogenous growth model explains the association between government spending and

economic growth where public expenditure composition is taken as one of the

determinants of economic growth (Sanz & Velazquez, 2001). Within the endogenous

25

growth model, governments make policies aimed at improving the resource allocation

where market forces have failed to improve. The model makes a distinction between

nonproductive and productive public expenditure whereas productive public

expenditure is believed to be critical in complementing private sector production

(Barro, 1990). It means that the best way a government can affect economic growth in

the long run is through greater investment in human resource, health and education and

research and development.

Endogenous growth models consider public spending by linking it with

the economy‘s long-term growth rate (Devarajan, et al., 1996). Further, economic

forces explain the positive relation between technological progress and the

accumulation of human knowledge.

2.2 Review of Existing Empirical Evidence.

Many researchers already tried to find out the association ship between

government expenditure and economic growth around the glove. In the past empirical

studies, existence of relationship (Ram, 1986) explained about total government

expenditures and economic growth while others found public expenditure is negatively

linked with growth (Landau, 1986) and yet some have found insignificant relation

between public spending and economic growth (Kormendi, 1985). A study by

Aigheyisi (2013) using 32 years’ time series data establish that total expenditure and

current expenditure showed positive impacts on GDP growth which was also

statistically significant in long term.

In most of the unindustrialized countries, many research focuses on

examining the part of public investment in the context of growth. There is believe that

bigger investment in infrastructure and human resource accumulation can promote long

term economic growth of a nation. This types of investment will also encourage private

sector participation and enhance productivity. According to Khan and Kumar (1997)

on their study on relative return between public and private investment amongst 95

emerging countries, they found that private investment has more impact than public

investment on growth. However public investment provide complimentary to private

investment. However, low income country will feel greater return from investment than

26

high income country. Alshahrani et al. (1997) using VECM in Saudi Arabia conformed

that public investment has potential to boost long run economic growth.

Albatel (2000) studied the association ship between government

expenditure and economic growth in Saudi Arabia: The study states that government

expenditure exerts positive impact on economic growth. A study conducted by Dandan

(2011) found that the total government expenditure has positive impact on GDP growth

which is also consistent with the Keynesian's theory of fiscal policy. Similarly,

Gemmell, Kneller &Sanz (2015) used multiple regression models in Nigeria for the

period of 1970 and 2011. They have concluded positive relationship in the long run

between public expenditure and economic growth in Nigeria. Also, (Al-Obaid, 2004)

analyzed the long run relation between government expenditure and real GDP where

findings showed statistically positive long run relationship between share of

government expenditure and per capita income. Recently, Lahirushan and Gunasekara

(2015) studied using panel data amongst nine Asian countries using co-integration

technique; fixed effects and Causality test (These countries include China, Japan, South

Korea, Singapore, Thailand, Malaysia, Sri Lanka, India and Bhutan). The empirical

findings showed significant positive impact of government expenditure on GDP growth

in Asian region. Seemingly, government expenditure and economic growth revealed a

long-run relationship in Asian countries and found that there is a unidirectional

causality flowing from economic growth to government spending and government

spending to economic growth in Asian countries. These findings, in general, meet the

expectation of outcome of public spending on growth. In reality, every emerging or

industrialized country expects positive results of their spending on nation’s growth. In

contrary, Alshahrani & Alsadiq (2014) estimated using system equation model and

states that economic growth is positively related to private domestic and public

investments in the long run. Larger Spending on building houses can also lift short term

economic growth. However, some other economist like Barro (1990), he stated negative

impact of public expenditure on economic growth. In addition, Devarajan (1996) also

observed that government capital expenditure has negative relationship with per-capita

growth.

A few number of studies has also focused attention on causality between

government expenditure and growth. Lai and Cheng (1997) conducted study in Korea

27

applying a VAR econometric technique. They have concluded bi-directional causal

relationship between government expenditure and economic growth exists. Aigheyisi

(2013) also found bidirectional causation between total expenditure, capital expenditure

and GDP. It means causality runs from both the directions in Nigerian economy. A

recent study by Lui et al. (2008) on causality between gross domestic product & public

spending in United State, the study confirmed that government expenditure cause

growth of GDP. However, the growth of GDP does not cause expansion of government

expenditure. Similarly, Loizides & Vamvoukas (2005) examined if the relative size of

public total spending in GNP Granger cause the rate of economic growth by employing

the trivariate causality test using data set on Greece, United Kingdom and Ireland. They

have found that government size granger causes economic growth rate in all the three

countries. And also, economic growth granger cause public expenditure for Greece and

United Kingdom when they add inflation in the data set. It is also clear that the statistical

results were true for the United Kingdom and Ireland both in the long run and short run.

Similar type of studies was piloted by Bader and Qarn (2003) to state the causality

between growth and expenditure in three different countries. They confirm that the

government expenditures and economic growth reveal negative relationship from both

the direction in Israel and Syria and one sided negative short run causality running from

economic growth to government expenditure in Egypt. In similar way Ebaidalla (2013)

using Granger causality test in Sudan for the period of 1970 to 2008 found that the

government expenditure can cause national income but not national income causing

expenditure growth. This result also propagates the support of Keynesian proposition

of public spending stimulating economic growth.

In the recent times, the association ship between different departments

of expenditures components and economic growth has received a lot of attention

amongst researchers. For an instant, as per the finding of the effect of different

components of public expenditure on growth is concerned, (Devarajan, 1996) stated a

positive and significant association ship between current expenditure and real GDP and

negatively significant association ship between capital components spending and real

GDP for 43 countries. The study conducted by Ghosh and Gregoriou (2008) in 15

developed and developing countries confirms that current public spending has

positively significant effect on the growth while capital spending has adverse but

28

significant effect with growth. In contrary, statistically insignificant estimated results

was also confirmed by Chamorro-Narvaez (2012) and Al-Fawwaz (2016) between

development expenditure and growth in Jordan. On the other hand, (Nurudeen &

Usman, 2010) in Nigeria stated that development expenditure, current expenditure and

government expenditure on human development have an adverse impact on economic

growth. Similar idea is also evident from Nworji, Obiwuru, Okwu and Nworji (2012)

in which case they found that government capital expenditure was inversely related

with economic services. But government expenditure on transport and communication

and health resulted positive impact on economic growth. On the other hand (Joharji &

Starr, 2010) examined using annual time series data to find the relationship between

development and maintenance expenditures between GDP in Saudi Arabia. They

confirmed that increase in government spending on current expenditure have greater

positive impacts on economic growth than capital expenditure. On contrary, a study in

Gulf Cooperation Council (GCC) by Espinoza and Senhadji (2011) confirmed capital

expenditure has larger impacts. Maingi (2010) stated the impact of public spending on

real economic growth using annual time series data for the period 45 years in Kenya.

Researcher applied Vector Auto Regression (VAR) estimation technique. The findings

argued government spending on education and infrastructure enhances growth in the

long run. In Similar way, Ashaure (1989) examined the link between aggregate outputs

and some government spending variables in the United States over the period 1949 -

1985. It was found that expenditure on electricity and gas supply, highways and streets,

mass transit, water and sewage system displayed influential positive significant on

growth.

Recent study by Musaba, Chilonda and Matchaya (2013) using VECM,

found that sectorial government expenditure related to education, health, agriculture,

defense, social safety and transportation and communication has insignificant

relationship on economic growth in short run. However, the long run results postulated

that government expenditure on agriculture and defenses has significant positive

impacts on economic growth. Spending on agriculture was potentially strong in

promoting economic growth (Fan, Yu & Saurkar, 2008). In contrary, Saad and

Kalakech (2009) used the same method and concluded that government educational

expenditure of its citizen confirmed positive relationship to economic growth in the

29

long period and adverse association ship in the short period of time and agriculture

expenditure and defense has a negative impact on economic growth during the long

period and insignificant impact during the short period of time.

In the empirical findings it was noted that public expenditure on

education is positive significant determinant of economic growth while spending on

security reason were seen to be insignificant to drive economic growth (Mudaki &

Masaviru, 2012). Increased expenditure on agriculture showed significant but

negatively related to economic growth. It was also clear from the study that expenditure

on economic affairs, transport and communication were also significant but weakly

related to economic growth. Similar idea is also evident from (Vu, 2005), where

telecommunication network are very responsive to growth. Erhan (2012) also

concluded that information and communication paly very important role in promoting

economic growth. Amasoma et al (2011) in Nigeria, using same method for the period

ranging 1970 to 2010 found that expenditure on agriculture was strongly significant to

economic growth and spending on information and communication, education were

prove to be insignificant in short and long period of time. On contrary, Musibau &

Rasak (2005) found that education prevails long run relationship to build a nation. In

case of infrastructural expansion Albala et al. (2001) argued positively significant

association with economic growth.

