Expenditure-growth nexus: does the source of finance matter? Empirical evidence from selected South Asian countries.
Ul Husnain, Muhammad Iftikhar
The study employs the Fixed Effect Model on a panel of four South
Asian countries viz., Pakistan, India, Sri Lanka, and Nepal, for the
period 1975-2008 to investigate if the source of finance matters in
determining the impact of public expenditure on growth. The analysis
shows that the source of finance does matter. Seigniorage-financed
public expenditure has a larger negative effect on growth, followed by
debt-financed and tax-financed public expenditure. Therefore, financing
of public expenditure through taxes is the least costly option available
with the governments in low-income countries. In general, fiscal
discipline through cuts in public spending is required to boost economic
growth.
Kevwords: Public Expenditure, Debt Financed, Tax Financed,
Seigniorage, Economic Growth
1. INTRODUCTION
Government can generate revenues to finance its expenditure in
three major ways i.e., taxes, bonds and seigniorage. (1) Interestingly,
public expenditure financed through different sources affect growth
differently. Which source of finance is less distortionary? is a
question that has attracted great attention over the years. However, no
consensus is available on the relative importance of the financing
source.
The prominent work on this issue relates to Miller and Russek
(1997) who provide a detailed discussion over the relative importance of
tax financed and debt financed increases in government expenditure in
terms of economic growth and report that the results vary considerably
as the source of finance differs. (2) Similarly, Bose, Holman and
Neanidis (2005) compare the effect of tax financed and seigniorage
financed increases in public expenditure on economic growth. (3)
Likewise, Palivos and Yip (1995) analyse the effects of tax financed and
money financed government consumption expenditure on economic growth and
social welfare within a framework of endogenous growth model. Latter, in
another study Espinosa-Vega and Yip (1999) study the effects of money
financed and tax financed increases in government consumption
expenditure on inflation and economic growth.
These studies have a common limitation that they do not examine the
effects of taxes, bonds and seigniorage individually. The results may
vary when all the three sources are taken into account simultaneously.
This study attempts to consider major sources of public finance
simultaneously to measure precise effect of public expenditure on
growth. The knowledge regarding the relative importance of different
sources of finance is critically important for the decision makers
especially in developing countries where high fiscal deficits persist.
The rest of the study is organised as follows; Section 2 describes data
and variables. Section 3 presents model and econometric methodology.
Section 4 comprises results. Section 5 concludes the study with some
policy implications.
2. DATA AND VARIABLES
The analysis employs panel data for four South Asian countries
viz., Pakistan, India, Sri Lanka and Nepal (4) over the period
1975-2008. Variables are categorised into two groups, fiscal and non
fiscal variables. Fiscal variables comprise public expenditure, public
revenues and government surplus/deficit. Trade openness, population
growth and investment (5) are the non fiscal/conditional variables. All
variables are measured as a share of GDP except growth in per capita GDP, the dependent variable, and population growth. Variables come from
three sources i.e., World Development Indicator (WDI), Government
Finance Statistics (GFS) and International Finance Statistics (IFS).
3. THE MODEL AND ECONOMETRIC METHODOLOGY
We start our model by defining the growth rate of per capita GDP as
under. (6)
git = [lny.sub.it] - [lny.sub.it-1] ... (1)
Where [g.sub.it] is growth in per capita GDP in country i at time
t. y is the Gross Domestic Product per capita, In is the natural
logarithm operator. Let [X.sub.it] be the vector of non
fiscal/conditional variables that generally appear in growth regressions
and [W.sub.jt] be the budget constraint, (7) the model can be written as
under;
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (2)
Where [u.sub.it] is the error term. The error term [u.sub.it]
captures, as usual, the impact of omitted variables. The critical
assumption about error term in classical regression model is that it is
independent and identically distributed. In pooled cross-section time
series analysis these omitted variables can be further categories into
three groups. Hence, the error term can be written as;
[u.sub.it] = [alpha][C.sub.i] + [delta][T.sub.t] + [[pi].sub.it]
... (3)
Where [C.sub.i] denotes the variation in cross country variables
such as climate and geography (8) and [alpha] measures the effect of
these variables. [T.sub.t] shows the time variant but country invariant variables such as world economic conditions, technological changes,
external effects such as war and [delta] captures the influence of these
factors. [pi] is the measure of both country and time variant variables.
