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RESEARCH MONOGRAPH 17

Deficit Financing, Crowding Out and Economic

Growth: Bangladesh Perspective

Dr. Prashanta Kumar Banerjee

Professor & Director (RD&C), BIBM

Abed Ali Consulting Editor, BIBM

Md. Mohiuddin Siddique

Associate Professor & Director (DSBM), BIBM

Md. Ruhul Amin Assistant Professor, BIBM

BANGLADESH INSTITUTE OF BANK MANAGEMENT

Mirpur, Dhaka

Deficit Financing, Crowding Out and Economic Growth: Bangladesh

Perspective


Abed Ali


Md. Ruhul Amin

Editor Dr. Toufic Ahmad Choudhury, Director General, BIBM

Dr. Prashanta Kumar Banerjee, Professor & Director (RD&C), BIBM

Support Team Md. Golam Kabir, Publications-cum-Public Relations Officer

Papon Tabassum, Research Officer

Md. Morshadur Rahman, Proof Reader

Graphics & Design Md. Awalad Hossain

Md. Nasir Uddin

Published: January, 2016

Published by Bangladesh Institute of Bank Management (BIBM)

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ii Research Monograph 17

Foreword

s part of the ongoing dissemination of BIBM research outputs, the present

research monograph contains the findings of the research project: “Deficit Financing,

Crowding Out and Economic Growth: Bangladesh Perspective”. Crowding out effect

of deficit financing on economic growth in the context of Bangladesh has been

examined in this study.

This publication empirically shows the crowding-out effect of Government

borrowing from banking system on the economic growth in Bangladesh. Government

borrowing from the commercial banks does not appear to exert any negative impact

on private investment by creating fund crisis in long run; rather, short term crowding

in effect has been noticed in the study. The study has also postulated that

Government can borrow from the banking sector up to 3% of GDP without any

hesitation and without hurtening the private investment.

It gives me immense pleasure, on behalf of BIBM, to offer this important resource of

academic inputs to the participants of financial institutions, policy makers,

academicians and common readers as well.

I hope this monograph will be a useful reference point for the stakeholders related to

fiscal and monetary policy implementation authorities.

We do encourage feedback from our esteemed readers on this issue which certainly

would help us improve upon our research activities in the years to ahead.

Dr. Toufic Ahmad Choudhury Director General

It gives me great pleasure, on behalf of BIBM, to offer this important resource to

A

Research Monograph 17 iii

Acknowledgement

his research project “Deficit Financing, Crowding Out and Economic Growth:

Bangladesh Perspective” has been completed with immense support from numerous

individuals and organizations.

We would like to express our gratitude to the honorable Director General, BIBM,

Dr. Toufic Ahmad Choudhury for his precious guidance, observations and ideas to

progress our work all the way through.

We are very much thankdful to Dr. Shah Md. Ahsan Habib, Professor and Director

(Training), BIBM; Mr. S. A. Chowdhury, A. K. Gangopadhaya Chair Professor, BIBM;

and Mr. Helal Ahmed Cowdhury, Supernumerary Professor, BIBM for their opinion

and observation about the report.

Bangladesh Bureaue of Statistics, Bangladesh Bank, different banks and many

organizations extended their cooperation for completing the report. We do very much

recognize their input in fulfilling our objectives.

We are also thankful to all of our faculty colleagues for their opinions and positive

suggestions to carry out our research.

Our honest appreciation goes to Ms. Papon Tabassum, Research Officer, BIBM and

Mr. Md. Awalad, Computer Operator, BIBM for their support.

Finally, we would like to extend our appreciation to those who, openly and sincerely,

extended their support in our research effort.


Abed Ali


Md. Ruhul Amin

T

iv Research Monograph 17

RESEARCH MONOGRAPH 17

eficit Financing, Crowding

Out and Economic Growth:

Bangladesh Perspective

D

Contents

Abbreviations viii

Executive Summary ix

1. Introduction 1

2. Literature Review 3

3. Theoretical Framework of Budget Deficit and Crowding Out Hypotheses 7

4. Methodology, Data Sources and Framework for Empirical Analysis 10

5. Pattern and Trend of Deficit Finance, Crowding Out and Economic Growth 12

6. Empirical Results and Discussions 20

7. Possible Highest Level of Public Borrowing from Commercial Banks 25

8. Concluding Remarks 27

References 28

Appendix 33

Tables

Table-1: GDP Growth Rate and Budget Deficit in Bangladesh (1980-2013) 13

Table-2: Govt. Expenditure: Development and Non-development Expenditure 14

Table-3: Govt. Development Expenditure and Private Investment 16

Table-4: Sources of Financing of Deficit Budget (in %) 17

Table-5: Borrowing from DMBs, Private Investment and Total Investment in

Bangladesh

18

Table-6: Growth Rate of Borrowing from DMBs and Interest Rate 20

Table-7: ADF and KPSS Tests Results 21

Table-8: Johansen-Juselius Cointegration Test 21

Table-9: Johansen-Juselius Cointegration Test 22

Table-10: VAR Estimates in Case of Bi-variate Analysis 23

Table-11: VAR Estimates in Case of Multivariate Analysis 24

Table-12: Johansen-Juselius Co-integration Test 26

Table-13: VECM Estimates in Case of Multivariate Analysis 27

Research Monograph 17 vii

Figures

Figure-1: Crowding Out Effect 8

Figure-2: Classical and Keynesian Views of Crowding Out 9

Figure-3: GDP Growth Rate and Budget Deficit (as % of GDP) in Bangladesh 13

Figure-4: Govt. Expenditure: Development and Non-development Expenditure 15

Figure-5: Govt. Development Expenditure and Private Investment 16

Figure-6: Sources of Deficit Finance (in %) 17

Figure-7: Borrowing from DMBs, Private Investment and Total Investment in

Bangladesh

19

Figure-8: Growth Rate of Borrowing from DMBS and Interest Rate (1980-2013) 20

Figure-9: CUSUM of Recursive Residuals 24

Figure-10: CUSUMSQ of Recursive Residuals 25

Abbreviations

ADF Augmented Dicky-Fuller

ADPs Annual Development Programs

ARDL Autoregressive Distributed Lag

BB Bangladesh Bank

BBS Bangladesh Bureau of Statistics

BIDS Bangladesh Institute of Development Studies

CAGR Compound Annual Growth Rate

CUSUM Cumulative Sum

CUSUMSQ Cumulative Sum of Squares

DMB Deposit Money Bank

FY Fiscal Year

GDP Gross Domestic Product

GNP Gross National Product

KPSS Kwiatkowski, Philips, Schmidt and Shin

NSD National Saving Directorate

OLS Ordinary Least Square

FPE Final Prediction Error

VAR Vector Autoregressive

VECM Vector Error-Correction Model

viii Research Monograph 17

Executive Summary

The nature of relationship between deficit financing, crowding out and economic growth

has long remained a major concern in macro policy framework. Particularly, it gets

serious attention in developing countries as these countries require high investment rate to

reach to a higher growth path. Existing literature showing the relationship between deficit

financing, crowding out and economic growth demonstrates two contrasting viewpoints.

Neo-classical economists argue that deficit financing can cause the interest rate to

increase and, thereby, crowds out private sector investment. Keynesian economists, on

the other hand, argue that an increase in government spending can stimulate private

investment in a situation where the economy operates at less than full-employment level

and a major portion of government borrowing is spent on improving investment

infrastructure of the country.

The empirical relationship found between budget deficit and investment in available

literature is inclusive. Easterly et al. (1994) in their study on public sector deficits and

macroeconomic performance point out that there is a positive relationship between fiscal

balances and interest rates. However, Brunner (1984) notes that portfolio analysis

suggests that interest rates are determined by stock demand and supply, and not by flow

demands and supply, as suggested by the loanable funds model as this can lead to either

significant or negligible effects of deficits on interest rates, depending on the sizes of

accumulated stock of debts and deficits. Mahmoudzadeh et al. (2013) find that the effect

of a budget deficit on private investment in developed countries is negative while for

developing countries, it is positive though the effects are marginal for both the groups.

Bose et al. (2007) investigating the relationship between budget deficit and economic

growth for 30 developing countries from 1970 to 1980 find that the budget deficit helps

the economy to grow if the deficits were due to productive expenditures such as

education, health and capital expenditures. This is also supported by the research made by

Fischer (1993). Brender and Drazen (2008) find that large and growing budget deficit in a

country gives negative signals to the citizens that the Government did not perform well in

managing the funds of a country. Hence, it will lead to slow economic growth due to lack

of confidence among investors and other neighboring countries. In Bangladesh

perspective, Majumder (2007) conducts a research on this issue and confirms that

Government borrowing has been crowding in, not crowding out private investment in

Bangladesh. In a recent study of BIDS, it has been found that government borrowing

from the banking sector does not cause any crowding out effect on private investment in

Research Monograph 17 ix

Bangladesh. Public investment by borrowing from the domestic sources on infrastructure

development rather encourages private investment. The study also suggests that the

government borrowing up to 2.5 per cent of GDP will not produce any crowding out

effect in the economy (Haroon 2014).