Similarly, ARDL estimates in Nigerian economy reveals that forestry

expenditure promotes growth while spending on education, transport has neutral impact

on long term growth. For the short period, these sectors were insignificant and also

government expenditure on defense retards the economic growth (Aremu et. al, 2015).

However, ARDL test result found out by (Egbetunde & O Fasanya, 2013) in the same

countries using time series data (1970 to 2010) contradicts with the above finding in

which the researcher proclaims that the frameworks are bound together conforming

significant long run relationship.

Lastly as highlighted in the review above that some researchers believe

that government involvement in the economy will bring economic growth while others

strongly opposes believing that government involvement in activities inherently is

inefficient and bureaucratic which deter economic growth. Yet some studies still view

30

that government spending was indeterminate of economic growth (Najkamp & Poot,

2002)

While economic theory does not provide clear cut solution to the debate

of how different constituents of government expenditure affect economic growth. On

the other hand, empirical evidence provides conflicting results in this regard. Therefore,

more empirical analysis is required to capture the relationship between economic

growth and different components of government expenditure to bridge the research gap.

Especially, to situate the study within the context of particular economy would

determine the phenomenon specific to where the study is conducted. In Bhutan, having

no such study being undertaken, this study would add to the literature on the issue from

the Bhutanese perspective.

Furthermore, although there are many theoretical and empirical

literatures available around the world with regard to impact of different components of

public expenditure on economic growth but the researches lack to find the same for

foreign affairs and tourism. In fact, no research has been carried out in this field in

Bhutan. Therefore, this paper aims to add foreign affair to extend the study on the

influence of public expenditure on real GDP growth in Bhutan.

31

CHAPTER 3

RESEARCH DESIGH AND METHODOLOGY

3.1 Theoretical Framework

The theoretical framework designed in this paper is based on Keynesian

theory and endogenous growth theory constructed by Barro & Sala-i-Martin (1992).

Firstly, Keynesian theory help us to model short run relationship between government

expenditure and real GDP growth. It states that government expenditure will boost

economic growth in a short run. For instance, during economic downturn a policy of

budgetary expansion will increase or help to stabilize short run fluctuation in economic

activities (Ju-Haung, 2006). Keynesian confirmed how the government can adjust the

budgetary and monetary policy to avoid severe slump that happened in the 1930’s. Thus

following Keynesian theory, the model expresses economic growth (GDP) as a

dependent variable which is a function of government expenditures. Here, Jerono

(2009) defined gross domestic product as

RGDP=f (government expenditure) (1)

The mechanisms through which public spending may affect GDP

growth rate relates to the government capacity on dealing with goods and services that

increases the aggregate final demand in the economy. The basic concept of growth

implies periodical change in output from periodical changes in inputs (Banister, 2000).

Thus public expenditure changes over a time creating change in output.

The second model relates to long run relationship. According to neo-

classical theory, fiscal policy helps to determine the output level rather it failed to state

steady state economic growth rate. However, Barro (1990), Barro and Sala-i-Martin

(1992) and Mendoza et al. (1997) provides a theoretical as well as empirical evidence

supporting that fiscal policy does affects both the output level and steady state economic

growth rate. Model of endogenous growth by Romer (1986), Lucas (1988), Barro

32

(1990) and Rebelo (1991) also confirmed the government participation in the growth

process. The key message of the endogenous growth model with government fiscal

policy is that higher taxation explicitly decreases output. However, that unambiguously

decrease of output may be counterbalance by using proceeds for productive spending

(Barro, 1990).

Barro and Sala-i-Martin (1992)6 used the modified Cobb-Douglas

production function to establish the persistence influence of fiscal policy determinants

on economic growth. The production function takes the following form:

𝑌 = 𝐴𝐾1−𝛼𝑔𝛼 (2)

Where, 0 < 𝛼 < 1. Y represent for per capita output, K represent per capita capital, g

represents per capital input provided by the government and A represents total factor

productivity level.

Now assuming that the budget can be balanced through increase in

lump-sum tax (LST) and proportional tax (𝜏). Consider there are n producers in the

economy. Each producer produces output yi. Therefore, the budget constraint is written

as:

𝑛𝜏𝑦 + 𝐿𝑆𝑇 = 𝐶 + 𝑔𝑛 (3)

In the above equation (𝜏) represents distortionary taxes which influence the saving-

investment decision of the household (private agents). LST are the non-distortionary

taxes which never affect the saving and investment decision of the individuals. C is the

unproductive government expenditures. It defines those expenditures which are

included by private agents in their utility function. g represents for productive

expenditures and it incorporates those expenditures which are included in private

6 See details study of how fiscal policy influence economic growth in the

work of Barro and Sala-i-Martin (1992, 1995).

33

agent’s production function. Accordingly, from the above specification of utility

function, Barro and Sala-i-Martin (1992) derived the long run growth rate as:

Ψ = 𝜆(1-𝜏)(1-𝛼)𝐴1

(1−𝛼)(𝑔

𝑦⁄ )𝛼

1−∝-𝜇 (4)

Where (λ & μ) are the parameters in the supposed utility function. Equation (4) above

shows that distortionary taxes (τ) and government productive expenditure (g)

respectively will have either negative or positive impact on economic growth. However,

indirect taxes (LST) and government unproductive expenditure (C) have neutral impact

on long run growth rate. Hence, the supposition of balanced budget is impractical

particularly in the emerging countries like Bhutan, thus the equation (3) can now be

improved as:

𝜏𝑛𝑦 + 𝐿𝑆𝑇 = 𝐶 + 𝑔𝑛𝑦 + 𝑓 (5)

Where f constitute for surplus or deficit budget in a given period. g is predicted to be

positive as g is productive, but (𝜏) is negative as it distorts private agent’s incentives to

invest. Both LST and C are anticipated to have zero effects on equilibrium growth.

Henceforth, we will follows the growth formula of Kneller et al. (1999) to determine

the impact of fiscal policy on economic growth. They have empirically tested the public

policy endogenous growth model and predicted that composition of taxation and

government expenditure will affect the steady state growth rate7. They specified

economic growth as a function of some fiscal and non-fiscal variables. Now the

equation is written as

Ψt = 𝛽0 + ∑ 𝑀𝑖𝑡𝛽𝑖𝑘𝑖=1 + ∑ 𝑍𝑗𝑡𝛾𝑗

𝑚𝑖=1 + 휀𝑡 (6)

7 However, they used 26 years panel data for 20 OECD countries, which

is from 1970 to 1995.

34

Where Ψ represents real GDP growth, M represents vector of fiscal policy variables

(government expenditure variables), Z represents vector of the non-fiscal policy or

control variables and 휀𝑡 is the random error term.

3.2 The Econometric Model and Estimation Technique

For the purpose of estimating effects of the composition of government

expenditures equation (7), (8), (9) and (10) will be used. This setting will be done by

transferring equation (6) into logarithmic form in order to help the analysis using linear

regression model. This type of idea is also evident from Barro (1990), where he

confirmed the difference between productive and unproductive expenditures by how

they affect the aggregate production function of the economy. Empirical literature has

underlined the distinction between productive and unproductive spending, say,

Devarajan, et al, 1996). This study targets on the link between various components of

government expenditure and economic growth without pre-judging which components

should be productive or unproductive. Similar idea is also confirmed from Barro &

Sala-i-Martin (1992), where government fiscal policy have greater importance on

growth.

The main goal of this research is to find out the relationship between

components of government expenditure and real GDP growth in Bhutan. And also to

find out which components of government expenditure contribute better than other.

Eventually, we will first analyze the effect of total expenditure, capital expenditure and

current public expenditure on real GDP growth than we will pin down our focus

exclusively on components; expenditure on Agriculture and Forest, Information and

Communication, Economic Affair and Foreign Affair. For this purpose, we separated

our model into four equation. First three models (equations) consists of total, capital

expenditure and current expenditure with gross capital formation and tourism revenue

as control variables. Second model take into account of four components of government

expenditures.

Econometrically, the set up to investigate the relation between

government expenditure and economic growth follows the empirical study of Ghosh,

S., & Gregoriou, A. (2008) and Bose et al. (2007) as these studies were applicable to

35

my study. However, the current study includes some additional variables of government

expenditure like government expenditure on foreign affair, and capital Formation and

revenue from tourism as a control variables as

Model 1A.