Now by substituting Equation (3) into Equation (2) the model takes the
following form:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] (4)
The estimation of above equation by ordinary least square method
will yield misleading results if the country specific and time specific
effects are ignored. (9) To avoid this bias we apply Fixed Effect Model
(FEM). (10) An alternative to FEM is Random Effect Model (REM) but our
choice is biased towards FEM. (11)
3.1. Government Budget Constraint
Government budget constraint can be written as an identity:
[EXPN.sub.jt] = [NTR.sub.jt] + [TR.sub.jt] + [D.sub.jt] +
[S.sub.jt] ... (5)
Where EXPN is the total government expenditure including interest
payments on debt. NTR is non tax revenue, TR is tax revenue, S is the
seigniorage used to finance budget deficit and D is the debt financing or rest of the budget financing. (12) The left hand side of the above
identity shows total expenditure while right hand side is the total
revenues from different sources. Inclusion of all the above components
of budget constraint into Equation (4) will give rise to the problem of
perfect collinearity as budget constraint is an identity. So, to avoid
this (at least) one of the components of budget constraint must be
omitted from the regression equation. The excluded element becomes an
implicit source of financing of expenditure as it can change freely. For
example if we omit [D.sub.it] and include all other elements in Equation
(4) then coefficient attached with public expenditure captures the
impact of debt financed increases in public spending on economic growth
as the other sources of finance do not change. Likewise, other financing
source i.e., tax and debt can be excluded in turn. (13) This taxonomy
has been adopted from Ahmed and Miller (2000), Miller and Russek (1997)
and Bose, Holman and Neanidis (2005).
4. RESULTS
As mentioned earlier, Fixed Effect Model (FEM) is used to estimate
different specifications. Table 1 shows the estimation output.
We start our discussion with the result for conditional variables.
Openness variable conveys generally a consistent story over time. It
remains highly significant with a positive sign in all the
specifications. This means that trade openness has exerted positive
effect on the economic growth of this region. This finding is consistent
with the existing empirical literature. (15)
Population growth, contrary to general perception, shows a positive
impact on growth in this region. It reveals that labour force has
contributed to the output of these economies over time. The reason for
this result may be the highly dependence of these economies on
agriculture sector that absorbs a large number of people and contributes
significantly to output of the country. This finding is similar to that
of Hakro (2009) who states that labour force is positively and
significantly associated with economic performance of the developing
South Asian nations. This suggests that government should spend on
education, training and skills as these facilities will enhance the
productivity of the workers. However, this finding is contrary to
Siddiqui and Malik (2001) who report that population growth is
negatively associated with growth in South Asia.
The results reported in Table 1 also show that public investment
has triggered growth in South Asia which highlights the role of
infrastructure in stimulating economic growth in developing countries.
This can be explained in terms of either underinvestment on the part of
private sector or the greater marginal productivity of public sector
resources. It suggests that scarce government expenditure should be
directed to increase new human capital along with the maintenance of the
existing stock of human capital. The findings are in conformity with the
findings of Knight, Loayza and Villanueva (1993), Ahmed and Miller
(2000), Ramirez and Nazmi (2003) and Amanja and Morrissey (2005) who
report that public investment is positively associated with economic
growth in developing countries.
Now the results of fiscal variables, in which we are interested
more, are discussed. Table 1 clearly brings out that the method of
financing has a crucial role in determining the effects of government
spending on economic growth. It is found that tax financed increases in
public spending are negatively associated with per capita GDP growth.
The findings of Barro (1990) support our results. He states that tax
financed public spending, mainly income tax on investment reduce profits
on private investment, and thus affect growth negatively. However,
Miller and Russek (1997) report results that are contrary to our
findings. They conclude that tax financed expenditure are pro growth for
the group of developing countries.
It is also found that debt financed increases in government
expenditure also affect growth negatively. Similar conclusion is reached
by Miller and Russek (1997) who point out that debt financed increases
in public spending are negatively associated with growth in developing
countries. Likewise, Siddiqui and Malik (2001) conclude that debt
accumulation has affected growth negatively in Pakistan, India and Sri
Lanka. They also report that all the debt indicators show significant
negative relationship with growth.