Bangladesh economy achieved GDP growth of 6.12 per cent at constant market prices in

FY 2013-14 and registered GDP growth rate averaging 6.2 per cent during the past five

years (MoF, Bangladesh Economic Review 2014). Both public investment and private

investment ought to be increased from its current level of 6.2 per cent and 20.4 per cent,

respectively of GDP in FY 2013 to become a middle income country within a decade by

increasing the GDP growth rate to 10 per cent by 2021 in its „Vision 2021‟. The tax

revenue to GDP in Bangladesh is 11.6 per cent at the end of 2013-2014 whereas during

the same period Malaysia, Nepal, Sri Lanka and India maintained this ratio at 16.11 per

cent, 15.3 per cent, 12.4 per cent and 11.98 per cent, respectively (World Bank Databank

2013). It seems that Bangladesh is not at par with these countries concerning tax–GDP

ratio although Bangladesh keeps on increasing this ratio. It forces government to borrow

from the domestic sources particularly from the banking system as scope for

concessionary external borrowing is shrinking. It is often argued that government's

borrowing from commercial banks keep away private investors from getting enough

money to invest in the economy, which retards the growth of the economy. Private sector

is also concerned as it is thought that more government borrowing will increase interest

rate on bank borrowing which will increase cost of funds of business. In this backdrop,

the current study is an attempt to analyze the crowding out effect of public borrowing

from commercial banks on private investment in Bangladesh to give some policy

proposals to relevant authorities including banks. Based on secondary data, it examines

the linkage between fiscal deficit with other relevant economic indicators by using

techniques like correlation, percentage, compound annual growth rate and other simple

accounting and financial techniques. In finding out the empirical relationship, standard

econometric models applicable for time series data from 1974 to 2013 have been

employed. The following bi-variate and multivariate models have been applied here for

cross examination of empirical results.

LPRI t = 0+ 1LGB_CB t +et--------------------------------------------------------------------------(1)

LPRI t = 0+ 1LGB_CB t +2LnY t +3 IR t +et ----------------------------------------- (2)

x Research Monograph 17

Where PRI= Private Investment, GB_CB = Government Borrowing from Commercial

Banks, Y = Gross Domestic Products, and IR= Interest Rate. The expected signs of the

parameters are: > 0, 1<0, 2> 0, and 3<0.

The pattern and trend of deficit finance, crowding out and economic growth in the context

of Bangladesh during 1980-2013 reveals the following major points:

(i) GDP growth rate exceeded budget deficit almost in all years since 2000.

The correlation coefficient between GDP growth rate and budget deficit as percentage of

GDP was found -0.41. Govt. expenditure persistently increased during the period

1980-2013 with the highest percentage of 24.13 in 2012. CAGR for non-development

expenditure (13.81%) was higher than that of development expenditure (9.62%).

(ii) Private investment as percentage to GDP was at the peak point in 1996-1997 and

2010-2011. A very high level of correlation coefficient between development expenditure

and private investment (+0.97) indicates positive influence of Govt. development

expenditure on increasing private investment. Government borrowing from domestic

sources especially from the banking sector has gradually become the most dominant

source of deficit financing with a share of 57.39 per cent in 2012-2013. Govt. borrowing

seems to have no such strong relationship with the lending interest rate.

Empirical findings on the dynamics between private investment, Government borrowing

from commercial banks, gross domestic products and interest rate progressed as per

following sequences.

Null hypothesis of unit root for any variable in the levels cannot be rejected using ADF

and KPSS tests. However, taking the first difference, the variables are found to be

integrated of first order. Johansen‟s co-integration test results show that private

investment and government borrowing are not co-integrated. Results of multivariate cases

among private investment, government borrowing from banks, GDP in current price and

interest rate indicates that these variables are not co-integrated.

Vector Error Correction Model (VECM) fails to show any co-integrating relationship

among variables. Then we estimate Vector Autoregressive Model (VAR) by the exclusion

of the error-correction term for Granger Causality with short-term interactive relationship.

The bi-variate estimation between private investment and Government borrowing reveals

that preceding year‟s private investment has profound influence on current year‟s private

investment as reflected through the associated t value. It is also found that current year

and preceding second year‟s borrowing from banking sector have positive relationship

Research Monograph 17 xi

with the current year private investment which means that more Government borrowing

in current and preceding second year leads to an increase in current year private

investment. As a result, existence of short-term crowding in effect seems evident in the

economy of Bangladesh. In case of multivariate analysis impact of preceding year‟s

investment and current and preceding second years‟ Government borrowing from the

banking system on current year investment is almost same like bi-variate estimation.

We have performed trial and error method and increased the amount of public borrowing

from banks up to 3 per cent of GDP to find out the highest level of Government

borrowing from banks in Bangladesh before witnessing any crowding out effect in the

economy. It is found that when Government borrows 3 per cent of GDP from banks then

a common force brings the private investment, Government borrowing from the banking

sector, GDP in current price and interest rate together in the long run. There is evidence

of subdue long term crowding out effect of public borrowing from banks on private

investment as reflected through the negative coefficient of the error correction term

without statistical significance.

The absence of crowding out effect can be explained by the presence of excess liquidity

in the banking sector of Bangladesh. Moreover, crowding in effect arises as every year a

large amount of government-borrowed money is spent for promoting private sector

investment and growth of agriculture sector. The findings of the study have important

implications for bankers and fiscal authority. There remains scope for the banking sector

to provide loan to the government as long as there is excess liquidity and the government

can also boost private investment by spending on physical infrastructure for promoting

investment and giving incentives to the real sector of the economy.

xii Research Monograph 17

Deficit Financing, Crowding Out and Economic Growth:

Bangladesh Perspective

1. Introduction

The possible relationship between deficit financing, crowding out and economic growth

attracts attention in both theoretical and empirical literature. Particularly, it gets serious

attention in developing countries as these countries are putting all efforts to get higher

economic growth through ensuring maximum public and private investment. Theoretical

and empirical analyses of the relationship between deficit financing, crowding out and

economic growth have highlighted two contrasting viewpoints. Neo-classical economists

argue that financing of rising fiscal deficit through public borrowing (especially from

banks) can cause the interest rate to increase, and thereby, result in “crowding out”

(i.e., exclusion) of private sector investment needs. When the Government jacks up its

borrowing in the domestic market, this can result in reduced availability of loanable funds

to the private sector, and hence, lowers private investment. Moreover, banks may prefer

to lend to the government, as it is virtually risk-free. Thus, an increase in the size of

public sector spending would be at the expense of the private sector and this can result in

adverse effects on economic growth, inflation and the exchange rate. Keynesian

economists, on the other hand, give a contrasting interpretation of the phenomenon. They

argue that an increase in Government spending can stimulate domestic economic activity

by a greater proportion (through the “multiplier” process), and thereby, “crowds in”

private investment, especially when the economy is at less than full-employment level.

But, there is a catch. Private sector can derive benefit only if public investment is in

physical infrastructure, education and health, which will facilitate and complement the

activities of the private sector. Therefore, if deficit finance causes productive public

investments and if public and private investments are complementary, then the negative

impact of high public borrowings on economic growth may be offset. However, the fear

about high fiscal deficit is justified if the Government incurs deficit to finance its current

expenses rather than capital expenditure.

In recent analyses, particularly in empirical literature, more interesting findings are

observed. Fatima et al. (2012) find that the relationship between budget deficit and

economic growth is negative, though the “crowding out” and “crowding in” phenomena

were not studied explicitly. Mahmoudzadeh et al. (2013) conclude that the effect of a

budget deficit on private investment in developed countries is negative (“crowding out”

effect) while for developing countries, it is positive (“crowding in” effect) though the

effects are marginal for both the groups. Biza et al. (2013) mention that South Africa has

been experiencing unprecedented budget deficits since the 1960s and shows that budget

deficit significantly crowds out private investment.

Research Monograph 17 1

Bangladesh economy achieved GDP growth of 6.12 per cent at constant market prices in

FY 2013-14 and registered GDP growth rate averaging 6.2 per cent during the past five

years (MOF, Bangladesh Economic Review 2014). With a view to becoming a middle

income country within a decade, Government plans to increase the GDP growth rate to 8

per cent by 2015 and to 10 per cent by 2021 in its „Vision 2021‟. Both public investment

and private investment ought to be increased from its current level of 6.2 per cent and

20.4 per cent, respectively of GDP in FY 2013 to accelerate the GDP growth to its target

level.

To achieve the said development vision and maintain social stability, Government of

Bangladesh follows expansionary budget policy and consequently, deficit financing is

increasing due to current tax base of the country is not enough to support this expected

development vision. The tax revenue to GDP in Bangladesh is 11.6 per cent at the end of

2013-2014 whereas during the same period Malaysia, Nepal, Sri Lanka and India

maintained this ratio at 16.11 per cent, 15.3 per cent, 12.4 per cent and 11.98 per cent,

respectively (World Bank Databank 2013). It seems that Bangladesh is not at par with

these countries concerning tax–GDP ratio although Bangladesh keeps on increasing this

ratio. It forces Government to borrow from the domestic sources particularly from the

banking system as scope for concessionary external borrowing is shrinking. For instance,

Government borrowing from the banking system both in absolute term and as percentage

of GDP soared until 2012 (BB, Financial Stability Report 2012). However, thereafter it

started to decrease although budget for Government borrowing from banks and non-banks

was too high. The budget for Government borrowing from domestic sources was targeted

at Tk. 33940 crore in 2013-2014, of which Tk. 25993 crore from banks and Tk. 7971

crore from non-banks. However, the Government borrowing from the banking system

stood at Tk. 4479.5 crore till December 2013 which was 17.2 per cent of total budget

target of Government borrowing from the banking system. Additionally, different public

sector corporations of Bangladesh also borrow from banks.