The first regression model is the linear regression between real GDP

growth and total government expenditure (TExp) with gross capital formation and gross

revenue from tourism being control variables. The equation is given below:

Model 1A

𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛽0 + 𝛽1𝑙𝑛𝑇𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (7)

Model 1B.

This linear regression model is the relationship between real GDP

(RGDP) and total current expenditure (CRExp). RGDP is the dependent variable and

CRExp is the explanatory variable with gross capital formation and revenue from

tourism as a control variable.

𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛿0 + 𝛽1𝑙𝑛𝐶𝑅𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (8)

Model 1C.

This linear regression model is the relationship between real GDP

(RGDP) and total capital expenditure (CAPExp). RGDP is the dependent variable and

CAPExp is the explanatory variable with gross capital formation and revenue from

tourism as a control variable.

𝑙𝑛𝑅𝐺𝐷𝑃 = 𝛿0 + 𝛽1𝑙𝑛𝐶𝐴𝑃𝐸𝑥𝑝𝑡 + 𝛽2𝑙𝑛𝐺𝐶𝐹𝑡 + 𝛽3𝑙𝑛𝑇𝑅𝑒𝑣𝑡 + 휀𝑡 (9)

β1 β2 and β3 each for the model stated above are the parameter to be estimated. So that

the prior economic expectations are; β1 β2 and β3 are greater than zero.

Where, t represents time series dimension. RGDP is the real GDP growth rate, TExp is

government total expenditure, CRExp is government current expenditure, TRev is gross

36

revenue from tourism and GCF is the gross capital formation. All these variables are

expressed in logarithmic transformation.

Model 2.

This regression model is the linear regression between real GDP growth

and different components of government expenditure such as expenditure on

agriculture and forest (ExpAF), economic affair (ExpEA), information and

communication (ExpIC) and foreign affair (ExpFA) with gross capital formation and

gross revenue from tourism being control variables. Real GDP is the dependent

variable. The equation is given below:

𝑙𝑛𝑅𝐺𝐷𝑃𝑡 = 𝛽0 + 𝛽1𝑙𝑛(ExpAFt) + 𝛽2𝑙𝑛 (ExpEAt) + 𝛽3𝑙𝑛 (ExpICt) + 𝛽4𝑙𝑛

(ExpFAt) + 𝛽5𝑙𝑛 (GCFt) + 𝛽6 𝑙𝑛(TRevt) + 휀𝑡 (10)

Where,

Ln RGDPt = Natural logarithm of real Gross Domestic Product at time t

Ln (ExpAFt) = Natural logarithm of expenditure on agriculture and forest

Ln (ExpEAt) = Natural logarithm of expenditure on economic affair

Ln (ExpICt) = Natural logarithm of expenditure on information and

Communication

Ln (ExpFAt) = Natural logarithm of real expenditure on foreign affair

Ln (GCFt) = Natural logarithm of real gross capital formation at time t

Ln (RevTt) = Natural logarithm of net revenue from tourism.

휀𝑡 = Random Error term (is stochastic variable to accommodate

the influence of other determinants of economic growth

which were not included in the model)

The prior economic expectations are; βi (i=1, 2…... 7) are greater than

zero. It implies that the intercept and slope coefficient are expected to have positive

sign, indicating that each components of public spending is expected to correlate

positively with real GDP growth. The study explores the positive and negative impact

37

of public expenditure on real GDP growth. To achieve these objectives, our study would

employ least square regression model and error correction model to examine long run

and short rum effects respectively. Eventually, we will base our result based on the

frame work of Keynesian and Endogenous growth theory for short and long run result

validations.

3.3 Time Series Properties of the Data and Techniques of testing

3.3.1 Estimation issue

Many macroeconomic time series are usually non-stationary and

applying standard least regression method to non-stationary data series can give

nonsense correlation and spurious regression. Therefore, it is important to test and

correct various pitfalls of time series data before applying OLS regression on the data.

The first step in analyzing time series data involved testing for stationary of the series

to ensure that the series have a zero mean and constant variance. That is, the time series

data under consideration should be tested for stationary before we can attempt to fit a

suitable model. Spurious regression is, therefore, not desirable. Thus we need to test

the series for unit root.

3.3.2. Testing for Unit Root

Checking non stationarity of the data is the first step in analyzing time

series data. To escape from estimating spurious results, the study conduct stationarity

test. The Augmented Dickey Fuller (ADF) is employed to check the existence of unit

root. The ADF regression equation to test unit root in a series Y is in the form:

∆𝑌𝑡 = 𝛼0 + 𝛽𝑦𝑡−1 + 𝛼1𝑇 + ∑ 𝛾𝑗𝑘𝑗=1 ∆𝑦𝑡−𝑗 + 휀𝑡 (11)

Where ∆𝑦𝑡 referred to first difference of the data, T is the time trend variable. The k

lagged difference terms are added to remove serial correlation in the residual and

𝛼0, β,𝛼1 and γ are estimated parameters. 휀𝑡 is random error term.

38

Model (11) is developed since all the variables of interest at level are

assumed to have unit root which could produce inconsistent result if the variables were

run together in the multiple regression without taking first difference. If the computed

ADF test statistic is greater than the ADF critical value at a given level of significance,

we do not reject the null hypothesis rather fail to reject null hypothesis that unit root

exits. Thus we differentiate all the series once to make stationary. Therefore, these

series are said to be integrated of order one, i.e. I (1).

In fact, knowing the order of integration between GDP growth and

compositions of public expenditure is the first step that enables us to determine the next

step of estimation. When variables of interest considered in this paper are found to be

stationary, then the estimation of regression is possible.

3.3.3 Error Correction Model

Computing long run estimates of co-integration relations is only a first

steps to estimate complete model. Along with the long run estimation, the short run

adjustment of the model is also equally important as it conveys the short run correction

behavior of the economic variables. The estimation of short run dynamics is often

carried out by first eliminating trends in the variables, mostly by differencing. However,

this method will throws away some potential information about the long run

association. The better approach is to transform the dynamic approach into error

correction mechanism. Error correction method conveys information about both long

run and short run properties of the model, with disequilibrium as a process of

adjustment to the long run dynamic model. Specifically, the model take the following

general form for the short run relationship.

∆𝑌𝑡 = 𝛼𝑖�̂�𝑡−1 + 𝛽1 ∗ ∆𝑌𝑡−1 + 𝛽𝑖 ∑ ∆𝑋𝑡−𝑘

𝑘

𝑘=1

(12)

Where, α shows the degree of adjustment of the dependent variables to its long run

solution. Where α is expected to be negative and less than 1, it serves to influence the

short term movements in the dependent variables.

39

3.4 Data

This research aims to establish the impact of government expenditure on

economic growth in Bhutan for the period between 1985 and 2015 for various

departments of government expenditure. The data of Capital expenditure, Current

expenditure, expenditure on Agriculture and Forest, Information and Communication,

Foreign Affairs and Economic Affairs were collected from SYB8. Data pertaining to

CPI was extracted from International Financial Statistics (IFS). While data on real GDP

and Gross Capital Formation were collected from national account statistics of Bhutan.

Finally, the data on tourism revenue was collected from office of TCB9. In line with

this, the answer to the question posed in chapter 1(one) is based on secondary data form

the various annual reports of the Government.

3.5 Definition and measurement of variables

1. Real GDP growth rate

This is the rate of increase in gross domestic product at constant price.

It captures the change in value of final goods and services produced in an economy for

a particular period of time.

2. Total Government Expenditure

Total government expenditure comprises of expenditures allotted to all

Ministries, Judiciary, Constitutional Bodies, Dzongkhag Administration and Geog

Administration.

3. Total capital expenditure

Total expenditures allotted to all Ministries, Judiciary, Constitutional

Bodies, Dzongkhag Administration and Geog Administration for creation new capital

8 National Statistical Year Book, National statistical Bureau

9 TCB stand for Tourism Council of Bhutan

40

goods. Capital expenditure includes acquisition or creation of capital assets such as

buildings, roads, land, equipment and machinery.

4. Total current expenditure

Total expenditures allotted to all Ministries, Judiciary, Constitutional

Bodies, Dzongkhag Administration and Geog Administration to meet daily

maintenance and repairing expenses. It includes spending on recurrent expenditure that

are incurred each year such like wages, salaries, administration, interest payment,

welfare service, etc.

5. Public expenditure on Agriculture and Forest

This is the fractional part of total government expenditure. It includes

the expenditure on all types of agricultural activities, environmental conservation, and

livestock, such as buying modern agricultural equipment’s, agricultural inputs like high

yielding seeds, etc.