As well as money financed expenditure are concerned, the findings
are not different from the previous two findings. It is concluded that
money financed expenditure produces a significant decrease in economic
growth for selected South Asian countries. The similar results are also
reported by Bose, Holman and Neanidis (2005). They conclude that
seigniorage financed public expenditure retards growth in developing
countries.
The results derived from the analysis highlight the relative
importance of different sources of financing public expenditure in
context of economic growth. It is inferred that though expenditure exert
negative effect financed through any source on growth yet they can be
ranked according to their relative effects. Tax financed expenditure
hurts growth least followed by debt financed and seigniorage financed
expenditure. This ranking is based on the magnitude of the coefficients
attached with public expenditure in different specifications. The
negative effect of seigniorage is largest as compare to debt financed
and tax financed public expenditure i.e., ([absolute value of -0.51]
> [absolute value of -0.40|]> [absolute value of -0.33]).
The findings that public expenditure is negatively correlated with
economic performance in South Asia mentions the inefficiency of the
public sector in this region. The reason of this negative effect of
public expenditure on growth may be the higher share of non development
expenditure in total expenditure. Furthermore, politicisation of public
resources can also explain this negative relationship between public
expenditure and economic growth. It is also possible that the government
size may have risen above the threshold level. The larger negative
effect of monetisation of public deficit reveals that the high inflation
has caused much to these economies. Tax financed expenditure hurt least
which shows that there is room to bridge fiscal deficit by enhancing the
efficiency of tax system and increase in tax revenue. It can be achieved
by broadening the tax base that is too narrow to generate government
revenues to finance its expenditure.
4.1. Analysis with Alternative Measures of Seigniorage
Now we re-do the previous exercise with two alternate measures of
seigniorage (16) to check the robustness of base line results. (17) The
results are reported in Table 2. It is clear from Table ,2 that the
results do not change with alternate measures of seigniorage regarding
public expenditure. The conditional variables have also the same sign
and level of significance.
5. CONCLUSION AND POLICY RECOMMENDATIONS
The study follows the procedure adopted by Miller and Russek
(1997), Bose, et al. (2005) and Ahmed and Miller (2000) to find the
precise effects of fiscal variables on economic growth. Contrary to
previous empirical studies, this study considers three sources of
financing i.e., tax, debt and seigniorage simultaneously to analyse
their individual impact on growth. It is found that source of financing
of public expenditure has a crucial role in determining its impact on
economic growth. Debt financed public expenditure retard economic
growth. Similarly expenditure financed through seigniorage has also
significant negative effect on economic growth. Likewise tax financed
public expenditure is negatively associated with economic growth.
Although all sources of public expenditure hamper growth yet seigniorage
financed expenditure has a larger negative effect on growth than debt
financed and tax financed expenditure.
Several policy implications emerge from the analysis. Firstly,
reduction in deficit is positively associated with economic growth as
public expenditure financed through any source retard growth in the
sample. Decrease in expenditure holding the revenue constant may be
effective to enhance growth. Secondly, the role of governments in these
countries has not been efficient and needs to be redefined. Thirdly, tax
finance is the relatively less costly option to finance public
expenditure in low income countries as it hurts growth least as compare
to its counter parts debt and seigniorage financed public expenditure.
However, in general fiscal discipline and reorganisation of scarce
resources can boost economic growth in this region.
Appendices
Table A-1
Measures of Seigniorage
Variables Description
Monetary Base Reserve money (line 14 in IFS)
(or high-powered
money)
Seigniorage l: Ratio of the change in high powered money to
nominal GDP (Fischer 1982)
Seigniorage 2: Ratio of high-powered money to nominal GDP in
current period minus ration of high-powered money
to nominal GDP in last period plus the product of
the ratio Of high powered money to nominal GDP in
last period times the growth rate of nominal GDP
In current period to one plus the growth rate of
GDP in current period (Walsh 1998).
Seigniorage 3: Ratio of the product of the inflation rate times
high powered money to the product of one plus the
inflation rate times nominal GDP [de Haan, et al.