Government borrowing is a much-talked issue in Bangladesh. It is often argued that

government's borrowing from commercial banks keep away private investors from getting

enough money to invest in the economy, which retards the growth of the economy.

Bankers are also wary of this effect as Government borrowing may reduce their capacity

to finance private sector sufficiently and sometimes banks, therefore, keep aloof from

Government investment although they have excess liquidity. Government also feels shy

to borrow from banks for financing essential developments like infrastructure

development in consideration of smooth channelizing of finance to the private sector.

Private sector is also concerned as it is thought that more Government borrowing will

increase interest rate on bank borrowing which will increase cost of funds of business.

With the expectation of accelerating implementation of ADP in the current fiscal year in

the improved political environment, the crowding out effect of Government borrowing

again comes back into discussion. The current study is an attempt to empirically analyze

2 Research Monograph 17

the crowding out effect of public borrowing from commercial banks on private

investment in Bangladesh to give some policy proposals to relevant authorities including

banks.

In Bangladesh perspective, Majumder (2007) conducts a research on this issue and

confirms that Government borrowing has been crowding in, not crowding out private

investment in Bangladesh. He concludes that Government can rely on domestic sources

other than Bangladesh Bank for meeting the deficit without hurting private investment as

long as excess liquidity prevails in the financial system. The paper made the conclusion

based on only cointegration analysis. However, besides cointegration, the current study

has also employed Vector Error-correction Model (VECM) and Vector Autoregressive

Model (VAR) to know direction of Granger causality in both the short and long run, if

any.

The objectives of this endeavor are to understand the pattern of fiscal deficit and

its relationship with different economic variables and then, investigate the empirical

relationship among deficit financing, crowding out and economic growth by applying

standard econometric models applicable for time series data. The study has also tried to

show the possible highest level of Govt. borrowing before witnessing any crowding out

effect in the economy.

The remaining part of the study is arranged as follows: in the second section, the existing

empirical literature on crowding out hypotheses is reviewed. The third section

summarizes theoretical framework. In the fourth section, methodology, data sources and

framework for bi-variate and multivariate time series techniques essential for estimating

the model are discussed. In the fifth section, pattern and trend of deficit budget, crowding

out and economic growth have been examined. The sixth section comprises of empirical

results and discussion. Section-7 shows possible highest level of public borrowing from

commercial banks. Finally, in the eighth section concluding remarks are outlined.

2. Literature Review

A large body of literature in the context of developed countries is found showing the

impact of budget deficit on private investment and the crowding out effect. Cebula et al.

(1981) implement three models in their study of the 'crowding out' effect of Federal

Government outlay decisions. The study examines crowding out by determining to what

degree the proportion of actual GNP that is devoted to private investment in new physical

capital is affected by the proportion of actual GNP devoted to federal Government

spending. Their new approach to the empirical dimension of the crowding out seek to

provide further insight into whether or not the crowding out issue is substantive.

The three alternative models are estimated, all of which find evidence of (a) a definite

pattern in which private investment is crowded out by Government spending and (b) only


partial crowding out. These findings are in consonance with Arestis (1979); Abrams and

Schmitz (1978); and Zahn (1978).

Dewald (1983) tests for the effects of deficits on both short- and long-term interest rates,

using two different estimating techniques. In one approach, annual data are used; in the

second approach, data are averaged over the business cycle. In either case, deficits have a

statistically significant effect on long- but not short-term rates. The author concludes that

deficits do not have a large and consistent effect on interest rates. However, an equally

important conclusion would seem to be that deficits have an effect on long-term interest

rates, although not on short-term rates. This means that deficits have an impact on

long-term consumption and investment and do not affect short term investments, hence

fiscal deficits crowded out long term investments.

On the other hand, Hoelscher (1983) constructs an empirical model of the short-term

credit market, with the interest rate on three-month Treasury bills a function of the money

base, inflation expectations, a cyclical variable-proxied by the unemployment rate and net

borrowing by the Federal Government. The results indicate that the coefficient on

Government borrowing is quite small and not statistically significant.

Makin (1983) uses a simple univariate regression equation for the changes in the

three-month Treasury bill rate as a function of either the change in the actual deficit

(relative to GNP) or the change in the high employment deficit. The coefficients for the

deficit variable are not statistically significant. Similar results of non-significance for the

fiscal variable are also reported for long-term interest rates. However, the analyses made

are said to be faulty for not including other important determinants such as the monetary

base and inflationary expectations.

According to Motley (1983), the budget deficit financed by borrowing from the private

sector leads to an increase in the supply of Government bonds, and to attract the private

sector to buy these bonds, the Government has to offer them at a low price, which

essentially implies an increase on interest rates, which in turn causes crowding out of

investment in the private sector. It is noted that the loanable funds model predicts that in

the absence of debt monetization, the effects of large fiscal deficits can lead to large

effects on interest rates. However, Brunner (1984) notes that portfolio analysis suggests

that interest rates are determined by stock demand and supply, and not by flow demands

and supply, as suggested by the loanable funds model as this can lead to either significant

or negligible effects of deficits on interest rates, depending on the sizes of accumulated

stock of debts and deficits.

In Tanzi‟s (1985) study of American statistics for the effects of Federal fiscal deficits on

the interest rate and macroeconomic performance, the results find a mixed association

between higher fiscal deficits and interest rates. The statistical significance of several

alternative fiscal measures in a model of interest rates on one-year Treasury bills is tested.


In the formulation, the interest rate is made a function of inflationary expectations using

the Livingston Index, the gap between real GNP and potential real GNP, Government

debt, total private investments as a percentage of real GDP and measures of the fiscal

deficit, including the DeLeeuw and Holloway (1985) measure of the structural deficit.

The study does not include a specific variable to capture the effects of monetary policy,

although the inflationary expectations variable may indirectly capture some aspects of

monetary policy. The results found are mixed. The sign on the structural deficit is

negative, suggesting that higher deficits lowers interest rates and positively impacts on

investment, a result that is difficult to reconcile with any theory. On the other hand, the

actual debt variable has the hypothesized positive and statistically significant effect.

Consistent with Tanzi‟s results Evans (1985) uses a conventional Keynesian model to

explain why deficits may be expected to affect interest rates which have an impact on

private investment. In his formulation, the nominal interest rate is a function of real

Government spending, the real deficit, the real money stock, and expected inflation.

While much of his analysis pertains to wartime, the period analyzed of most interest is

from October 1979 to December 1983 (Evans 1985). The study uses monthly data and

two-stage least squares estimation to deal with the problem of the endogeneity of the

deficit. In any case, the coefficient on the deficit is usually negative and statistically

significant. This result is difficult to explain with any theory, and stops short of arguments

that deficits lower interest rates. The author does, however, argue that no empirical

support can be found for the notion that deficits raise interest rates. The explanation is

that the Ricardian equivalence theorem must have held. But other interpretations are also

possible, such as that international capital mobility dominates interest rate movements for

the period, or that price controls and rationing accounts for the results for some of the

wartime periods.

Easterly et al. (1994) in their study on public sector deficits and macroeconomic

performance point out that there is a positive relationship between fiscal balances and

interest rates. This assertion is in contrast with the common prediction that deficits cause

high interest rates and surpluses low interest rates. There are a large number of negative

real interest rates in the sample study and their finding is explained by the relationship

between financial repression and fiscal deficits. Economies which go through budget

deficits risk the possibility of financing their debt through seigniorage resulting in high

inflation. The study shows little correlation between fiscal balances and inflation rates.

In their study, they acknowledge the work done by Haan and Zelhorst (1990) in their

study on the impact of Government deficits on money growth in developing countries that

the correlation between interest rates and inflation holds for countries with high inflation.

An empirical relationship between Government deficits and interest rates was published

by Ball and Mankiw (1995) in one of their study relating to the issue of Government

deficit. Their model is in the Keynesian tradition, emphasizing income determination.


In their model, the ten-year Government bond rate is made a function of the log of real

per capita Government debt, the log of real per capita non Government GNP, expected

inflation, the monetary base, and the lagged change in the dependent variable. The results

reported show that the Government debt variable has a statistically significant though

small effect, thus, revealing that budget deficits has a small effect on the level of interest

rate. In another study, taking the case of United States from the year 1960 to 1994, they

got the evidence in favor of the proposition that the persistent budget deficit reduces the

economic growth through its negative impact on private investment. The same conclusion

was found in a research made on the pattern of Government expenditures for 30

developing countries (Bose et al. 2007).

Empirical evidence on the extent of crowding out due to fiscal deficit in Indian economy

has been mixed. Patnaik (2001) finds that given the money supply, increase in deficit

may raise interest rate leading which leads to crowding out. Similarly, Lal et al. (2001)

observe that monetization of large fiscal deficits led to higher real interest rate and

crowding out of private investment. Crowding-out effect in India has been investigated by

Mitra (2006) the result of which suggests the presence of crowding-out, though

government investment had a positive impact on the economy in the long-run. Contrary to

these, Chakrabarty (2006) finds crowding in effect rather than crowding out during the

period 1970-71 to 2002-03.