6. Public expenditure on information and Communication

This is the fractional part of total government expenditure. MoIC10

is

responsible for prompting the development of reliable and sustainable information,

communication and transport networks and systems. It also includes activities such as

national telecommunication network, fiber optic cable connection layouts, and postal

services.

7. Public expenditure on Foreign Affair

Public expenditure on Foreign Affair is the part of total expenditures

which includes expenses on development of foreign relations.

8. Public expenditures on Economic Affair

This is the fractional part of total government expenditure directed to

activities such as Trade, Industry, Intellectual Property, Geology and Mines, Hydro met

10 MoIC stand for Ministry of Information and Communication

41

services, Renewable Energy, Cottage and Small Industry. This sector is responsible for

proper management of economy in the country.

9. Gross Capital Formation

Gross capital accumulation during an accounting period in country, and

the term refers to additions of capital stock, such as equipment, tools, transportation

assets, and electricity.

10. Revenue from Tourism

Gross revenue earned by tourism sector in the form of royalties, fees and

other charges.

3.6 Working hypothesis

The main Hypotheses of this research includes the following

1. H01: Total public expenditure contributes negatively on real GDP growth in

Bhutan.

2. H02: Total capital expenditure contributes negatively on real GDP growth in

Bhutan

3. H03: Total current expenditure contributes negatively on real GDP growth in

Bhutan

4. H04: Government expenditure on Agriculture and Forest has no significant

contribution on real GDP growth in Bhutan.

5. H05: Government expenditure on Economic Affair has no significant

contribution on real GDP growth in Bhutan.

6. H06: Public expenditure on Information and Communication has no significant

contribution on real GDP growth in Bhutan.

7. H07: Public expenditure on Foreign Affair has no significant contribution on

real GDP growth in Bhutan.

42

CHAPTER 4

RESULTS AND DISCUSSIONS

4.1 Descriptive Study

In this section, descriptive and econometric analysis of the relationship

between government expenditure and real GDP growth are presented. First we present

the descriptive statistics to show the nature of the data. Secondly, we perform the

stationary test and then follow by regression analysis. The data are in real term (constant

price). The nominal values of each variables have been divided by consumer price index

(CPI) to generate real data.

A graphical representation of total government expenditure together

with real GDP indicates an increasing trend in the data over the time as shown in figure

4.1.1.

Figure.4.1.1

Real total expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

0

5000

10000

15000

20000

25000

30000

35000

0

10000

20000

30000

40000

50000

60000

70000To

tal E

xpen

dit

ure

Rea

l GD

P

Year

Figures in million Nu.

Real GDP Total Expenditure

43

The graph 4.1.1 clearly states that government expenditure in Bhutan

accelerated over the year with much greater rate.

Similarly, the trend in the data of capital expenditure along with real

GDP also predicts increasing trend over the year. While the expenditure for fiscal year

2012/2014 projective to decline nominally by 9%. This is due to the shortage of rupee

reserve (Indian currency). In this case, government has tighten the country’s

expenditure to bring the shortage in line with available resources (see graph 4.1.2).

Figure. 4.1.2

Real capital expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

0

2000

4000

6000

8000

10000

12000

14000

16000

0

10000

20000

30000

40000

50000

60000

70000

Cap

ital

Exp

end

itu

re

Rea

l GD

P

Year

Figures in million Nu.

Real GDP Capital Expenditure

44

A graphical representation of total current expenditure together with real

GDP indicated an increasing trend in data over the time as given below in figure 4.1.3.

Figure. 4.1.3

Real current expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

Current expenditure shows increasing trend as it includes all general

public final consumption expenditures for buying of goods and services. It also

includes national defense and security. However, it excludes public military spending

which are portion of government capital formation.

0

2000

4000

6000

8000

10000

12000

14000

16000

0

10000

20000

30000

40000

50000

60000

70000

Cu

rren

t Ex

pen

dit

ure

Rea

l GD

P

Year

Figures in illion Nu.

RGDP Current Expenditure

45

A graphical representation of real expenditure on Agriculture and Forest

together with real GDP depicted that the two series has rising trend with some curvature

over some years.

Figure.4.1.4

Real Agriculture and Forest expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

The figure 4.1.4 states that there was high public spending on

Agriculture and Forest. The increasing trend of public expenditure in this ministry was

due to free distribution of agricultural equipment and improved seeds to the farmers

which includes expenditure on utility van, power taller, seed and saplings, and other

livestock related services.

0

500

1000

1500

2000

2500

0

10000

20000

30000

40000

50000

60000

70000

Exp

. on

Agr

icu

ltu

re &

Fo

rest

Rea

l GD

P

Year

Figures in milliion Nu.

RGDP Exp Agriculture & Forest

46

The real expenditure on information and communication also showed

increasing trend along with the trend of real GDP with some curvature. This increase

in public spending pertains to government expenditure on installation of more new

modern telecommunication facilities and other services during some year.

Figure.4.1.5

Real Information and com. expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

0

200

400

600

800

1000

1200

1400

1600

0

10000

20000

30000

40000

50000

60000

70000

Exp

. on

info

rmat

ion

Rea

l GD

P

Year

Figures in million Nu.

Real GDP Expenditure Information and Communication

47

The graphical representation of expenditure on economic affair

together with real GDP is presented in figure 4.1.6. The spending in this department

was mostly constant over the years.

Figure.4.1.6

Real economic affair expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

The sharp increase in expenditure on ministry economic affair in the

fiscal year 2000-2002 was mainly due to privatization of Public sector activities.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

0

10000

20000

30000

40000

50000

60000

70000

Exp

. on

Eco

no

mic

Aff

air

Rea

l GD

P

Year

Figures in million Nu.

Real GDP Expenditure on Economic Affair

48

The graph of real foreign expenditure with real GDP indicates upward

trend between the years ranging from 1985 to 2015. This increasing trend of foreign

expenditure indicates the investment in creating better development of foreign

relations.

Figure.4.1.6

Real foreign expenditure and real GDP of Bhutan, 1985-2015

Source: National Statistical Year Book, National Statistical Bureau, Bhutan

Gross capital formation together with real GDP also revealed increasing

trend. It means that there was an increasing rate of new capital formation in Bhutan

over the year. The fluctuation over the year was mainly due to major investment in

mega Hydro power Plat beside other. Similarly, the fall in the domestic investment in

2007-2008 was due to global financial crisis.

0

100

200

300

400

500

600

0

10000

20000

30000

40000

50000

60000

70000

Exp

. on

Fo

reig

n A

ffai

r

Rea

l GD

P

Year

Figures in million Nu.

Real GDP Expenditure Foreign Affair

49

Figure.4.1.7

Real gross capital formation with and real GDP of Bhutan, 1985-2015

Source: National Account Statistics, National Statistical Bureau, Bhutan

Revenue from tourism together with real GDP also revealed increasing

trend in data. It means gross revenue received every year seems to be increasing along

with an increased in real GDP. This shows that the government obtains additional

amount of revenue from tourism each year to finance its expenditure. This is shown in

figure. 4.1.8

0

5000

10000

15000

20000

25000

30000

35000

0

10000

20000

30000

40000

50000

60000

70000

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Gro

ss C

apit

al F

orm

atio

n

Rea

l GD

P

Year

Figures in milliion Nu.

Real GDP Gross Capital Formation

50

Figure.4.1.8

Real Gross revenue from tourism and real GDP of Bhutan, 1985-2015

Source: National Account Statistics and TCB11

4.2 Descriptive statistics

The descriptive statistics are presented in Table 4.1. This paper used

annual data covering the period 0f 31 years. The variables we include in our study

comprise of real gross domestic product (RGDP), total expenditure (TExp), total capital

expenditure (CAPExp), total current expenditure (CRExp), expenditures on

Agriculture and Forest (ExpAF), Information and Communication (ExpIC), Economic

Affair (ExpEA) and Foreign Affair (ExpFA) respectively. In addition, gross capital

formation (GCF) and revenue from tourism (TRev) are used as control variables. Real

GDP is considered as dependent variable whereas all other variables are explanatory

variables. All the variables were expressed in real term.

11 Tourism council of Bhutan

0

500

1000

1500

2000

2500

3000

3500

0

10000

20000

30000

40000

50000

60000

70000

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

Tou

rism

Rev

enu

e

Rea

l GD

p

Year

Figures in million Nu.

