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Joanna Siwińska1
Fiscal imbalances and economic growth – an empirical study.
Preliminary, incomplete version.
Introduction.
Persistent fiscal imbalances are regarded by most economists as an undesirable outcome of
(imprudent) policymaking. High government deficits and public debts may seriously
destabilize the economy – inter alia, they are blamed for causing inflation, triggering currency
crises, and decreasing national savings (see, for example Sargent and Wallace 1981;
Krugman, 1979; Domenech, Taguas and Varela, 2000).
These concerns have led many countries to adopt fiscal policy rules2 designed to curb fiscal
imbalances (for an overview of different kinds of fiscal rules, see for example, Kennedy and
Robins, 2001). The EU has also recognized the possible harmful effects of public sector
imbalances what has led to the implementation of the controversial fiscal rules of Maastricht
Treaty and Stability and Growth Pact.
Although the possible consequences of fiscal imbalances are generally well described
(although not uncontroversial, see, for example, Elmendorf and Mankiw, 1998), surprisingly,
the influence of public deficit and debt on one crucial variable - economic growth - has not, as
of yet, attracted much empirical work.
The main goal of this paper is to fill this gap. This paper adopts the Extreme Bound Analysis
(EBA) developed by Levine and Renelt (1992) and Sala-i-Martin (1997) to empirically assess
the impact of fiscal imbalances on the rate of economic growth.
The paper is structured as follows: the first part lists theoretical models that discuss the
possible impact of fiscal imbalances on economic growth and reviews the existing empirical
Dr Joanna Siwińska, Warsaw University, Faculty of Economic Sciences, Chair of Public Sector Economics.
“A fiscal policy rule is defined (...) as a permanent constraint on fiscal policy, typically defined in terms of an
indicator of overall fiscal performance. The rules under consideration cover summary fiscal indicators, such as
the government budget deficit, debt (...) often expressed as a numerical ceiling or target, in proportion to GDP)”
(Kopits, Symansky, 1998, p. 2).
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evidence. The second part outlines the estimation method and present regression results and
the third part concludes.
1. Short overview of existing theoretical and empirical work.
According to neoclassical growth models, the long-run steady-state growth rate of output per
worker depends only on technological progress, which is however an exogenous variable, left
unexplained by these models. Therefore, as it is well known, within neoclassical framework,
fiscal imbalances may only influence the long-run level of output and the transition to steadystate, but not long-run economic growth rate. “Because of that, the conventional wisdom
based on the neoclassical model has been that differences in tax systems and in debt (…) can
be important determinants of the level of output but are unlikely to have an important effect
on the rate of growth” (Easterly, Rebelo, 1993 p. 420)
The inability of neoclassical growth models to explain the long-run growth process has led
economists to develop new models that deviate from neoclassical framework. These
“endogenous growth” models allow for the determination of the growth rate of output within
the model and provide a theoretical framework that enables the researcher to analyze the
possible consequences of fiscal policy and fiscal imbalances (as well as other policy
variables) for economic growth. An example of a framework that discusses the aftermath of
fiscal imbalances is Turnovsky (2000). He assumes a production function similar to Romer
(1986) “learning by doing” model, where an increase in private capital stock leads also to an
increase of the stock of knowledge (knowledge is a public good). Such production function,
together with additional assumptions concerning private returns to capital3, is enough to
generate endogenous growth. Turnovsky (2000) shows that fiscal imbalances imply a change
in the composition and the ratio of government expenditure and taxation and that these
changes influence the private return from capital and hence the long run growth. In a
framework of Ak production function, it is easy to show (see Barro, 1990) that taxation,
which decreases private returns to capital will decrease economic growth, while government
expenditures that increase private return to capital (productive government expenditures)
might increase the rate of growth4. Consequently, Turnovsky (2000) shows that keeping
government spending fixed, an increase in debt which allows to decrease taxation (of capital)
3
Private return to capital cannot be too small
Provided that the ratio of productive expenditure to GDP does not exceed a given threshold level, that depends
on parameters of the production function.