The possibility of crowding out in Pakistan tested by Hyder (2001) using vector

error-correction framework found complementary relationship between public and private

investment. A study by Naqvi (2002) in the context of Pakistan also gives evidence that

past government investment has had a positive impact on private investment. Khan and

Abid (2009) using the time series data of 34 years find crowding in effect rather than

crowding out that resulted from market imperfections and excess liquidity.

Expansionary fiscal policy may result in higher level of income that may also raise

interest rate and thereby reduce private investment. Priyadarshanee and Banda (2013)

examine whether there exists such financial crowding out in Sri Lankan economy using

time series data from 1960 to 2007. The study finds no evidence of financial crowding

out, rather private investment appeared to have increased as a result of fiscal expansion.

Bista (2013) studies the relationship between domestic borrowing and private investment

in Nepal. Based on the time period from 1975 to 2011, the study finds a positive impact

of domestic borrowing on private investment.

Chowdhury (2004) examines the crowding out issue in five South Asian economies using

a VAR model. It was found that fiscal deficit does not have any significant influence on

the domestic interest of the sample countries. Budget deficit, through the expansion of

public utility services and infrastructure may improve private sector productivity. The net

impact on aggregate output of the crowding out effect of public expenditure clearly

depends on the relative strengths of these two opposite effects. The relationship between


fiscal deficit and economic growth is inconclusive because of the presence of conflicting

evidence. While some studies (e.g. Thornton 1990) have provided evidence in favour of a

net positive effect, others (e.g. Baily 1980; Feldstein 1980) have indicated a negative net

effect. Bose (2007) investigating the relationship between budget deficit and economic

growth for 30 developing countries from 1970 to 1990 finds that the budget deficit helps

the economy to grow if the deficits were due to productive expenditures such as

education, health and capital expenditures. This is also supported by the research made by

Fischer (1993). Brender and Drazen (2008) find that large and growing budget deficit in

a country gives negative signals to the citizens that the Government did not perform well

in managing the funds of a country. Hence, it will lead to low economic growth due to

lack of confidence among investors and other neighboring countries. In contrast to this, a

neutral relationship between budget deficit and economic growth is found in Saudi Arabia

(Ghali 1997). The same conclusion is supported based on the cross sectional analysis

made by Kormendi and Meguire (1985). In a recent study of BIDS covering data

spanning 1987-2011, it has been found that government borrowing from the banking

sector does not cause any crowding out effect on private investment in Bangladesh.

Public investment by borrowing from the domestic sources on infrastructure development

rather encourages private investment. The study also suggests that the government

borrowing up to 2.5 per cent of GDP will not produce any crowding out effect in the

economy. The study mentions that crowding out effect is not observed in 2011 even after

Government borrowed highest amount in that year (2.5 per cent of GDP) (Haroon 2014).

3. Theoretical Framework of Budget Deficit and Crowding Out Hypotheses

Budget deficit as a part of fiscal policy makes significant impact on some macroeconomic

indicators such as growth rate, private investment and on the composition of output mix

of an economy. Deficit budget can be financed in three ways- taxes, borrowing and

through monetization, also known as inflation tax. As narrow tax base limits financing

deficit budget and possibility of high inflation discourages financing deficit budget

through monetization, an increasing amount of budget deficit generally thus forces the

Government to go for higher borrowing from the financial sector. The impact of

Government borrowing from banks on private investment has remained a much-debated

issue in macroeconomics. The classical and monetarist view suggest that higher

Government debt crowds out private investment through reducing the availability of

loanable fund and increasing the interest rate. The extent of crowing out depends on

interest sensitivity of investment demand, firm‟s dependence on bank for raising fund and

overall investment climate. An increase in Government expenditure increases aggregate

demand in the economy. In IS-LM framework, IS curve shifts rightward due to increase

in Government expenditure and leads to higher income. Transaction demand for money

rises because of increase in income and, given a fixed level of money supply, the increase

in the transaction demand for money drives interest rate upward. As a result, firms cut

down their investment spending on plant and equipment, housing construction. Crowding


out hypothesis states that expansionary fiscal policy inevitably comes at the expense of

the private sector of the economy, unless monetary policy is accommodative. Crowding

out can be explained by using a simple macroeconomic identity namely, savings-

investment, excluding the foreign sector in the following way:

[(G-T) + I] = S

The left side of the equation shows total demand for borrowing. There are two elements

in the demand for borrowing- one is Government demand for loanable funds (G-T); and

the other is private sector demand for loanable funds intended for capital investment (I).

Right hand side shows the supply for loanable funds, i.e. national savings (S). The

equation is shown graphically in Figure-1. Equilibrium interest rate is set on i0, at the

intersection point of demand and supply for loanable funds. At this interest rate level,

the private capital level is I0. That represents private demand for loanable funds under

existing interest rates of i0. Total demand for capital shifts to the right due to increase in

Government borrowing for deficit finance as shown on Figure-1. That sets interest rate

at a higher level. However, the higher interest rate leads to lower private demand for

capital at level I1. So the private capital is crowded out by the additional Government

borrowing of loanable funds. The amount of crowding out is (I0-I1).

Figure 1: Crowding Out Effect

Source: Langdana (2009) (taken from Gaber 2010)

The neoclassical view rests on the assumption of full employment and excludes

government‟s policy interventions. Equilibrium in the market for loanable fund (equality

between savings and investment) is attained by the movement of interest rate. Interest rate

increases to bring the capital market into equilibrium when Government expands its

expenditure and thus private sector investment is crowded out.

The Keynesian approach, on the other hand, finds some logical ground in the event of

crowding out in a situation especially where there remains a considerable degree of

unemployment in the economy and interest rate sensitivity of investment is low.

Expansionary fiscal policy, even if it is debt-financed, leads to little or no increase in the


interest rate and increase output and income. There are two channels of increase in

income- one through the increase in aggregate demand in a multiple stages known as

multiplier effect and another through its impact on investment. As demand for goods and

services increases followed by expansionary fiscal policy, investment expenditure rises to

match the demand for additional goods. Therefore, there will be crowding in rather than

crowding out. However, the Keynesian analysis does not rule out the possibility of partial

crowding out. The magnitude of crowding out under the Keynesian framework depends

on the slope of both IS and LM curve. The range lies in between liquidity trap with no

crowding out and classical case with full crowding out. Keynesians agree with

monetarists on the crowding-out hypothesis only when the economy is operating at the

full-employment level. At this level of output, there remains no scope for further

expansion of output and any increase in Government expenditure shifts resources away

from the private sector. The phenomenon is sometimes called real crowding out. The

adverse effects of such type of crowding out on long-term growth can be accommodated

by financing productive sectors such as education, training, health and research.

Another dimension of crowding out takes place through the linkage of a country with the

rest of the world due to the prevalence of floating exchange rates, as demonstrated by the

Mundell Fleming Model. Higher interest rates caused by Government borrowing attract

financial capital from foreign financial markets. Under floating exchange rates, it leads to

appreciation of the exchange rate and reduces domestic exports. Crowding out situation

and its different possibilities are shown in the following box.

Figure 2: Classical and Keynesian Views of Crowding Out

Source: Prepared by Researchers


4. Methodology, Data Sources and Framework for Empirical Analysis

a. Methodology and Data Sources

In the present study, as stated earlier, understanding the pattern of fiscal deficit and its

relationship with different economic indicators and then, investigating the empirical

relationship among deficit financing, crowding out and economic growth are the focal

points. A number of graphical presentations have also been shown in the paper. The study

is entirely based on secondary data.

In addressing the first objective, the study has been devoted to examine the linkage

between fiscal deficits with other relevant economic indicators by using techniques like

correlation, percentage, Compound Annual Growth Rate (CAGR) and other simple

accounting and financial techniques. In finding out the empirical relationship, standard

econometric models applicable for time series data have been employed.

But, for the first objective, the researchers have used data sets spanning from 1980 to

2013 with some exception depending on availability and suitability. Annual data from

1974 through 2013 has been used when empirical relationship is examined through

econometrics analysis. Data are gleaned from the various publications of Bangladesh

Bureau of Statistics (BBS), Ministry of Finance (MoF) of People‟s Republic of

Bangladesh, Economic Trends and Scheduled Banks Statistics published by the

Bangladesh Bank (BB) and International Financial Statistics (IFS) of International

Monetary Fund (IMF).

b. Empirical Design

As mentioned before, the summary application of the crowding out issue is that expansion

in the Government sector inevitably comes at the expense of the private sector, unless the

money supply is expanded during the process. It leads to higher interest rate and

increased interest rate may push private sector to take less amount of loan from banks or

to take loan from foreign financial market to continue their investment. However,

crowding out of private sector happens when the economy is operating at the full

employment level. The negative effect of such type of crowding out on economic growth

can be moderated if the Government uses its deficit to finance productive investment in

infrastructure, education, training, health and research. The theoretical foundation on the

interaction among deficit financing, crowding out and economic growth has enabled us to

frame the following model. However, both bi-variate and multivariate models are used

here for cross examination of empirical results.

