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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
Dr. Prashanta Kumar Banerjee
Abed Ali
Md. Mohiuddin Siddique
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)
Plot No. 4, Main Road No. 1 (South), Section No. 2
Mirpur, Dhaka-1216, Bangladesh
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Printed by Nahida Art Press, 64/F, R.K. Mission Road, Dhaka, Bangladesh.
Copyright © BIBM 2016, All Rights Reserved No part of this report may be reproduced or utilized in any form or by any means, electronic
or mechanical, including photocopying, recording or by any information storage and
retrieval system, without the permission of the publisher
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.
Dr. Prashanta Kumar Banerjee
Abed Ali
Md. Mohiuddin Siddique
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
Research Monograph 17 3
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.
4 Research Monograph 17
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.
Research Monograph 17 5
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
6 Research Monograph 17
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
Research Monograph 17 7
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
8 Research Monograph 17
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
Research Monograph 17 9
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
10 Research Monograph 17
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
Research Monograph 17 11
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.
12 Research Monograph 17
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
Research Monograph 17 13
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
14 Research Monograph 17
Figure 4: Govt. Expenditure: Development and Non-development Expenditure
Source: MoF, Bangladesh Economic Review, 1980-2013
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.
Research Monograph 17 15
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
Source: MoF, Bangladesh Economic Review, 1980-2013
Figure 5: Govt. Development Expenditure and Private Investment
Source: MoF, Bangladesh Economic Review, 1980-2013
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
16 Research Monograph 17
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
Source: MoF, Bangladesh Economic Review, 1991-2013
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 %)
Source: MoF, Bangladesh Economic Review, 2006-2013
19.77
-26.93
-5.91
4.43 2.31
14.81 -1.44
-3.00 1.14
Research Monograph 17 17
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
18 Research Monograph 17
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.
Research Monograph 17 19
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
20 Research Monograph 17
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
Source: Researchers‟ Calculation
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.
Research Monograph 17 21
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.
Table 9: 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) 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
Source: Researchers‟ Calculation
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.
22 Research Monograph 17
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
Source: Researchers‟ Calculation
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.
Research Monograph 17 23
Table 11: VAR Estimates in Case of Multivariate Analysis
Source: Researchers‟ Calculation
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
Source: Researchers‟ Calculation
-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
F-statistic 691.7701
Prob (F-statistic) 0.000000
Durbin-Watson Stat 1.875048
24 Research Monograph 17
Figure 10: CUSUMSQ of Recursive Residuals
Source: Researchers‟ Calculation
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
Research Monograph 17 25
Table 12: 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) 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
Source: Researchers‟ Calculation
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.
26 Research Monograph 17
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
F-statistic 1.231426
Prob (F-statistic) 0.319181
Durbin-Watson Stat 2.200544
Source: Researchers‟ Calculation
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
Research Monograph 17 27
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
Research Monograph 17 33
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.
34 Research Monograph 17
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