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will raise the rate of economic growth. Similarly, if government spending is productive, its
increase financed by an increase in debt (as opposed to an increase in taxation) can be also
growth-enhancing. However, if government spending is not productive, an increase in debt
caused by increased public expenditure will not change the rate of economic growth.
However, if the government is to remain solvent, policy leading to accumulation of debt,
might have to be reversed.
Hence, Turnovsky (2000) shows that the accumulation of government debt might be growth
neutral or growth enhancing, while a decrease in government debt might be growth neutral or
growth-decreasing. However, following this line, it can also be easily shown that an increase
in government debt might imply an increase in interest expenditures that might crowd out
productive expenditures or cause an increase in taxation, which in turn will reduce the growth
rate. It is worth stressing that according to Turnovsky, it’s not the fiscal imbalances per se that
influence growth but the change in public expenditure and taxation that they imply.
Saint-Paul (1992) has a different approach. He assumes a simple AK production function and
additionally assumes that economic agents have a constant probability of death. This implies
that contrary to Barro (1978) government bonds increase net wealth (i.e. financial wealth) of
households. This means that government debt increases households’ wealth thus stimulating
private consumption, decreasing savings and growth. It is also worth noting that in his model,
taxation doesn’t affect the rate of growth of output. Hence a bigger government debt is
associated with reduced growth, not because of change in patter of public spending or taxation
but because it changes household’s behavior and reduces savings.
Another model, due to Riera (2003) uses similar reasoning and stresses that fiscal imbalances
can increase interest rates and discourage investment in physical and also in human capital
and hence depress growth.
There is also another line of theoretical (as well as empirical research), which might be placed
under the heading of “debt overhang hypothesis”. It doesn’t directly concentrate on the issues
of economic growth, but rather on the influence of debt - public as well as private - on the
ratio of investment. The proponents of this hypothesis argue that excessive debt will
discourage investment. There are several explanations for that. Krugman (1998) argues that if
a country is unable to meet its external debt service obligations then the remaining required
payments might be conditioned on the country’s performance. This might discourage the
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“effort” made by this country to improve its situation, i.e. discourage domestic, as well as
foreign investment. As Krugman (1988 p.1) puts it: “the benefits of good performance go
largely to creditors rather then (to the country) itself”
Agenor (1999) and Pattillo, Poirson and Ricci (2002) argue that a high debt burden increases
uncertainty concerning for example future government policies (taxes, inflation, etc),
increasing the uncertainty of future payoffs from investments. As Serven (1997) shows, this
will discourage long-term, irreversible investments. Serven (1997) argues that in case of many
investment projects, their costs are partly or completely a sunk cost - they cannot be
recovered. This implies that if future return from investment is uncertain, investors will
choose not to invest, as long as current profit from investment is smaller than the costs of
possible irreversible loss. Hence high debt that increases uncertainty, will decrease
investments, and consequently - growth.
The empirical research on public sector imbalances, investment and economic growth is
limited and most researchers concentrate not on public debt, but rather on external debt. The
latter is also relevant for the discussion of public debt, as in developing countries most of
external borrowing has been made by the government sector.
Some empirical papers concentrate only on the impact of external debt on the ratio of
investment. Deshpande (1995) and Greene and Villanueva (1991) estimate a regression for
developing countries and find that external debt has a negative impact on investments. On the
other hand, Cohen (1993) using data for developing countries in 1980’s doesn’t find a
statistically significant relationship between external indebtedness and investment ratio and
concludes that a large stock of debt cannot be an “unconditional predictor of a low investment
rate in 1980’s” (Cohen, 1993 p. 441). However, his estimations indicate that investments are
crowded out by the debt service expenditures.
Another line of research concentrates directly on economic growth. Patillo, Poirson, and Ricci
(2002) estimate a panel regression for 93 developing countries over the period 1969-1998,
which indicates that the impact of external debt on growth is non-linear – positive, when debt
is low and negative, when debt ratio exceeds a certain critical value. They estimate that this
critical value is around 160-170 percent of exports and 35-40 percent of income.