LPRI t = 0+ 1LGB_CB t +et ---------------------------------------------------------------- (1)

LPRI t = 0+ 1LGB_CB t +2LnY t +3 IR t +et -------------------------------- (2)

Where, PRI= Private Investment, GB_CB = Government Borrowing from Commercial

Banks, Y= Gross Domestic Products, and IR= Interest Rate. The variables in the function

are defined as follows: private investment means investment made by private


entrepreneurs no matter whether they are local or from abroad. Government borrowing

refers to part of total borrowing that is from banks other than central bank. In other words,

public borrowing figures show how much money is siphoned off from the banks‟ funds

available for potential private use. As higher fiscal deficit forces Government to take

more funds from banking system, Government borrowing from banks has been used in

the study instead of using amount or rate of fiscal deficit. GDP conveys its usual meaning

that is, value of all goods and services produced domestically, Interest rate stands for

weighted average interest rates on advances charged by different banks. Data for all

variables are taken in current price. For analytical convenience, all variables except

nominal interest rate are taken in log level. There are two reasons why variables are

converted into natural logs. First, the coefficients of the cointegrating vector can be

interpreted as long-term elasticities if the variables are in logs. Second, if the variables are

in logs, the first difference can be interpreted as growth rates. The expected signs of the

parameters are: >0, 1<0, 2>0, and 3<0. The error-term (e) is assumed to be

independently and identically distributed. The additional symbol (t) is used for

time-subscript.

First, the time series property of each variable is diagnosed under a univariate analysis by

implementing the ADF (Augmented Dicky-Fuller) for the unit root (nonstationarity)

following (Dickey and Fuller 1981; Fuller 1996). The KPSS (Kwiatkowski, Philips,

Schmidt and Shin) test for no unit root (stationarity) is applied as a counterpart of ADF

following (Kwiatkowski et al. 1992). If these tests confirm stationarity in time series data

of each variable, equation 1(one) is required to be estimated appropriately by the

Ordinary Least Square (OLS) method. Otherwise, its application leads to misleading

inferences in presence of spurious correlation (Granger and Newbold 1974).

Second, in the event of nonstationarity of each variable, the cointegrating relationship

among variables is necessary to be estimated by implementing Johansen-Juselius

procedure (Johansen 1988; Johansen and Juselius 1990, 1992) to overcome the associated

problem of spurious correlation and misleading inferences. In this procedure, all the

variables must have the same order of integration or depiction of I (d) behavior for

cointegration. In the Johansen-Juselius procedure, λmax test or λtrace test or both may be

conducted. The selection of the test is at the discretion of the researchers in view of their

trade-offs for bias, inefficiency, local power, and sample size distortions.

However, to address the issue of unequal order of integration of non-stationary variables

for long-run equilibrium relationship and causal flows, the ARDL model or bounds-

testing procedure, as suggested by Pesaran et al. (2001) will be needed to be applied.

This procedure bypasses the pre-testing for unit-root. Moreover, this is also applicable to

small sample unlike the Engle-Granger and the Johansen-Juselius procedures. In case of

ARDL model, if the calculated F-statistic is above its upper critical value, the null

hypothesis of no long-run relationship can be rejected irrespective of the orders of


integration for the time series variables. Conversely, if the calculated F-statistic falls

below its lower critical value, the null hypothesis cannot be rejected. If the calculated

F-statistic falls between its lower and upper critical values, the inference remains

inconclusive.

The evidence of cointegration, however, cannot tell us the direction of Granger causality

among the variables, i.e., which variable is leading and which variable is lagging.

That can be done by the test of the Vector Error-correction Model (VECM) that can

indicate the direction of Granger causality both in the short and long run. The following

VECM models will be established as Engle and Granger (1987) specified.

ΔlnPRIt = 0 + ECM t 1 +

p

iitPRIbi

1

ln +

p

iitCBGBci

0

_ln …………......................……………… (3)

ΔlnPRIt = 0 + ECM t 1 +

p

iitPRIbi

1

ln +

p

iitCBGBci

0

_ln +

p

iitYdi

0

ln

+

p

iitIRei

0

ln … (4)

However, in the absence of nonstationarity in time series data and cointegration, the

Vector Autoregressive (VAR) approach is applicable through dropping error correction

term from the above VECM, as outlined in Granger (1988). The appropriate lag-lengths

are selected with the aid of the FPE (Final Prediction Error) criterion (Akaike 1969) to

ensure that errors are white noise. This helps overcome the problem of over/ under

parameterization that may induce bias and inefficiency in the parametric estimates.

5. Pattern and Trend of Deficit Finance, Crowding Out and Economic Growth

5.1 Budget Deficit and GDP Growth

Budget deficit is commonly used as part of expansionary fiscal policy to increase the rate

of economic growth of a country. Table-1 shows that budget deficit as percentage of GDP

was higher than growth rates of GDP in the years 1980 and 1990. After 2000, growth rate

of GDP exceeded budget deficit as percentage of GDP almost in all years. A more clear

picture is evident in the chart. Figure-3 depicts that GDP growth rate was less than budget

deficit as percentage of GDP till the fiscal year 1994-1995. Thereafter, growth rate of

GDP started to rise and went above the relative percentage of budget deficit. The growth

rate of GDP hovered around 6 per cent in the last entire decade but budget deficit as

percentage of GDP was kept at 5.1 percent or below in the same period. The economy of

the country has, therefore, been maintaining its growth trajectory without over-depending

on budget deficit indicating the Government‟s good fiscal performance during the period.

Compound Annual Growth Rate (CAGR) of GDP stood at 4.71 per cent during

1980-2013 but amount of budget deficit increased during the same period by 12.02 per

cent as per its CAGR indicating growth rate of absolute amount of budget deficit above

than that of absolute amount of GDP. The correlation coefficient between GDP growth

rate and budget deficit as percentage of GDP is negative (-0.41) indicating negative

relationship between both the variables and GDP growth rate mostly driven by the

private sector.


Table 1: GDP Growth Rate and Budget Deficit in Bangladesh (1980-2013)

Year 1980 1990 2000 2010 2011 2012 2013

CAGR

(1980-

2013)

GDP Growth Rate (%)

CAGR of Volume of

GDP (%)

3.39 3.4 5.27 6.71 6.32 6.03 6.12

4.71

Budget Deficit as % of

GDP

CAGR of Volume of

Budget Deficit (%)

4.8 6.0 5.1 4.4 5.1 5.0 4.6

12.02

Correlation Coefficient between GDP Growth Rate and Budget Deficit as

% of GDP

-0.41

Source: BBS, Statistical Yearbook 1980-2013

Figure 3: GDP Growth Rate and Budget Deficit (as % of GDP) in Bangladesh

Source: BBS, Statistical Yearbook 1980-2013

5.2 Development and Non-Development Expenditure

Table-2 shows the trend and pattern of Govt. expenditure. The table reveals that

Govt. expenditure persistently increased during the period 1980-2013 as evident from the

year-on-year growth rate. This growth rate reached the highest percentage of 24.13 in

0

1

2

3

4

5

6

7

8

9

198

0-8

1

198

1-8

2

198

2-8

3

198

3-8

4

198

4-8

5

198

5-8

6

198

6-8

7

198

7-8

8

198

8-8

9

198

9-9

0

199

0-9

1

199

1-9

2

199

2-9

3

199

3-9

4

199

4-9

5

199

5-9

6

199

6-9

7

199

7-9

8

199

8-9

9

199

9-0

0

200

0-0

1

200

1-0

2

200

2-0

3

200

3-0

4

200

4-0

5

200

5-0

6

200

6-0

7

200

7-0

8

200

8-0

9

200

9-1

0

201

0-1

1

201

1-1

2

201

2-1

3

Per

cen

tag

e

GDP Growth Rate (%) Bugdet Deficit as % of GDP

5.26

14.67 9.01 10.88

5.54

19.71

4.44 3.36


2012 but afterwards growth rate of expenditure was somewhat tampered. Of the Govt.

expenditure, volume of non-development expenditure and development expenditure was

almost the same during 1980-2000 but thereafter non-development expenditure increased

sharply compared to development expenditure (Figure-4). The CAGR also recorded

higher for non-development expenditure, growth rate of development expenditure was

9.62 per cent whereas that of non-development expenditure was 13.81 per cent. In terms

of year-on-year growth rates, variations have been noticed. In the years 1990 and 2012,

growth rate of non-development expenditure exceeded development expenditure but in

other years higher growth rates have been observed for development expenditure. It

seems that Govt. needs to spend more money for salary, supplies, maintenance, interest

payment, subsidy, etc. More non-development expenditure may promote misallocation or

underutilization of resources although this may also bolster economic growth by putting

money into people‟s pockets. Positive correlations among total, development and non-

development expenditures are also evident from Table-2.

Table 2: Govt. Expenditure: Development and Non-development Expenditure

Year 1980 1990 2000 2010 2011 2012 2013

CAGR

(1980-

2013)

Growth of Total Expenditure (%)

CAGR of Total Expenditure (%)

13.88 12.09 13.58 17.41 17.50 24.13 17.44

12.12

Growth of Development Expenditure (%)

CAGR of Development Expenditure (%)

15.88 -3.99 17.86 24.75 27.88 15.60 26.73

9.62

Growth of Non-Development

Expenditure (%)

CAGR of Non-Development

Expenditure (%)

10.40 28.38 10.01 14.62 8.19 21.46 9.42

13.81

Correlation Coefficient between Total Expenditure and Development Expenditure

Correlation Coefficient between Total Expenditure and Non-development Expenditure

Correlation Coefficient between Development and Non-development Expenditure

0.988

0.996

0.974

Source: MoF, Bangladesh Economic Review, 1980-2013

10.97 10.03

16.99

9.50

11.45 14.40

6.57 10.42 6.84

16.36 9.70 14.12


Figure 4: Govt. Expenditure: Development and Non-development Expenditure


5.3 Government Expenditure and Private Investment

In examining the trend of development expenditure, it is seen that this grew at a

decreasing rate during the period although it is expected that this expenditure would be

growing at higher rate to achieve more GDP growth rate. On a year-on-year basis,

development expenditure as percentage of GDP was 11.67 in 1980-1981 but thereafter it

persistently decreased and reached 4.82 per cent in 2013 (Table-3). Figure-5 also

indicates the same scenario. CAGR of development expenditure calculated on the basis of

absolute figure during the period showed a moderate growth rate of 9.62 per cent.