(1993), Walsh (1998)].
Reproduced from Bose, Holman and Neanidis (2005) Bose, et al.
(2005).
Table A-2
Variables and Their Source
Variables Source
Per Capita GDP World Development Indicator
Openness (Imports+ Export) World Development Indicator
Population Growth World Development Indicator
Gross Fixed Capital Formation World Development Indicator
Total Revenue Government Finance Statistics
Tax Revenue Government Finance Statistics
Deficit Calculated
Seigniorage Calculated
Total Expenditure Government Finance Statistics
Reserve Money International Finance Statistics
Consumer Price Index (CPI) World Development Indicators
APPENDIX II
DESCRIPTION OF VARIABLES
1.1. Government Borrowing
To finance its deficit government has to borrow. Contrary to other
fiscal variables, to have the direct measure of government borrowing is
often a difficult task in empirical literature. (18) Rodriguez (1994)
used the difference between deficit and revenues from printing of money
as a proxy for the part of total public spending which is financed
through issuing of interest bearing bonds. We also follow this approach
to measure the government borrowing.
1.2. Seigniorage
Like government borrowing, the measurement of seigniorage has also
been a widely discussed issue in empirical literature. To measure its
magnitude different alternative estimates have been suggested. (19) We
follow the methodology adopted by Fischer (1982), Walsh (1998) and De
Haan, Zelhorst, and Roukens (1993) to measure seigniorage.
1.3. Deficit
From total expenditure and total revenues series we construct a
variable deficit by subtracting total government expenditure from total
government revenues.
1.4. Trade Openness
Trade openness is the sum of exports and imports of goods and
services measured as a share of gross domestic product.
1.5. Reserve Money
The monetary base, high-powered money, comprises central bank
liabilities that support the expansion of broad money and credit.
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Comments
(1) This paper investigates the effect of source of finance
regarding public expenditures on GDP growth. The study has been
conducted for a panel of South Asian countries viz. Pakistan, India, Sri
Lanka and Nepal. (Why other countries e.g. Bangladesh, Maldives, Bhutan
and Afghanistan have not been included)?
(2) My major difficulty with the paper is that its objective is to
focus on the public expenditure on economic growth, the variables it
uses are revenue variables rather than expenditure variables. For
example, the author gives govt. budget constraint in section 3.1 on page
5. Lines 10-11 read "the left hand side of the above identity shows
the total expenditure while the right hand side is the total revenue
from different sources". Now, if the three components of right hand
side viz. total revenue, debt and signorage are used in regression, it
means that only revenue variables are used as explanatory variables. In
other words no component of government expenditure is included, yet on
page 3, third last line reads "fiscal variables comprise public
expenditure, public revenue and government deficit".
(3) I also have some difficulty in the interpretation of results in
Table 1. Three columns appear to be three different regressions. First
explanatory variable is labelled as "total expenditures".
There are no country specific effects which in fact is the essence of
fixed effects model. Only two non-fiscal variables are included in the
model viz. Population growth and openness. Other important variables
like investment, literacy etc., are missing from the model. It is
important to control for these variables as these variables are believed
to have an important impact on economic growth.
(4) The paper needs some clarity about tax revenue and total
revenue. Non tax revenue is also important (according to Pakistan
Economic Survey 2009-10 it has climbed to Rs 646 billion).
(5) Moreover, it is not clear how the budget constraint in equation
5 is incorporated in the model i.e. what is the objective function for
which equation 5 is used as a constraint. In other words, there is no
link between equation 5 and the model estimation in the paper.
(6) In discussing alternative measures of signorage, the author
gives only reference but has not discussed what these measures are. The
ranking of these sources is based only on sign of coefficient and size
of coefficient, which is small, but in the conclusion author says
"sources of finance of public expenditure has crucial role".
(7) Finally some minor comments, the variables are not discussed
adequately for example, it is not clear how openness has been computed.
Also, previous literature has not been reviewed adequately. I hope these
comments are useful for the improvement of the paper.