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Clements, Bhattacharya and Nguyen (2003) estimate a panel regression for 55 poor
economies over the period 1970-99 and also find a non-linear relationship between external
debt and growth: according to their calculations an external debt higher than 30-37% of GDP
reduces the GDP growth rate. They also find that the debt service expenditures crowd out
public investment.
Chowdhury (2001) studies the impact of foreign indebtedness on the rate of economic growth
using two samples of developing countries. He uses the Levine and Renelt’s (1992) „extreme
bound analysis” and proves that the impact of external debt on growth is negative and robust.
The paper by Smyth and Hsing (1995) examines explicitly the impact of public debt on the
rate of growth. They estimate a regression using data on US economy and find that the impact
of debt on growth it is non-linear – positive for smaller debt ratio and negative for larger
values. They estimate the threshold value at 48,9% of GDP.
Another paper concentrating only on public debt is Lin and Sosin (2001). They examine the
relationship between government external indebtedness and economic growth. Their crosssection regression analysis is based on different samples: industrial countries, African
countries, Latin American countries, Asian and other countries and a wide sample
incorporating all of the listed countries. The impact of debt on growth is negative, but
insignificant in most regressions. It remains significant only in the African sub sample.
Eastrely and Rebelo (1993) also estimate a number of cross-country growth regressions and
include, among other fiscal variables, a measure of government surplus and find that its
relation to growth rate and investment rate is positive and robust.
2. Empirical analysis of the impact of fiscal imbalances on growth.
The existing work on the influence of total public debt on growth is limited and inconclusive.
The empirical analysis of this paper is intended to fill this gap and to verify the impact of
public sector imbalances on economic growth. However, empirical analysis of growth is not
straightforward. As Levine and Renelt (1992) stress, over 50 variables have been found to be
significantly correlated with rate of output growth. Of course, it is impossible to include all of
the in a single regression, hence most researchers in attempt to find a relationship between
growth and a given variable of interest consider only a small number of other explanatory
variables. This puts into question the reliability of these studies. The solution to this problem
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proposed by Levine and Renelt (1992) is to use the so called “extreme bound analysis”
(EBA). This paper utilizes two versions of EBA: as developed by Levine and Renelt (1992)
and by Sala-i-Martin (1997).
In short, Levine and Renelt (1992) propose to estimate regressions of the following form:
y = βi I + βmM + βzZ + u,
where:

y is the per capital growth rate,

I is a set of “basic” variables, always included in regressions

M is the variable of interest

Z is a subset of variables that have been identified by previous studies as being
correlated with growth.
The Levine and Renelt methodology calls for estimations of a number of regressions, starting
with the base regression, without the subset of Z variables. The following estimated
regressions are more extended and contain combinations of up to three different Z variables.
This procedure allows the researcher “to find the widest range of coefficient estimates for the
variable of interest” (Levine and Renelt, 1992, p. 944). The last step is to calculate the
extreme bounds of βm - the coefficient on the variable of interest - which is done by finding
the highest and lowest value of βm and then adding two standard deviations to the highest
value and subtracting two standard deviations from the lowest value. If the coefficient at the
extreme bound remains significant and of the same value “then one can maintain a fair
amount of confidence in that partial correlation” (Levine and Renelt, 1992, p. 944).
However, Sala-i-Martin (1997) criticizes this approach as too extreme and proposes a less
stringent method. He proposes to move away from the binary “robust” “not robust”
classification and instead to look at the whole distribution of coefficient estimates and to
assign some “level of confidence” to the coefficient. Hence, Sala-i-Martin (1997) also starts
with estimating a number of regressions, similar to Levine and Renelt (1992). Then he
calculates the cumulative distribution function of coefficient βm.. If the probability that βm is
either greater than or less then zero is 95% or higher, he considers the variable as robust.
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Since Levine and Renelt’s (1992) and Sala-i-Martin’s (1997) work, both variants of EBA
have been utilized by numerous researchers, but according to my knowledge, none of them
had addressed the issue of fiscal imbalances.
Following Levine and Renelt (1992) and Sala-i-Martin (1997), the set of base “I” variables
that appear in the base regression and all following regressions encompasses:

Log of initial GDP per capita (GDP),

Log of investment share in GDP (inv) and

Log of population growth (pop).