Real GDP Tourism Revenue

51

Table 4.1

Descriptive statistics

Measurement mean Std. Dev. Minimum Maximum skewness kurtosis

RGDP 25656.4 15942.63 6756.9 59240.0 .74568 2.2221

TExp 12905.8 8553.56 3498.4 28858.9 .64778 1.8862

CAPExp 6449.6 4202.52 1930.5 15022.2 .65147 2.0437

CRExp 6456.2 4409.2 1402.3 14393.8 .66635 1.8763

ExpAF 1145.60 471.21 384.5 1989.5 .13932 1.867

ExpEA 987.15 773.12 212.2 4104.3 2.2555 9.5641

ExpIC 714.97 413.16 105.2 1463.6 .19645 2.0791

ExpFA 249.81 137.22 2.9 539.4 .29382 2.4545

GCF 12623.3 9487.58 3403.63 32716.1 .93930 2.6188

TRev 938.02 967.03 82.67 3141.7 1.1119 2.9362

Source: Summarized by author

In the table 4.1, skewness coefficient depicts that real GDP, TExp,

CAPExp, CRExp, ExpAF, ExpIC, ExpFA, GCF were normal except ExpEA and TRev.

This conclusion was being reached as the skewness coefficient adjusted between -1 and

+1(Bulmer, 1979). If the skewness is positive, the data were positively skewed or

skewed right. If the skewness coefficient is negative, the data were negatively skewed

or skewed left. In fact, the distributions were positively skewed with expenditure on

economic affair distribution with longest tail. However, Kurtosis coefficient depicted

that GDP, TExp, CAPExp, CRExp, ExpAF, ExpIC and ExpFA have platykurtic

distribution. While ExpEA variables had a leptokurtic distribution while remaining

variables conformed platykurtic distribution. According to George and Mallery (2010)

the values for symmetry and Kurtosis ranging from -2 to +2 are considered satisfactory

in order to prove normal univariate distribution

52

4.3 Diagnostic Testing

Gujarati (2004) suggest that in order to have decent econometric models

for least square regression, it should qualify some assumptions. Some of these

assumptions includes that the data should be linear, the residual must be normally

distributed, no correlation between independent variables, no multicollinearity, etc.

Therefore, this study conduct correlation test, multicollinearity test and residual

diagnostic test as shown in the coming sections.

4.3.1 Correlation Test.

One of the important assumption of least square econometric analysis

on the time series data is that the independent variables should not have correlation to

each other. To test this important assumption, we used pair-wise correlation test. Many

literature mentioned that correlation should not be larger than of 0.8 in case of pair-

wise correlation matrix. This test is shown in tables 4.2 and 4.3 respectively.

Table 4.2

Model 1: Pair-Wise correlation matrix

lnTExp lnCAPExp lnCRExp lnGCF lnTRev

lnTExp 1

lnCAPExp 0.9872 1

lnCRExp 0.9879 0.9508 1

lnGCF 0.9564 0.9487 0.9419 1

lnTRev 0.9417 0.9364 0.9250 0.9390 1

Source: Author’s calculation

53

Table 4.3

Model 2: Pair-Wise correlation matrix

lnExpAF lnExpEA lnExpIC lnExpFA lnGCF lnRevT

lnExpAF 1

lnExpEA 0.2613 1

lnExpIC -0.0219 -0.0429 1

lnExpFA 0.7620 0.4578 -0.0190 1

lnGCF 0.8183 0.3128 0.0385 0.6583 1

lnRevT 0.7168 0.2013 -0.0027 0.6600 0.9390 1

Source: Author’s calculation

From the correlation results presented in table 4.2, we concluded that the

independent variables were highly correlated with each other in model 1. Many

literature suggested that correlation should not be larger than of 0.8 in case of pair-wise

correlation matrix. However, model 2 reflected some positive correlation between

expenditure on agriculture and forest and gross capital formation. And also gross capital

formation and tourism revenue were highly correlated. This type of correlation might

introduce multicollinearity in a way. So using least square regression in such a situation

might result in spurious regression.

As it is usually known that we face with autocorrelation with time series

data. We use regression with the Newey-West Standard Error regression technique. The

Newey-West (1987) variance estimator is an extension that yields consistent estimates

when there is autocorrelation in addition to possible heteroskedasticity.

The next steps is to check multicollinearity between explanatory

variables. From table 4.2, it is known that there is very high correlation between

independent variables. Owing to the high multicollinearity in the estimation, we

decided to drop gross capital formation from the model

54

4.3.2 Multicollinearity Test.

If there is a perfect linear relationship among the explanatory variables,

the estimates for a regression model cannot be BLUE. When two or more than two

variables are collinear, it is often called multicollinearity. Which means there should

not be multicollinearity among variables. To test this important assumption, we used

VIF. And the rule of thumb for VIF suggest that VIF of 10 or greater are cited as

symbolic of problematic collinearity. On the other hand, the tolerance value lower than

0.1 is cited as multicollinearity. In such a situation, one independent variable could be

considered as a linear combination of other independent variables. Table 4.4 below

represents the multicollinearity test.

Table: 4.4

Variance Inflation Factor

Model 1A Model 1B Model 1C Model 2

lnTExp 8.84

lnCAPExp 8.12

lnCRExp 6.93

lnExpAF 4.11

lnExpEA 1.31

lnExpIC 1.00

lnExpFA 2.92

lnTRev 8.84 8.12 6.93 3.05

Mean VIF 8.84 8.12 6.93 2.48

Source: Author’s calculation

Table 4.4 suggests that our regression model do not suffer from sever

multicollinearity or are not so worrisome. So we can proceed with the estimation using

simple least square method. But before we estimate the regression, the primary step is

to check the stationarity of the data under study. Therefore, we begin with testing unit

root of the series.

55

4.4 Long run relationship and short run adjustment

4.4.1 Unit Root Test

We performed Augmented Dickey Fuller unit root test and used the

critical values proposed by McKinnon (1991).

The unit root test results are presented in the table 4.5. We have included

trend in the test specification. The results suggests that variables from both the models

are not stationary at level with 5% significance level. However, all variables became

stationary after taking the first difference. This implies that the variables are integrated

of order one, say I (1). Therefore, we examine the existence of long run relationship

between the real GDP and components of government expenditure by using the two-

step Engle-Granger co-integration test.

Table: 4.5

Result of Unit Root Test

At level At first difference

variables ADF statistics ADF statistics Conclusion

lnRGDP -2.422 -4.825*** I(1)

lnTExp -1.980 -6.073*** I(1)

lnCAPExp -2.290 -6.638*** I(1)

lnCRExp -2.118 -5.011*** I(1)

lnExpAF -3.718 -6.652*** I(1)

lnExpEA -3.467 -7.366*** I(1)

lnExpIC -2.894 -5.605 *** I(1)

lnExpFA -3.564 -5.621*** I(1)

lnTRev -3.572 -4.558*** I(1)

**(***) denotes rejection of the hypothesis at 5%(1%) significance level

Source: Author’s calculation

Table 4.5 suggests that the variables we considered might be co-

integrated. Therefore, we will perform the co-integration test in the next section.

56

4.4.2 Co-integration

Because all variables are integrated of order 1, we examine the long run

association between real GDP and components of government expenditure. If the sets

of a variables are of the same order and if it have one or more linear combination of

these variables that is stationary, then the variables are cointegrated. We perform the

two-step Engle-Granger co-integration test. We have tested the residuals and found that

all equations are cointegrated.

The ADF test result of the unit root test with the residuals are presented

in the table 4.6.

Table 4.6

Residual Based Test for Co-integration (Stationary Test)

Models Test

Statistics

1% critical

value

5% critical

value

10% critical

value

Order of

Cointegration

Model 1A -3.568 -3.716 -2.986 -2.624 I(0)

Model 1B -4.042 -3.716 -2.986 -2.624 I(0)

Model 1C -4.135 -3.716 -2.986 -2.624 I(0)

Model 2 -4.872 -3.716 -2.986 -2.624 I(0)

Source: Author’s calculation

The cointegration in table 4.6 confirms that the residuals are stationary

at 1% significance level. Therefore, is stationary at level, say I(0). It means that there

exist a long run relationship between dependent variable (real GDP) and independent

variables (total expenditure, capital expenditure, current expenditure, expenditure on

agriculture and forest, information and communication, economic affair, foreign affair,

gross capital formation and tourism revenue). Thus, we can examine the long run

relationship between real GDP and components of government expenditure by using

the Ordinary Least Square method.

4.4.3 Long run relationship estimation

The first objective is to find out the effects of different components of

government expenditure on the real GDP growth. The long run relationship are

57

presented in tables 4.7 and 4.8 and short run adjustments are presented in tables 4.9,

4.10, 4.11 and 4.12. All the estimations are computed taking variables in their level

form in Stata.