On the other hand, private investment as percentage to GDP was at the peak point in

1996-1997 and 2010-2011 but thereafter, sluggishness was observed as it was hovering

around 16 per cent in 2012 and 2013. It is a common concern for the policy makers to

increase this ratio with a view to achieving more GDP growth rate. However, CAGR of

private investment of 14.42 per cent indicating a fair growth rate of investment. A very

high level of correlation coefficient between development expenditure and private

investment (+0.97) indicates positive influence of Govt. development expenditure on

increasing private investment.


Table 3: Govt. Development Expenditure and Private Investment

Year 1980 1990 2000 2010 2011 2012 2013 CAGR

(1980-

2013)

Total Development Expenditure

as % of GDP

CAGR of Total Development

Expenditure (%)

11.67 6.79 6.42 4.44 4.30 4.32 4.82

9.62

Private Investment as % of GDP

CAGR of Total Private

Investment (%)

9.55 5.82 15.61 19.40 16.97 16.59 16.44

14.42

Correlation Coefficient between Development Expenditure and Private Investment 0.97


Figure 5: Govt. Development Expenditure and Private Investment


5.4 Sources of Financing of Deficit Budget

In financing deficit budget, Government borrowing from domestic sources increased over

time compared to borrowing from external sources (Table-4; Figure-6) and borrowing

from the banking sector progressively emerged as the key source of deficit financing. The

domestic source financed almost 65 per cent deficit budget in 2013-2014, which was only

29.61 per cent in 1990-1991 fiscal year. The external borrowing was 70.39 per cent in

1990-1991 which came down to around 34.62 per cent in 2013-2014. Among the

domestic sources, banking sector provided 57.39 per cent finance to the Govt. in

6.57 10.42 6.84 16.99

7.90 22.52 12.879 9.99


financing its deficit budget of 2012-2013. Non-banking sources through mainly National

Saving Directorate (NSD) instruments financed 7.95 per cent of deficit budget in

2012-2013. Correlation coefficients among each variable are negative which is generally

expected, as sources of finance are alternatives.

Table 4: Sources of Financing of Deficit Budget (in %)

Year 1991 2000* 2010 2011 2012 2013 CAGR

(1991-

2013)

Share of Bank Borrowing

CAGR of Share of Bank Borrowing

18.95 22.21 27.89 52.76 62.85 57.39

4.88

Share of Non-bank Borrowing

CAGR of Share of Non-bank Borrowing

10.66 32.24 27.89 18.49 11.54 7.95

-1.25

Share of External Borrowing

CAGR of Share of External Borrowing

70.39 39.43 44.17 28.72 25.59 34.62

-3.01

Correlation Coefficient between Share of Bank Borrowing and Non-bank Borrowing

Correlation Coefficient between Share of Bank Borrowing and External Borrowing

Correlation Coefficient between Share of Non-bank Borrowing and External Borrowing

-0.79

-0.76

0.58


Note: Summation of all financing sources is not equal to 100 per cent because of error and omission.

Figure 6: Sources of Deficit Finance (in %)


19.77

-26.93

-5.91

4.43 2.31

14.81 -1.44

-3.00 1.14


5.5 Borrowing from Deposit Money Banks (DMBs), Private Investment and Total

Investment in Bangladesh

A comparative picture of Govt. borrowing from DMBs, and private investment as well as

public investment is shown in Table-5 and Figure-7. A huge oscillation of Govt.

borrowing from DMBs was observed on a year-on-year basis growth rate and this

variation has been moderate in case of private as well as total investment. As per CAGR,

Govt. borrowing from DMBs increased annually at the rate of 18.36 during 1980-2013,

but this growth rate was significantly high after 2010 as evident from CAGR of 48.96

percent during 2010-2013. However, growth rates of private and public investment were

not seemingly much influenced by high Govt. borrowing from DMBS particularly during

the years from 2010 to 2013. On a year-on-year basis, private investment grew by more

than 12 per cent in 2010 and onwards which was 10.22 per cent and 8.88 per cent in 1990

and 2000. CAGR of private investment and Govt. investment were 14.42 per cent and

13.79 per cent, respectively even after high Govt. borrowing particularly in the last few

years of our total sample period. Figure-7 also reveals that increased amount of Govt.

borrowing from DMBs act as complementary in gradual growth of private investment.

The calculated coefficient of correlation among variables also indicates that high positive

relationship exists among variables. Even correlation between growth rate of borrowing

from DMBs and private investment is highly positive (0.947).

Table 5: Borrowing from DMBs, Private Investment and Total Investment in

Bangladesh

Year 1980 1990 2000 2010 2011 2012 2013 CAGR (1980-

2013)

Growth Rate of Borrowing from

DMBs (%)

CAGR of Volume of Borrowing

from DMBs (%)

18.46 1.56

25.46

9.88 26.9 28.85 48.65

18.36

Growth of Private Investment

CAGR of Volume of Private

Investment (%)

38.19

10.22

8.88

12.05

15.41

12.65

12.58

14.42

Growth of Total Investment (%)

CAGR of Volume of Total

Investment (%)

25.20

10.84

11.96

14.00

18.21

16.17

19.70

13.79

Correlation Coefficient between Growth Rate of Borrowing from DMBs and Private Investment

Correlation Coefficient between Growth Rate of Borrowing from DMBs and Total Investment

Correlation Coefficient between Private Investment and Total Investment

0.947

0.961

0.998

Source: BBS, Statistical Yearbook, 1980-2013

13.3 18.79 14.51 48.96

9.67 18.99 11.22 13.23

7.90 22.52 12.87 9.99


Figure 7: Borrowing from DMBs, Private Investment and

Total Investment in Bangladesh

Source: BBS, Statistical Yearbook, 1980-2013

5.6 Borrowing from DMBs and Interest Rate

Crowding out effect theorizes that once public authorities borrow from the domestic

market, there emerges a fund crisis due to excess demand, which raises interest rate

leading to the reduction of private investment. Table-6 and Figure-8 indicate that there is

a slight impact of ups and downs of govt. borrowing on lending interest rate. The CAGR

of Govt. borrowing from DMBs during 1980-2013 was 18.36 per cent but CAGR of

interest was only 0.13 per cent during the same period (Table-6). Figure-8 shows that

Govt. borrowing increased sharply in the years 1982-1983, 1991-1992 and 2007-2008 but

interest rate was almost stable in those years. On the other hand, almost non movement or

a minor movement of interest rate was observed in the years 1984-1985, 1995-96,

2001-02 and 2005-06 although year-on-year growth rate of borrowing was negative in

those years (Figure-8). The correlation coefficients between growth rate of public

borrowing from DMBs and interest rate is negligible (0.08). It indicates that interest rate

is almost non-sensitive to public borrowing. In other words, we can say that public

borrowing does not crowd out private investment.


Table 6: Growth Rate of Borrowing from DMBs and Interest Rate

Year 1980 1990 2000 2010 2011 2012 2013 CAGR

(1980-

2013)

Growth Rate of Borrowing

from DMBs (%)

CAGR of Volume of

Borrowing from DMBs (%)

18.46 1.56

25.46

9.88 26.9 28.85 48.65

18.36

Interest Rate (%) 13.07 14.83 13.86 11.31 12.42 13.75 13.67 0.13

Correlation Coefficient between Growth Rate of Borrowing from DMBs and Interest Rate 0.08

Sources: BBS, Statistical Yearbook, 1980-2013 and BB, Monthly Economic Trend, 1980-2013

Figure 8: Growth Rate of Borrowing from DMBS and Interest Rate (1980-2013)

Sources: BBS, Statistical Yearbook, 1980-2013 and BB, Monthly Economic Trend, 1980-2013

6. Empirical Results and Discussions

In this section, we test the dynamics between private investment, Government borrowing

from commercial banks, gross domestic products and interest rate as per following

sequences.

Unit Root Tests

The results of the Augmented Dickey-Fuller (ADF) and the Kwiatkowski-Phillips-

Schmidt-Shin (KPSS) tests on the series in levels and first differencing are placed in

Table-7. According to the results, we cannot reject the null hypothesis of unit root for any

variable in the levels using ADF and KPSS tests. However, when we take first difference

of these variables and perform ADF and KPSS tests again, we reject the null hypothesis

of unit root of each variable. Thus, we conclude that the variables are integrated of first

order or I(1).

13.35 18.79 14.51 48.96


Table 7: ADF and KPSS Tests Results

ADF KPSS

Variables Level First Differ Level First Differ

LPRI -0.648453 -7.419194 0.771180 0.100732

LGB_CB 0.386102 -5.389784 0.768626 0.077139

LY 0.798282 -6.467416 0.771425 0.136306

Int -2.6250377 -4.947173 0.168627 -

Source: Researchers‟ Calculation

Notes: *The MacKinnon (1996) ADF critical values are –3.752946 and –2.998064 at 1% and 5% levels of

significance, respectively. The KPSS (Kwiatkowski et al. 1992) critical values are 0.73900 and 0.46300 at the

aforementioned levels of significance, respectively.