The “M” variable of interest is log of government debt to GDP ratio (debt).
From the set of basic “I” variables, I omit the fourth variable included by Levine and Renelt –
secondary school enrolment rate, as several authors question the influence of this variable on
economic growth (see, for example Pritchett, 1996)5.
The set of “Z” variables includes log of: secondary school enrolment rate, tertiary school
enrolment rate, consumption of general government as percentage of GDP, international trade
as percentage of GDP, share of manufactures in exports and rate of inflation (measured by
CPI).
I estimate the cross-section regressions for two sub samples - a broad sample encompassing
developing and developed countries (a detailed list is included in the Appendix) and a sample
of 25 EU countries. The regressions are estimated by OLS, with White HeteroskedasticityConsistent Standard Errors & Covariance. For the broad sample, the data on GDP per capita
growth and level were taken from Summers-Heston Penn World Tables; for the EU-25
sample, this data comes from Eurostat. The remaining variables are from World Bank World
Development Indicators, except for public debt for the EU-25, which is also taken from
Eurostat. In case of broad sample all the data, except initial GDP per capital, is averaged over
1990-2000. Initial GDP is an average over 1986-1988. For the EU-25 sample, series were
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As De la Fuente and Domenech (2001) argue, the lack of robust relationship between data on human capital
and economic growth may be due to poor quality of the easily accessible data on human capital. As shown by
authors, using better quality data will generally give positive and robust relationship measures of human capital
and growth.
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available up to 2003, hence, the data, except for the level of initial GDP is averaged over
1996-20036. Initial GDP per capita is for 1994.
Following Levine and Renelt (1992), I estimate a number of regressions, with different linear
combinations of up to three Z variables. Table 1 below gives the results for the basic
regression with the “I” variables and ratio of debt to GDP. Table 2 includes the upper and
lower bound for the public debt coefficient (βm), average value of this coefficient and its
standard error computed for the values from all regressions, fraction of significant coefficients
at the 5% and 10% level and the fraction of the density function of βm lying to the left of zero.
Table 1. Results of the base regression.
Broad sample
Variable
Debt
GDP
Inv
pop
R-squared
Adjusted R-squared
No of obs.
EU sample
Coefficient
Coefficient
-0.626**
-0.886***
(-2.13)
(-4.72)
-0.716**
-0.293
(-2.97)
(-0.92)
3.540***
3.010***
(5.054)
(3.01)
-1.126***
-0.338
(-3.39)
(-0.28)
0.447
0.412
0.4192
0.329
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25
Source: Own calculations
t-statistics are in parenthesis,
* indicates significance at 10% level,
** indicates significance at 5% level,
*** indicates significance at 1% level
All the coefficients have the expected sign, however in case of EU-25 sample, surprisingly,
neither population growth nor initial level of GDP per capita are statistically significant. In
both samples the coefficient on debt ratio is negative and highly significant.
I include a shorter time period than in the broad sample in order to exclude the first half f 1990’s which in case
of New Member States was a period of turbulences associated with the initial transformation period.
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Table 2 Extreme bounds and cumulative distribution function (CDF) of the coefficient on debt
ratio.
Broad
Upper
Lower
Average
bound
bound
value
-1,214***
0,116
(-2,13)
(-1,45)
-2,447***
0,056*
(-3,93)
(-1,82)
Standard
of error
Percentage
of significant
Percentage CDF
significant
βm
βm
at 5%
at 10%
-0,424
0,228
27%
90%
0,968
-1,124
0,319
90%
100%
0,999
sample
EU-25
Source: Own calculations
t-statistics are in parenthesis,
* indicates significance at 10% level,
** indicates significance at 5% level,
*** indicates significance at 1% level,
In case of both samples the value of βm changes sign at the extreme bounds, thus according to
EBA of Levine and Renelt (1992) the ratio of public debt turns out to be a variable that is not
robustly correlated to growth. However according to the less stringent Sala-i-Martin’s (1997)
EBA, in both samples (and very strongly in the EU-25 sample) the public debt ratio is a
robust variable, which impact on economic growth is negative.