The first long run relationship we considered is the association ship

between the real GDP and the total government expenditure. We also consider different

types of government expenditure which are capital and current expenditures. The

results in table 4.7 (model 1A, model 1B and model 1C) shows that the sign of the

coefficient (beta) corresponding to total expenditure (TExp), Capital expenditure

(CAPExp), current expenditure (CRExp) components and tourism revenue are

positively and statistically significant as expected in all models. This means that total

government expenditure, capital expenditure and current expenditure have positive

relationship with real GDP growth in the long run.

Table 4.7

Model 1: Long Run Estimated Result

Dependent variable: log of real GDP (lnRGDP)

Method: Least Square

Variables Model 1A Model 1B Model 1C

Coef. Coef. Coef.

lnTExp .550***

(.1025)

lnCAPExp .318***

(.1143)

lnCURExp .557***

(.0958)

lnTRev .224***

(.0612)

.353***

(.0676)

.213***

(.0518)

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level.

Figure in the bracket () indicates newey-west standard error.

Source: Author’s calculation

58

In addition, the coefficient of individual variables is discussed hereafter.

The long run result indicated that the total government expenditure have positive and

statistically significant relationship with real GDP growth. The coefficient of 0.550 (p-

value=0.002) implies that one percentage increases in total government expenditure

will result in 0.55 percentage increase in the real GDP. This finding is in accordance

with the finding of Albatel (2000), Aigheyisi (2013), and Gemmell et.al (2015).

However, our finding is consistence with the theoretical frame work developed by

Barro and Sala-i-Martin (1992). Furthermore, the coefficient of tourism revenue of

0.224 suggests that one percentage increase in earning revenue from tourism will boost

growth of real GDP by 0.22 percentage. Thus, the study confirms to have long run

association between real GDP and stated independent variables.

As per the finding of the influence of different types of public

expenditure on growth is concerned, we have noted in the literature review that

Devarajan et al. (1996) found a positive and significant relationship between current

expenditure and real GDP growth and negative and significant relationship between

capital components expenditure and real GDP growth for 43 countries. Our long run

result indicates that government capital expenditure and current expenditure revealed

positively statistically significant association ship with the real GDP growth. From table

4.7, one percentage increase in government current expenditure will leads to 0.55

percentage increase of real GDP growth in the long run (p-value=0.000). Moreover,

one percentage increase in the capital expenditure results in an increases in the real

GDP growth by 0.318 percentage. These findings were consistent with Gemmell et.al

(2015), Al-Fawwaz (2016) and Dandan (2011) where they have stated that total capital

expenditure and current expenditure resulted positive and significant impacts on GDP

growth in the long run. Moreover, our findings signifies the productive use of Public

resources in Bhutan. On the other hand, our findings differ with those of Ghosh and

Gregoriou (2008) as they have found that capital expenditure is statistically

insignificant in the long run.

The coefficient associated with tourism revenue is positive and

statistically significance in the long run. This suggested that an increase in gross income

from tourism will boost real GDP growth in the long run. Which means that an increase

in the number of tourists visiting the country really matters in Bhutan. In particular, the

59

positive value in the long run coefficient imply that all other thing being equal, a rise in

tourism revenue promotes long term economic growth. The coefficient suggests that

one percentage increase in gross revenue from tourism leads to 0.22 percentage, 0.35

percentage and 0.21 percentage increase in real GDP growth respectively (see table 4.7

Model 1A, Model 1B & Model 1C). These finding suggests that income made from

tourism industry can boost economic growth in Bhutan. Therefore, government should

discover more tourism activities, spots with modern amenities. And also, revisit tourism

policy to address the high prevailing tourist tariff in order to receive more number of

dollar paying tourists in the country. Furthermore, the role of government should be

supportive in all case to allow tourism sectors to drive economic growth in Bhutan.

We also consider the relationship between the real GDP and government

expenditure from different departments (Ministries) as shown in model 2. The result

are presented in table 4.8. Based on R-square, the model performed well. The result

shows that the sign of the coefficient (beta) corresponding to expenditure on agriculture

and forest, information and communication, economic affair and tourism revenue turn

out to be positive as theoretically expected in the model. However, government

expenditure on Foreign Affair was significantly negative in the long run.

60

Table 4.8

Model 2: Long Run Estimated Result

Dependent variable: RGDP (Real GDP)

Method: Least Square

Variables Coefficients

lnExpAF .247**

(.1287)

lnExpEA .077

(.0528)

lnExpIC .090**

(.037)

lnExpFA -.095**

(.0465)

lnTRev .502***

(.0449)

R-Squared 0.9394

Prob(F-Stat) 0.0000

Durbin-Watson stat. 1.178835

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level.

Figure in the bracket () indicates standard error.

Source: Author’s calculation.

The coefficient associated with expenditure on agriculture and forest is

statistically significant and accomplish positive value only in the long run. The long run

coefficient is positively significant at a 5% significant level. From table 4.8, a one

percentage increase in agriculture and forest expenditure will results to 0.24 percentage

rise in the real GDP growth (p-value=0.001). Moreover, a one percentage increase in

the expenditure on information and communication results in an increase in the real

GDP by 0.09 percentage (p-value=0.020). Similar findings were stated by (Vu, 2005),

Yu et.al (2008), Erhan (2012) and Musaba et.al (2013). They found that spending on

61

agriculture was potentially strong in promoting economic growth in the long term. In

contrary, Saad and Kalakech (2009) and Amasoma et al. (2011) found spending on

agriculture was insignificant in both long and short term.

Furthermore, the long run result indicated that the expenditure on

Economic Affair attached significant association with real GDP but insignificant in the

short run, which means that the expenditures on economic service was unproductive.

These types of statistically insignificant effects of government spending may be due to

disorganization. Perhaps, inefficiency of government expenditures has widely been

associated in the literature with bad governance and high corruption which happens

mostly in developing countries. It can be said that this sector should have significant

impact on economic growth as it is the main pillar of the economy.

Unexpectedly, government expenditure on Foreign Affair is found to be

negative although significant determinant of real GDP growth, which did not conform

to the expectation of a positive linkage between expenditure on Foreign Affair and real

GDP growth. From the table 4.8, a one percentage increase in government expenditure

on foreign affair will leads to 0.09 percentage decrease in the real GDP growth in the

long run. Our result could be generalized to the fact that the expenses on development

of foreign relations do not create any valuable economic activities. It means that

expenditure on foreign affair exert adverse effect on real GDP growth in Bhutanese

economy. So the excess use of government fund in this department (Ministry) become

unproductive. As (Devarajan, 1996) stated that seemingly productive expenditure,

when used more will became unproductive.

Finally, the statistical significant of the coefficient corresponding to

tourism revenue shows positive effects on real GDP growth in Bhutan. It is Significant

at 1% significance level. Unlike in model 1, when we conditions tourism revenue along

with government expenditure at disaggregate level, its impact increase drastically.

Tourism play key role in promoting long term growth in Bhutan. The coefficient of

0.502 suggest that one percentage increase in revenue generation from tourism

increases real GDP growth by 0.502 percentage in the long run. While the short run, it

is reported to exert negative impact on real GDP growth in Bhutan.

Nevertheless, our findings are consistent with endogenous growth

theory of fiscal policy laid down by Barro (1990) and Barro and Sala-i-Martin (1992).

62

The endogenous growth model explains the relationship between government spending

and economic growth where public expenditure composition is taken as one of the

determinants of economic growth (Sanz & Velazquez, 2001). However, in reality, we

cannot guarantee our findings. These findings may depend on various aspects like

methods or techniques adopted, type of country under study to analyze, assumptions,

etc. With the theoretical framework about the effects of public expenditure on economic

growth is concerned, Barro (1990), Bajo-Rubio (2000) and Milbourne et al. (2003)

reported that a positive effect is anticipated to be found where size of government is

smaller (like Bhutan) and negative effects to those countries where size is bigger than

a certain threshold, mostly developed countries. However, in general, the success of

public spending in intensifying the economy and fostering rapid economic growth

depends on whether the expenditure is productive or unproductive. All things being

equal, productive expenditure would have positive effect on the economy, while

unproductive expenditure would have negative effect or no effect in the nations’

economy.

4.4.4 Short-run Adjustment

By knowing that there exist a long run association between dependent

variable and independent variables then there will be error correction process is taking

place. It means that there could be deviations from the equilibrium relations in the short

term. This disequilibrium come from the short run fluctuations on the data series. ECM

methods predicts how quickly can real GDP adjust towards the long run equilibrium

after a short period shock. ECM includes using the previous value of residual to adjust

the short run deviations from the equilibrium. Therefore, the expected sign of the

coefficient of ECM should be negative and statistically different from zero. This

negative sign reports a return of the variables towards equilibrium. The complete value

of coefficient of the lagged value of residual denotes the speed of adjustment and

indicates how quickly equilibrium is restored in the event of short term shock.