Cointegration: First, we present the Johansen‟s cointegration test results for bi-variate

cases between private investment and Government borrowing from commercial banks

and thereafter we perform this test for multivariate cases covering two more independent

variables. Table-8 displays the results of the bi-variate case. The null hypothesis is that

there is no „conintegrating relationships among the specified variables. For private

investment and Government borrowing from commercial banks, we cannot reject the null

hypothesis. Thus, we conclude that these variables are not conintegrated. It means that

there is no long run theoretical relationship or equilibrium relationship between private

investment and Government borrowing from banks. Both λtrace Statistic λmax test results

support this finding.

Table 8: Johansen-Juselius Cointegration Test

Hypotheses

λtrace Statistic λmax Statistic

λtrace 0.05 Critical

Values Prob λmax

0.05 Critical

Values Prob

None (H0: r = 0) 11.70687 15.49471 0.1715 11.65557 14.26460 0.1243

At most 1 (H0: r ≤ 1) 0.051304 3.841466 0.8208 0.051304 3.841466 0.8208


Note: Trace and max test indicates no cointegration at the 0.05 level

Table-9 presents the cointegrating results of the multivariate cases where we have added

GDP in current price and interest rate. When we examine conintegration among private

investment, Government borrowing from banks, GDP in current price and interest rate,

the null hypothesis of no cointegration cannot be rejected at the 5 per cent level by λtrace

Statistic. However, λmax Statistic (Max-eigenvalue test) indicates 1 (one) cointegrating

relationship among variables at the 0.05 level. The Monte Carlo experiments reported in

Cheung and Lai (1993) suggest that the trace test shows more robustness to both

skewness and excess kurtosis in the residuals than the maximum Eigen value. Moreover,

as shown above in the bi-variate case between private investment and Government

borrowing from banks, both λtrace Statistic and λmax Statistic cannot reject null hypothesis

of no cointegration at the 5 per cent level.


In the light of the above evidence, we conclude that these variables are not cointegrated.

It implies that there is no common force that brings the private investment, Government

borrowing from the banking sector, GDP in current price and interest rate together in the

long run.


Hypotheses



Values Prob λmax

0.05 Critical

Values Prob

None (H0: r = 0) 41.43512 47.85613 0.1752 28.48383 27.58434 0.0383

At most 1(H0: r ≤ 1) 12.95129 29.79707 0.8938 7.027549 21.13162 0.9528

At most 2 (H0: r ≤ 2) 5.923746 15.49471 0.7045 5.911308 14.26460 0.6246

At most 3 (H0: r ≤ 3) 0.012438 3.841466 0.9110 0.012438 3.841466 0.9110

Trace test indicates no cointegration at the 0.05 level

Max-eigen value test indicates 1 cointegrating eqn(s) at the 0.05 level


Vector Autoregressive Model

As we fail to get the conintegrating relationship among variables (Tables-8 and 9),

we estimate here Vector Autoregressive Model (VAR) by the exclusion of the

error-correction term for Granger Causality with short-term interactive relationship

(Granger 1988). The bi-variate estimation between private investment and Government

borrowing is reported in Table-10. The table reveals that preceding year‟s private

investment has profound influence on current year‟s private investment as reflected

through the associated t value. In other words, previous years‟ well-built private

investment boosted up the current year private investment. In case of short-term

relationship between private investment and Government borrowing, it is found that

current year and preceding second year‟s borrowing from banking sector have positive

relationship with the current year private investment. This relationship is statistically

significant in case of impact of preceding second year‟s borrowing on current year

investment (t-value=2.573557) whereas contemporary relationship is not statistically

significant (t-value=1.348998). It means that more Government borrowing in current and

preceding second year leads to an increase in current year private investment. As a result,

existence of short term crowding in effect seems evident in the economy of Bangladesh.

However, previous year‟s Government borrowing has only a subdued negative impact on

the current years investment (t-value= -1.507954).

The numerical value of adjusted R2 and F-statistics is substantially high. However, the

DW-value at 1.600011 indicates a positive auto-correlation.


Table 10: VAR Estimates in Case of Bi-variate Analysis

Variable Coefficient Std. Error t-Statistic Prob.

C 0.613184 0.178556 3.434131 0.0017

LPRIV(-1) 0.891683 0.162909 5.473485 0.0000

LPRIV(-2) -0.168569 0.155360 -1.085021 0.2863

LGB_CB 0.175776 0.130301 1.348998 0.1871

LGB_CB(-1) -0.290603 0.192714 -1.507954 0.1417

LGB_CB(-2) 0.380003 0.147657 2.573557 0.0151

R-squared 0.994299

Adjusted R-squared 0.993379

Durbin-Watson stat 1.600011

F-statistic 1081.278

Prob (F-statistic) 0.000000


In case of multivariate analysis (Table-11), impact of preceding year‟s investment and

current and preceding second years‟ Government borrowing from the banking system on

current year investment is almost same like bi-variate estimation. Additionally, current

year Government borrowing from the banking system is profoundly contributing to the

increase of private investment as reflected through associated t-value. It again confirms

with statistical significance that there is no crowding out effects in Bangladesh, rather, the

crowding in effect in short term is evident. One discernible finding is that current year

interest rate has negative relationship on current year investment with statistical

significance (t= -2.117010). To add further, a high interest rate discourages current year

private investment very much.

The numerical value of adjusted R2 at 0.995285 shows that the current investment is

explained overwhelmingly by the explanatory variables. The F-statistics at 691.7701 is

also substantially high. The DW-value at 1.875048 indicates a marginal positive

auto-correlation.


Table 11: VAR Estimates in Case of Multivariate Analysis


In examining structural stability, Cumulative Sum (CUSUM) and Cumulative Sum of

Squares (CUSUMSQ) are plotted in Figures-9 and 10. These figures show that both

CUSUM and CUSUMSQ plotted from a recursive statement of the model lie within the

5% critical bound. Thus, parameters of the VAR do not suffer from any structural

instability, i.e. there is strong evidence in favor of stable parameters.

Figure 9: CUSUM of Recursive Residuals


-20

-15

-10

-5

0

5

10

15

90 92 94 96 98 00 02 04 06 08 10 12

CUSUM 5% Significance

Variable Coefficient Std. Error t-Statistic Prob. C 3.079577 1.063644 2.895307 0.0078

LPRIV(-1) 0.652218 0.160258 4.069811 0.0004

LPRIV(-2) 0.086252 0.156708 0.550401 0.5869

LGB_CB 0.295894 0.128870 2.296068 0.0303

LGB_CB(-1) -0.280440 0.166154 -1.687829 0.1039

LGB_CB(-2) 0.452047 0.133281 3.391684 0.0023

LY -0.245003 0.373880 -0.655297 0.5183

LY(-1) 0.256131 0.492920 0.519620 0.6079

LY(-2) -0.308963 0.322854 -0.956976 0.3477

INT -0.069132 0.032655 -2.117010 0.0444

INT(-1) -0.009067 0.048838 -0.185657 0.8542

INT(-2) 0.029870 0.032570 0.917100 0.3679

R-squared 0.996725 Mean Dependent Var 11.97461

Adjusted R-squared 0.995285 S.D. Dependent Var 1.702945



Durbin-Watson Stat 1.875048


Figure 10: CUSUMSQ of Recursive Residuals


7. Possible Highest Level of Public Borrowing from Commercial Banks

Government borrowing from banks is not a new phenomenon for developing countries.

Abbas (2007); and Abbas & Christensen (2007) show that bank-holdings of domestic

public debt in low income countries were about 5.5 per cent of GDP in the 1975-1985

period and increased to 8.4 per cent of GDP in the 1996-2004 period. The increase was

particularly large in emerging market countries, where bank-holdings of public debt went

from 7.8 to 14.3 per cent of GDP. In this perspective, a common question is that what

should be the highest level of Government borrowing from banks in Bangladesh before

witnessing any crowding out effect in the economy. In addressing this issue, the study has

followed trial and error method, and increased the amount of public borrowing from

banks up to 3 per cent of GDP for examining the empirical relationship. First,

cointegrating relationship has been checked in this respect.

Table-12 shows that the null hypothesis of at most one conintegrating relationship is

accepted at the 5 per cent level by λtrace and λmax Statistic. It means that conintegrating

relationship exists among private investment, Government borrowing from commercial

banks (3% of GDP), GDP in current price and interest rate although cointegrating

relationship is not found when we consider annual actual amount of Government

borrowing from banks (Tables-8 and 9). It implies that when Government borrows

3 per cent of GDP from banks then a common force brings the private investment,

Government borrowing from the banking sector, GDP in current price and interest rate

together in the long run.