3. Conclusions
The theoretical models that discuss the impact of fiscal imbalances on long-run economic
growth do not yield uniform conclusions. While some models show that public debt will
lower the rate of economic growth, some argue that this impact is ambivalent, depending
largely on the implied change in level and composition of public expenditure and taxation.
Empirical research on the influence of budget deficits and public debt on economic growth is
limited. Some authors report a negative correlation between indicators of fiscal imbalances
and economic growth, but most of the existing research concentrates only on the impact of
external debt (public and private). The goal of this paper was to fill this gap in empirical
literature. I have used the extreme bound analysis of Levine and Renelt (1992) and Sala-iMartin (1997) to assess the possible influence of public debt on growth.
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While the coefficient on public debt doesn’t pass the very stringent EBA of Levine and Renelt
(1992), it does pass the less rigorous EBA of Sala-i-Martin (1997). These results indicate that
prolonged fiscal imbalances seem to be detrimental to the rate of economic growth.
References
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Chowdhury A., 2001, Foreign Debt and Growth in Developing Countries, paper presented at
WIDER Conference on Debt Relief (Helsinki: United Nations University) (August).
Clements B., Bhattacharya R., Nguyen T. 2003, “External Debt, Public Investment, and
Growth in Low-Income Countries”, IMF Working Paper, IMF WP 03/249,
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Cohen D., 1993, “Low Investment and Large LDC Debt in the 1980s,” American Economic
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Development Economics, vol. 52(1),
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in OECD” Economic Letters, vol. 69,
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Bureau of Economic Research, Cambridge.
Greene J. , Villanueva D., 1991, “Private Investment in Developing Countries.” IMF Staff
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Kennedy S., Robbins J., 2001, “The Role of Fiscal Rules in Determining Fiscal Performance”
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Appendix.
Sample of countries used in the analysis:
Algeria, Australia, Belgium, Belize, Botswana, Burundi, Cameroon, Canada, Chile, China,
Colombia, Congo, Rep., Costa Rica, Cote d'Ivoire, Cyprus, Dominican Republic, Egypt, Arab
Rep., Ethiopia, Fiji, Finland, Germany, Greece, Guatemala, Iceland, India, Indonesia, Israel,
Jamaica, Japan, Jordan, Kenya, Korea, Rep., Lebanon, Madagascar, Malaysia, Malta,
Mauritius, Mexico, Morocco, Nepal, Netherlands, Norway, Pakistan, Papua New Guinea,
Paraguay, Peru, Philippines, Portugal, Rwanda, Senegal, Sierra Leone, Singapore, South
Africa, Spain, Sri Lanka, St. Vincent and the Grenadines, Swaziland, Switzerland, Trinidad
and Tobago, Tunisia, Turkey, Uganda, United Kingdom, Uruguay, Zambia, Zimbabwe
List of data and sources:
GPD per capita growth rate
Heston A., Summers R., Aten B.,
Penn World Table Version 6.1,
Center for International Comparisons
at the University of Pennsylvania
(CICUP), October 2002;
EUROSTAT (for the EU -25
sample)
GDp per capita:
Heston A., Summers R., Aten B.,
Penn World Table Version 6.1,
Center for International Comparisons
at the University of Pennsylvania
(CICUP), October 2002
EUROSTAT (for the EU -25 sample)
Central government debt, in % of GDP World Bank, World Development
Indicators (WDI), 2005
General government debt, in % of GDP
EUROSTAT (available only for EU25 sample)
General government final consumption World Bank, WDI, 2005
expenditure (% of GDP)
Gross fixed capital formation (% of GDP)
World Bank, WDI, 2005
School enrollment, secondary (% gross)
World Bank, WDI, 2005
School enrollment, tertiary (% gross)
World Bank, WDI, 2005
Population growth (annual %)
World Bank, WDI, 2005
Inflation, consumer prices (annual %)
World Bank, WDI, 2005
Manufactures exports (% of merchandise World Bank, WDI, 2005
exports)
Trade (% of GDP)
World Bank, WDI, 2005
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