The short run coefficient of single variables should be examine to find

out the relevant addition of each variables of government expenditure on real GDP

growth. We present our short run regression equations taking lagged value of real GDP,

lagged value of real total expenditure, lagged value current expenditure and lagged

63

value of revenue from tourism along with residual. All the variables in the short run do

not conform priori expectation. They are all negative and insignificant. However,

lagged value of capital expenditure is negative and significant at 10% significant level

(Table 4.10). This finding is consistent with the previous finding of Lheanacho (2016)

and Ghosh and Gregoriou (2008). On contrary, lagged value of tourism revenue is

reported to be negative determinant of real GDP growth (see tables no. 4.9, 4.10 and

4.11). The coefficients of the error correction (uhat-1) are as anticipated, negative and

statistically significant at 1% significant level. Such type of finding was also reported

by Aigheyisi (2013). Thus error correction will precisely act to restore equilibrium

when there is deviation in the short run. So we will consider only error correction in

our main analysis.

Table 4.9

Model 1A: Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP LD.lnTExp LD.lnTRev Uhat(-1)

D.lnRGDP -.1699

(.1500)

-.07818

(.0621)

-.05906*

(.0322)

-.3524***

(.0811)

D.lnTExp 1.274**

(.5661)

.13154

(.2345)

.0373

(.1216)

.49101

(.3063)

D.lnTRev -.3136

(.79573)

.12725

(.32968)

.08470

(.1709)

1.265***

(.4305)

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Figure in the bracket () indicates standard error.

R square - 53%

Source: Author’s calculation

The result of error correction model (see table 4.9, Model 1A) shows

that the previous growth value of lagged GDP is negative and insignificant. From the

64

result, lagged error correction value is negative and significant, which conforms the

error correction in the model. This means that the speed of adjustment of lnRGDP is

negative and significant. More essentially, the estimated coefficient of ECM term is -

0.352, which is significant at 1% significance level and has correct sign as expected,

suggests that approximately 0.35 percentage of deviations in previous year is corrected

in the current year. Table 4.9 suggests that though the lagged value of total expenditure

is not significant, error correction appeared to restore any short run deviations from the

long run equilibrium.

Table 4.10

Model 1B Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP LD.lnCAPExp LD.lnTRev Uhat(-1)

D.lnRGDP -.1472

(.1516)

-.0722*

(.04124)

-.06104*

(.03307)

-.2832***

(.0607)

D.lnCAPExp .9673

(.87813)

-.2348

(.23890)

.19737

(.19158)

.05406

( .35215)

D.lnTRev -.2824

(.74916)

.0298

(.20381)

.1311

(.16344)

1.057***

(.3004)

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Figure in the bracket () indicates standard error.

R square was 52%

Source: Author’s calculation

Similarly model 1B suggests that lagged value of real GDP is negative

and insignificant. However, lagged value of capital expenditure is negative and

significant. This means that previous value of government capital expenditure has

negative impact on current growth. On the other hand, lagged error correction value

(Uhat-1) is negative and significant. The coefficient of 0.283, significant at 5% level,

65

suggests that approximately 0.28 percentage of disequilibrium in previous year is

corrected by real GDP in the current year (Table 4.10).

Table 4.11

Model 1C Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP LD.lnCRExp LD.lnTRev Uhat(-1)

D.lnRGDP -.04650

(.16267)

-.0078

(.06392)

-.081**

(.03613)

-.327***

(.10343)

D.lnCRExp 1.4053***

(.47846)

.31947*

(.1880)

-.0207

(.10628)

.803***

(.30424)

D.lnTRev -.86408

(.85861)

.14859

(.3374)

.15536

(.19072)

1.271**

(.5459)

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Figure in the bracket () indicates standard error.

R square = 53%

Source: Author’s calculation

From table 4.11, the lagged value of error correction (Uhat-1) is negative

and significant. The coefficient of -0.327 explains that the disequilibrium in the

previous period will be corrected at the speed of 0.327 percentage annually in the

current period. It means that real GDP can be restore if there is any short run deviations

from the long run equilibrium. As mentioned earlier, tourism revenue have adverse

impact on real GDP.

Finally, in regard of model two, the analysis showed that all the variables

are negative and insignificant. Therefore, for our better analysis, we dropped all

independent variables as they were not significant in the short run. These variables

includes one period lagged value of real GDP, lagged value of expenditures on

agriculture and forest, information and communication, economic affairs, foreign

66

affair, tourism revenue and lagged value of error term. We try to examine only with

lagged value of residual on each dependent variables as shown below in table 4.12.

Table 4.12

Model 2 Short Run Estimated Result /ECM

Dependent Variables Coefficient

Uhat (-1)

D.lnRGDP -.107**

(.0553)

D.lnExpAF .457

(.3890)

D.lnExpEA -.893

(.8354)

D.lnExpIC .341

(.781)

D.lnExpFA -1.016

(1.183)

D. lnTRev .651***

(.242)

*[**](***) denotes rejection of the hypothesis at 10%[5%] (1%) significance

level. Figure in the bracket () indicates standard error.

Source: Author’s calculation

From table 4.12, lagged error correction value was negative and

significant with regard to real GDP growth as a dependent variable. The Uhat (-1)

coefficient is the speed of adjustment factor, ECM term. The ECM term is negative and

significant at 5% significant level as expected. This entails that 0.107 percentage of

disequilibrium in the previous year is restore in the current period.

Thus according to tables 4.9, 4.10, 4.11 and 4.12, real GDP appear to

respond to restore disequilibrium in Bhutanese economy. It entails that the real GDP

67

will converge to long run equilibrium path when there is any short run deviation.

Therefore, the real GDP is stable in the long run in Bhutan.

Notes: variables as previously defined, all the variables are in first difference for the

short run analysis. Uhat (-1) is the ECM term.

68

CHAPTER 5

CONCLUSION AND RECAMMENDATIONS

5.1 Conclusion

Many kinds of studies were carried out by different researchers of

diverse background in order to understand the impact of government spending at the

aggregated and disaggregated level on the economic growth using different techniques

and economic variables. Few of these studies involved to study the impact of public

spending on different sectors of the economy, say like percapita economic growth.

Many other advocates devoted their studies to examine the role of economic growth on

public spending. In this study, we narrow down our analysis to predict the influence of

public expenditure on real GDP in Bhutan.

Since economic theories provided no clear cut answer to how

government size affect economic growth, researchers mostly rely on existing empirical

studies. There has been mixed results on this issue. Ram(1986), Grossman(1988),

Aschauer(1989), Holmes and Hutton(1990) generally found positive association, while

other such like Landau (1986) & Bradley(1989) argued negative or insignificant

relationship between size of a government and growth. This research relied on

Keynesian theory and Endogenous Growth theory developed by Barro and Sala-i-

Martin (1992) as a basis to theoretically validate the findings (results).

The contribution of this research have two folds in existing literature.

Firstly, our findings complement the overall existing literature where most researcher

have had focused on panel cross country analysis. As we know that the effects of public

spending on growth are likely to be influenced by institutional factors and the quality

of bureaucratic systems, it is more appropriate to carryout time series analysis to tackle

such issues. Secondly, this research will immensely help planners in Bhutan as it is the

first research in

relation to public expenditure and real GDP growth. No studies has been conducted in

relation to public expenditure and real GDP growth in Bhutan.

69

Our analysis started with a discussion of pattern and trend of

government expenditure in Bhutan over the period of 31 years, starting from 1985. The

evidence from the graph and statistics showed that total government expenditure has

increased over the time. In other hand, we can see that relative increase in size of public

spending was not accompanied by robust economic growth in the recent times. In fact,

economic growth in Bhutan dropped to 2.14% in fiscal year 2012-2013. This shows

that over the past three decades, government spending grew at a faster rate than the

growth of real GDP. Thus, the rapid growth of Public expenditure caused a concern

among policy makers on its implication on growth. In such type of financial state, an

explanation requires studying the impact of public spending on real GDP growth. This

study is one which tries to investigate the effects of components of government

expenditure on real GDP growth in Bhutan.

The study used unit root test, Cointegration, Least Square regression and

error correction methods to answer the question set in chapter 1. Unlike most of the

studies that used panel or cross-sectional data, this paper take annual data into account

to evaluate the relationship between real GDP growth and components of government

expenditure. After using the stated methodology, the study found interesting results.