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

90 92 94 96 98 00 02 04 06 08 10 12

CUSUM of Squares 5% Significance



Hypotheses



Values Prob λmax

0.05 Critical

Values Prob

None (H0: r = 0) 727.6122 47.85613 0.0001 708.7146 27.58434 0.0001

At most 1 (H0: r ≤ 1) 18.89765 29.79707 0.5003 13.97874 21.13162 0.3668

At most 2 (H0: r ≤ 2) 4.918906 15.49471 0.8174 4.917423 14.26460 0.7522

At most 3 (H0: r ≤ 3) 0.001483 3.841466 0.001483 3.841466 0.9675

Trace test indicates 1 cointegrating eqn(s) at the 0.05 level

Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level

* denotes rejection of the hypothesis at the 0.05 level


However, cointegration, however, cannot tell us the direction of Granger Causality

between the variables as to which is leading and which variable is lagging (i.e. which

variable is exogenous and which variable is endogenous). For the endogeneity and

exogeneity of the variables of the variables, we can apply Vector Error Corection Model

(VECM). As conintegration relationship is found, we are now moving to know the long

term as well as short term relationship through VECM. Table-13 reveals that coefficient

of error correction term have the expected negative sign for long-run convergence without

statistical significance. There is evidence of subdue long-term crowding out effect of

public borrowing from banks on private investment as reflected through the negative

coefficient of the error correction term without statistical significance. In examining short

term effect, Government borrowing from commercial banks in the preceding year without

statistical significance and preceding second year with statistical significance has negative

impact on the current year private investment. It also favors short-term crowding out

effect. However, insignificance of F-statistics reveals weak evidence in favor of this

conclusion. As a whole, we can conclude that Government can borrow from the banking

sector up to 3% of GDP without any hesitation. In this case, banks will get more safe

investment opportunities without upsetting the growth of private investment and

consequently debt securities market is expected to be enriched with more securities and

investors which is also a keen pillar of a healthy financial system of a country.


Table 13: VECM Estimates in Case of Multivariate Analysis

Variable Coefficient t-Statistic Prob.

C 0.225431 2.588428 0.0156

RES(-1) -0.151680 -1.233239 0.2285

D(LPRIV(-1)) 0.088574 0.458421 0.6505

D(LPRIV(-2)) 0.017723 0.091628 0.9277

D(LY(-1)) 966.8755 1.238944 0.2264

D(LY(-2)) 1536.278 2.064105 0.0491

D(LGB_CB (-1)) -0.665382 -1.239458 0.2262

D(LGB_CB (-2)) -0.177320 -2.064491 0.0491

D(INT(-1)) -0.015741 -0.349978 0.7292

D(INT(-2)) -0.024242 -0.547523 0.5887

R-squared 0.298867 Mean Dependent Var 0.152463

Adjusted R-squared 0.056167 S.D. Dependent Var 0.153115



Durbin-Watson Stat 2.200544


8. Concluding Remarks

The presence of crowding out effect of Government borrowing on private investment has

been examined in the study. With a view to accomplish this objective, a model for

investment function has been estimated considering Government borrowing from the

banking system, GDP in current price and interest rate as independent variables.

The main finding of this study is that there is no long-run relationship among variables.

However, in case of short-term relationship, findings of the study confirmed with

statistical relationship that there is no crowding out effects in Bangladesh, rather, the

crowding in effect is evident.

Crowding out effect of Government borrowing takes place mainly due to shortage of

funds in the banking sector. The banking sector of Bangladesh has long been

characterized by excess liquidity resulting in fund crisis of crowding out effect does not

work in the economy. In other words, Government borrowing from the commercial banks

does not appear to exert any negative impact on private investment by creating fund

crisis. Moreover, crowding in effect may be explained in the context of economic

scenario of Bangladesh. Every year, a large amount of government-borrowed money is

spent as transfer payment for promoting private sector investment and growth of

agriculture sector. Private investment in a number of areas is enjoying tax exemption.

Apart from cash incentives the facilities in the form of income tax exemption, tax holiday,

duty-draw-back and duty free imports in particular areas are available for private

industries. Farmers are getting subsidy in the form of reduced price of agriculture inputs.

A substantial amount of Government funds flows towards poor people under social safety


network which increases consumption of products produced by private sector. It can be

inferred that private investment is encouraged by subsidy and transfer payment programs

to the industrial sector as well as same to consumers particularly poor people. Amount

necessary for subsidy and transfer payment compels Government to borrow from the

banking sector. Another explanation of crowding in phenomenon is irregularities in

implementing Annual Development Programs (ADPs) financed through Government

borrowing by the involved officers, contractors and politicians. It results in transfer of

public funds to the private sector and excess spending in the form of consumption as well

as investment.

In general, public borrowing taken to finance ADP is supposed to be complementary to

the private economic activities. ADP mostly spent for infrastructure development

encourages more private investment through offering good environment for private

investment and outsourcing many tasks to the private enterprises in completing

Government projects. Crowding in is, therefore, a consequence of public borrowing.

It may be summed up that short term crowding in effect is evident in Bangladesh

economy and many reasons of imperfect market of Bangladesh are available to support

crowding in argument. The results of study have important implications for bankers and

authorities responsible for fiscal management. Existence of excess liquidity after giving

loan to the private sector and sustainable public debt scenario together put bankers to lend

more to the government. The fiscal authority is also in a position to foster private

investment and hence economic growth through increasing public expenditures backed by

borrowing from the banking system.

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Appendix

Discussion Summary on National Seminar on “Deficit Financing, Crowding Out and

Economic Growth: Bangladesh Perspective”

Bangladesh Institute of Bank Management (BIBM) arranged a national seminar on

“Deficit Financing, Crowding Out and Economic Growth: Bangladesh Perspective” on

November 22, 2014. Mr. Md. Abul Quasem, Chairman, Executive committee of BIBM

and Deputy Governor, Bangladesh Bank was present in the seminar as the chief guest.

Mr. Md. Abdus Salam, CEO & Managing Director, Janata Bank Limited; Mr. M. Shah

Alam Sarwar, Managing Director & CEO, IFIC Bank Limited; and Dr. Md.

Akhtaruzzaman, Economic Advisor, Bangladesh Bank were present in the seminar as

designated discussants. Mr. S. A. Chowdhury, A. K. Gangopadhaya Chair Professor,

BIBM chaired the occasion. A total number of 200 participants including chief

executives, high officials of different banks, academicians, media representatives and

faculty members & students of BIBM participated in the seminar. The summary of

seminar discussion on the paper is as follows:

Comments of the Chief Guest

Mr. Md. Abul Quasem, Chairman, Executive Committee of BIBM, and Deputy

Governor, Bangladesh Bank underscored the importance of the subject. He mentioned

that government is very conscious about taking loan from the banking sector. He added

that government mostly borrows from banks for investments in development work.

Comments of the Chairman

Mr. S. A. Chowdhury, A. K. Gangopadhaya Chair Professor of BIBM accentuated the

importance of the subject matter of the seminar and expected that the findings of this

study will be considered with priority in the policy making process of the government.

Comments of the Discussants

Mr. Md. Abdus Salam, CEO & Managing Director of Janata Bank Limited told that

deficit financing is observed in the budget. He added that budget deficit is financed from

various sources including external and internal sources. The sources include central bank,

commercial banks, government saving instruments, etc. He told that deficit financing has

a positive inflationary impact and a negative impact on investment in the society. The

side effect is crowding out, crowding in. In his opinion when we say crowding out

government is taking the responsibility to provide goods and services in which case

private sector will be driven out. He also suggested using data upto 2014 for the analysis.

Mr. M. Shah Alam Sarwar, Managing Director & CEO of IFIC Bank limited appreciated

the researchers for doing research on crucial subject and presenting a well written paper.

He told that private investment is one of the factors of economic growth, not a total


gematic term for economic growth. He added that economic growth is not only dependent

on economic parameter but also on some other non-economic factors such as governance,

administration of fund etc. But he pointed out that it is very difficult to incorporate those

factors in research model as we lack proper data base related to those parameters. He told

that on the one hand banking sector has liquidity; on the other hand interest rate is not

declining. He doubted whether interest rate is a determinant of the level of private

investment. He opines that other factors may influence the demand/ supply of loanable

funds by the private sector.

Dr. Md. Akhtaruzzaman, Economic Advisor, Bangladesh Bank has pointed out that

another research paper can be produced by taking into consideration of other economic

variables such as industrial production volume index as a proxy of scale variable

representing economic growth. He suggested to use industrial production volume index as

dependent variable instead of GDP in order to increase the number of observation as the

larger the number of observation, more robust the result will be in case of time series

econometric analysis. He also suggested providing the explanation of the findings of the

inverse relationship between interest rate and private sector credit demand which is

already a finding of the paper but some further explanation can be given in the finding

part of the paper. He added that government borrowing from the central bank should also

be considered along with government borrowing from commercial banks in order to get

more robustness in the result as well as research findings for supporting crowding in

effect in the perspective of Bangladesh economy. The reason is that when government

borrows from the central bank there is a currency implication as money supply will

increase in the economy and private sector credit may increase due to increase in money

supply which may lead to crowding in phenomenon. He added that some literatures from

peer countries such as India, Sri Lanka, Vietnam, etc. can be incorporated to compare the

findings of those countries with Bangladesh perspective which will enrich the paper.

Some Key Points Highlighted by the Participants

Proxy variable of private sector investment may be more clarified with supporting

literatures and more variables representing private investment can be included.

Whether crowding in effect found in the paper has been occurring due to government

borrowing from commercial banks or due to private borrowing from foreign banks/

institutions can be investigated.

Neighbouring country experiences regarding government borrowing and its impact on

private sector can be incorporated in the paper.

More literature reviews particularly related to crowding out and economic growth can

be added to enrich the paper.

External borrowing and FDI could be included in the government borrowing.


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