Ejaz Ghani
Pakistan Institute of Development Economics,
Islamabad
Muhammad Iftikhar ul Husnain <
[email protected]> is
PhD Scholar, FUUAST School of Economic Sciences, Federal Urdu University of Arts, Science and Technology (FUUAST), Islamabad.
(1) Revenues generated from printing of money are called
seigniorage.
(2) Miller and Russek (1997) report that in developing countries
tax financed increases in public expenditure lead to higher growth while
debt financed increases retard economic growth. For developed countries,
debt financed increases in public expenditure does not affect growth
while tax financed increases lead to lower growth.
(3) Bose, Holman and Neanidis (2005) suggest that in high income
countries tax financed government expenditure retard economic growth
than if it were financed through seigniorage while for low income
countries increases in government expenditure financed with seigniorage
retard growth more as compared to if it were financed through taxes.
(4) Unavailability of data forced us to exclude other South Asian
countries from the sample.
(5) Gross fixed capital formation as a share of GDP is used as a
proxy for investment.
(6) We borrow some work from Miller and Russek (1997), Helms
(1985), Bose, Holman and Neanidis (2005).
(7) Budget constraint is discussed shortly.
(8) These variables are time invariant.
(9) See Hsiao (1986).
(10) FEM is also called Least Square Dummy Variable (LSDV).
(11) "If T (the number of time series) is large and N (the
cross sectional unit) is small, there is likely to be little difference
in the values of the parameters estimated by FEM and REM. Hence, the
choice here is based on computational convenience. On this score FEM is
preferable" [Gujrati (1995)].
(12) New issues of interest bearing debt make a major part of rest
of budget financing [Bose, Holman, and Neanidis (2005)].
(13) Non tax revenue is not a choice variable. So we exclude debt,
tax and seigniorage in turn to see the impact of public expenditure on
economic growth when financed through these sources.
(14) We use Fischer (1982) procedure to estimate magnitude of
seigniorage in our base line regression.
(15) A significantly positive impact of openness variable on
investment share of GDP has been reported by Levine and Renelt (1992).
Ahmed and Miller (2000) also find a positive significant effect of a
country's openness on its investment. Bose, Holman and Neanidis
(2005) point out the positive effect of trade variable on economic
growth both for developed and developing countries.
(16) Walsh (1998) and De Haan, Zelhorst, and Roukens (1993).
(17) There are some other measures of seigniorage available in
empirical literature and the analysis with only one such measure does
not seem sufficient. The detail description of these seigniorage
measures is available in the appendix.
(18) Bose, Holman and Neanidis (2005).
(19) See Drazen (1985), Klein and Neumann (1990) and Honohan
(1996).
Table 1
Results with Aggregated Public Expenditure Using Fixed Effect Model
(FEM) Per Capita GDP Growth is the Dependent Variable
Tax Debt Money
Finance Finance Finance (14)
Total Expenditure -0.329 * -0.397 * -0.510 ***
[-2.68] [-3.33] [-1.67]
Openness 0.101 ** 0.103 ** 0.102 **
[2.43] [2.47] [2.44]
Population 0.509 0.504 0.537
[1.451 [1.481 [1.581
Investment 0.149 *** 0.148 *** 0.150 ***
[1.75] [1.76] [1.771
R-square 0.486 0.485 0.486
F-test 2 t)9 907 1) 1 11
*, **, *** mean significantly different from zero (two tailed test)
at the I percent, 5 percent and 10 percent level respectively.
T-statistics are in parenthesis.
Table 2
Results with Alternative Seigniorage Measures Using Fixed Effect
Model (FEM) Per Capita GDP Growth is the Dependent Variable
Fischer Walsh De Haan, et
(1982) (1978) al. (1983)
Public Expenditure -0.510 *** -1.157 *** -1.271 ***
[-1.67] [-1.70] [-1.81]
Openness 0.102 ** 0.099 ** 0.099 **
[2.44] [2.40] [2.41]
Population 0.537 0.439 0.331
[1.58] [1.41] [1.31]
Investment 0.150 *** 0.142 *** 0.139 ***
[1.77] [1.69] [1.68]
F-test 2.09 2.15 2.16
**, *** mean significantly different from zero (two tailed test) at
5 percent and 10 percent level respectively. T-statistics are in
parenthesis.