The study discovered that some types of government expenditure have potential to

promote real GDP growth. Firstly, the empirical finding pertaining to model 1

demonstrated a significant positive impact of government expenditure on real GDP

growth with current expenditure having greater impact on GDP growth. This suggest

that spending on repair and maintenance has a stronger impact on growth than capital

spending. Indeed, all variables stated in model 1A, 1B and 1C including control variable

showed statistically positive impact on real GDP growth. This tells us that total

government expenditure, capital expenditure, current expenditure, and revenue from

tourism have growth enhancing effects in long run in Bhutanese economy. However,

Model 2 predicted mixed findings.

Following are the main findings of this study. It state the presence of

long run equilibrium relationship exist among the variables. It is also known that

Productive government expenditure affects economic growth positively and

significantly (Barro, 1990). It means that, the success of public spending in intensifying

the economy and fostering rapid economic growth depends on whether the expenditure

70

is productive or unproductive. All things being equal, productive expenditure would

have positive effects on the economy, while unproductive expenditure would have

negative effects on the economy. Therefore, the findings from these fiscal variables

strongly support the prediction of public fiscal policy endogenous growth model. On

the other hand, expenditure on economic affair showed positive but insignificant result

in the long run. However, expenditure on foreign affair exert adverse effect on growth

of real GDP. It also crucial to state that the negative and significant coefficient of Uhat

(-1) indicates that Bhutan’s real GDP responds to restore disequilibrium in the long run.

It means that real GDP will converge to long run equilibrium path if there is any short

run deviation.

5.2 Policy Recommendation

Economic growth in Bhutan highlights volatility and registered very low

in some year. On the other hand, government spending as a fiscal policy tool failed to

play its expected role to stimulate the GDP growth in Bhutan. In this regard, we draw

some policy recommendation from the findings of our study, such as:

1. The study recommends that government should not waste its

available resources in order to finance non-productive expenditure since they have

neutral or no impact on GDP growth. Rather government should use available income

for Productive Purpose. Such type of policy will be helpful in improving infrastructure

facilities, education, agriculture, health that will in turn boost private sectors

investments.

2. Government should allocate higher percentage of resources to

spend on Agriculture sector and information and communication. Spending on

information and communication will improve the quality of linkage of road way, air

way, telecommunication network and IT park. While spending on agriculture and forest

will make Bhutan to meet food self-sufficiency and ensure food security of a nation.

3. Government should decrease the spending on Ministry of Foreign

Affair as it has adverse effect on real GDP growth both in long and short run.

4. Although public spending in economic affair is found to be

insignificant determinant of GDP growth, government should not cut allocation of

71

expenditure on this department as it remain important pillar of economic growth in

Bhutan. Increasing spending on economic affair improves Cottage and Small industries

which was indeed growing very slowly over the year accept hydro power sector.

5. Government should discover more tourism activities, spots with

modern amenities to encourage more inflow of foreign tourist in the country as it

contributes to GDP growth in Bhutan. And also, revisit tourism policy to address the

high prevailing tourist tariff in order to receive more number of dollar paying tourists

in the country. Finally, the role of government should be supportive in all case to allow

tourism sectors to drive economic growth in Bhutan and ensure sustainability of the

industry.

1.3. Suggestions for future research

One of the core macroeconomic indicator associated with fiscal policy

is government expenditure, which was covered in current paper. In this empirical study,

out of ten departments (Ministries) only four are included due to unavailability of data.

To evaluate the impact of government expenditure (fiscal policy) on economic growth

further in more detail, other important sector should be applied such as education,

health, etc. in order to check which sectors contributes the most. Moreover, tax revenue

should be included as it increases the government expenditure. Subsequently, increase

in government spending will then increases total GDP in a specific year.

Furthermore, different econometric techniques should be applied beside

what is used in this study. I suggest to use VECM which represent the system equations

model beside other good model. This model can explain the relation of all variables

together in the system.

72

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APPENDIX

Appendix 1. Estimated Result with gross capital formation and tourism revenue as

control variables.

Table 1.1

Model 1: Long Run Estimated Result

Dependent variable: log of real GDP (lnRGDP)

Method: Least Square

Variables Model 1A Model 1B Model 1C

Coef. Coef. Coef.

lnTExp .398***

(.1298)

lnCAPExp(-1)

.242***

(.0586)

lnCURExp .471 ***

(.1107)

lnGCF .214**

(.0854)

.229***

(.071)

.159**

(.071)

lnTRev .176***

(.0602)

.243***

(.0348)

.163***

(.0553)

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Figure in the bracket () indicates newey-west standard error.

Source: Author’s calculation

81

Table 1.2

Model 2: Long Run Estimated Result

Dependent variable: RGDP

Method: Least Square

Variables Coefficient

lnExpAF .139

(.1088108)

lnExpEA .009

(.0434385)

lnExpIC .0710**

(.0306234)

lnExpFA -.0734*

(.0388867)

lnGCF .394***

(.1035404)

lnTRev .286***

(.0669194)

R-Squared 0.9670

Adj. R-Squared 0.9587

Prob(F-Stat) 0.0000

Durbin-Watson stat. 1.277282

Source: Author’s calculation

82

Table 1.3

Model 1A: Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP LD.lnTExp LD.lnGCF LD.lnTRev Uhat(-1)

D.lnRGDP -.1767

(.1463)

-.08606

(.0604)

-.00925

(.0343)

-.06247**

(.03142)

-.405***

(.0863)

D.lnTExp 1.2289

(.5865)

.018413**

(.2423)

.13008

(.13769)

.03956

(.12593)

.3557

(.3460)

D.lnGCF -.36963

(.70870)

.61583**

(.29284)

.01830

(.1663)

-.4221***

(.15216)

1.123**

(.4180)

D.lnTRev -.41368

(.8484)

.01153

(.3505)

.10989

(.1821)

-.16751

(.19919)

1.073**

(.5005)

Figure in the bracket () indicates standard error.

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Source: Author’s calculation

83

Table 1.4

Model 1B Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP L2D.lnCAPE

xp

LD.lnGCF LD.lnTRev Uhat(-1)

D.lnRGDP -.0516

(.18965)

-.00150

(.012482)

-.00293

(.04568)

-.05215

(.04121)

-.198**

(.08150)

L1D.lnCAPEx

p

.64534

(.89901)

-.05275

(.05917)

.19321

(.21657)

.22963

(.19535)

-.21025

(.38638)

D.lnGCF -.479559

(.70310)

.00828

(.04627)

.070171

(.16937)

-.416**

(.15278)

.771***

(.30218)

D.lnTRev -.93163

(.95790)

.03349

(.06304)

-.24540

(.23075)

.06343

(.20815)

.21155*

(.41168)

Figure in the bracket () indicates standard error.

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Source: Author’s calculation

84

Table 1.5

Model 1B Short Run Estimated Result

Dependent

variables

Independent variables

LD.lnRGDP LD.lnCRExp LD.lnGCF LD.lnTRev Uhat (-1)

D.lnRGDP -.06960

(.15220)

-.05064

(.0631)

.0051

(.03598)

-.0870**

(.03387)

-.447***

(.11273)

D.lnCRExp 1.442***

(.489)

.3067

(.2028)

.16868

(.11565)

-.0387

(.1088)

.810**

(.36230)

D.lnGCF -.60466

(.74222)

.37496

(.30782)

.00812

(.17549)

-.3265*

(.1652)

1.0397*

(.5497)

D.lnTRev -.7923

(.87008)

.16393

(.3608)

.1607

(.19365)

-.2279

(.20572)

1.3066*

(.64446)

Figure in the bracket () indicates standard error.

*[**](***) denotes rejection of the hypothesis at 10%[5%](1%) significance level

Source: Author’s calculation

85

Table 1.6

Model 2 Short Run Estimated Result

Dependent Variables Independent variable

Coefficient

Uhat (-1)

D.lnRGDP -.1395**

(.07007)

D.lnExpAF .2348

(.5042)

D.lnExpEA -1.861

(1.0975)

D.lnExpIC .51500

(.9919)

D.lnExpFA -.9514

(1.515)

D.lnGCF .7991***

(.2553)

D. lnTRev .5622*

(.32855)

Source: Author’s calculation

86

BIOGRAPHY

Name Bal Bdr. Kharka

Date of birth November 27, 1984

Educational Attainment 2005-2007: Bachelor of Commerce (Hons)

Sherubtse College, Kanglung Bhutan

2009: Post Graduate Diploma in Education

Samtse College of Education (NIE), Bhutan

Scholarship Thailand International Cooperation Agency

TICA (Agency)