The Effect of Foreign Aid on Economic Growth in Developing Countries

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The Effect of Foreign Aid on Economic Growth in Developing Countries
E. M. Ekanayake, Bethune-Cookman University, Daytona Beach, Florida, USA.
Dasha Chatrna, University of Florida, Gainesville, Florida, USA.

ABSTRACT

This paper analyzes the effects of foreign aid on the economic growth of developing countries. The study
uses annual data on a group of 85 developing countries covering Asia, Africa, and Latin America and the
Caribbean for the period 1980-2007. We explore the hypothesis that foreign aid can promote growth in
developing countries. We test this hypothesis using panel data series for foreign aid, while accounting for
regional differences in Asian, African, Latin American, and the Caribbean countries as well as the
differences in income levels. While the findings of previous studies are generally mixed, our results also
indicate that foreign aid has mixed effects on economic growth in developing countries.

JEL Classifications: F21, F43, O40

INTRODUCTION

The role of foreign aid in the growth process of developing countries has been a topic of intense debate.
Foreign aid is an important topic given its implications for poverty reduction in developing countries.
Previous empirical studies on foreign aid and economic growth generate mixed results. For example,
Papanek (1973), Dowling and Hiemenz (1982), Gupta and Islam (1983), Hansen and Tarp (2000),
Burnside and Dollar (2000), Gomanee, et al. (2003), Dalgaard et al. (2004), and Karras (2006), find
evidence for positive impact of foreign aid on growth; Burnside and Dollar (2000) and Brautigam and
Knack (2004) find evidence for negative impact of foreign aid and growth, while Mosley (1980), Mosley,
et al. (1987), Boone (1996), and Jensen and Paldam (2003) find evidence to suggest that aid has no
impact on growth. It should be noted that, although Burnside and Dollar (2000) concluded that foreign aid
has positive effects, this conclusion applies only to economies in which it is combined with good fiscal,
monetary, and trade policies. A recent study by Doucouliagos and Paldam (2009), using the meta-analysis
covering 68 papers containing a total of 543 direct estimates, it is found that the effect of aid on growth
estimates scatter considerably and add up to a small positive, but insignificant, effect on growth. The zero
correlation result has yet to be overcome.

The main role of foreign aid in stimulating economic growth is to supplement domestic sources of finance
such as savings, thus increasing the amount of investment and capital stock. As Morrissey (2001) points
out, there are a number of mechanisms through which aid can contribute to economic growth, including
(a) aid increases investment, in physical and human capital; (b) aid increases the capacity to import
capital goods or technology; (c) aid does not have indirect effects that reduce investment or savings rates;
and aid is associated with technology transfer that increases the productivity of capital and promotes
endogenous technical change. According to McGillivray, et al. (2006), four main alternative views on the
effectiveness of aid have been suggested, namely, (a) aid has decreasing returns, (b) aid effectiveness is
influenced by external and climatic conditions, (c) aid effectiveness is influenced by political conditions,
and (d) aid effectiveness depends on institutional quality.

It is interesting to note that in recent years there has been a significant increase in aid flows to developing
countries although other types of flows such as foreign direct investment and other private flows are
declining. For example, according to the Organization for Economic Corporation and Development
(OECD, 2009b), foreign direct investment and other private flows are on the decline, and remittances are
expected to drop significantly in 2009. Budgets of many developing countries were hit hard by the rises in
food and oil prices in the last two years. Many countries are not in a strong fiscal position to address the

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current financial crisis. According to the OECD (2009b), in 2008, total net official development
assistance (ODA) from members of the OECD’s Development Assistance Committee (DAC) rose by
10.2% in real terms to US$119.8 billion and are expected to rise to US$130 billion by 2010. Africa is the
largest recipient of foreign aid. For example, net bilateral ODA from DAC donors to Africa in 2008
totaled US$26 billion, of which US$22.5 billion went to sub-Saharan Africa. Excluding volatile debt
relief grants, bilateral aid to Africa and sub-Saharan Africa rose by 10.6% and 10% respectively in real
terms.

Given the importance of foreign aid to the economies of developing countries, it is important to
understand its contribution to economic growth of developing countries. This paper analyzes the effects
of foreign aid on the economic growth of developing countries. We analyze these effects using panel data
series for foreign aid, while accounting for regional differences in Asian, African, Latin American, and
the Caribbean countries as well as the differences in income levels. One of the contributions of this paper
is its contribution to the existing empirical literature on the effects of foreign aid on economic growth of
developing countries through its thorough analysis covering a large number of developing countries as
well as a longer time period. The study focuses on the time period 1980-2007. In order to better
understand the effect of aid on growth as well as any change of its effect over time, we also estimated
three separate models for shorter time periods, namely, 1980-1989, 1990-1999, and 2000-2007.

The paper is structured as follows: The next section presents a survey of literature, whereas Section 3
presents the specification of the econometric model and data sources. The empirical results are presented
and discussed in Section 4 and finally, Section 5 summarizes the main results and concludes with some
policy implications.

METHODOLOGY AND DATA

Specification of Model

This section discusses the model specifications to examine the relationships between foreign aid and per
capita GDP growth. The models specified are estimated using panel least squares estimation method.

The model is derived, in conventional manner, from a production function in which foreign aid is
introduced as an input in addition to labor and domestic capital. In the usual notation the production
function can be written as follows:


Y = f ( ,
L K , )
A








(1)

where Y is gross domestic product (GDP) in real terms, L is labor input, K is domestic capital stock, and
A is stock of foreign aid.

Assuming (1) to be linear in logs, taking logs and differencing, we obtain the following expression
describing the determinants of the growth rate of real GDP:

y = ? + ? l + ? k + ? a







(2)

where lower case letters denote the rate of growth of individual variables. Following the precedent set in
numerous previous studies, we approximate the rate of growth of the capital stock by the share of
investment in GDP. This is necessary due to the formidable problems associated with attempts to measure
the capital stock, especially in the context of developing countries. In addition, we also replace the rate of
change in labor input by the growth rate of population. Following Karras (2006) and others, we also

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include several other variables that often believed to have a favorable effect on growth. As pointed out by
Feeny and McGillivray (2008), a reasonably robust finding of recent studies is that there is an inverted U-
shaped relationship between aid and growth. This finding indicates that there are diminishing returns to
aid due to recipient countries having absorptive capacity constraints. Absorptive capacity relates to an aid
recipient’s ability to utilize foreign aid inflows effectively. In order to take into account this relationship,
a square term is added to the following model. These changes yield the following growth equation:

?
2
INV ?
? AID ?
? AID ?
GGDP = ? + ? GPOP + ? ?
? + ? ?
? + ? ?
? + ? ln G
( DP ) + ? INF + e (3)
it
0
1
it
2
3
4
5
i0
6
it
it
? GDP ?
? GDP ?
? GDP ?
it
it
it

where GGD i
Pt is the growth rate of real GDP per capita of country i in year t , GPO i
P t is the growth
rate of population of country i in year t , INV is the investment of country i in year t , AID is the
foreign aid of country i in year t , GDP is the initial level of GDP of country i , and INF is the
i0
it
inflation rate of country i in year t . The growth rate of population is a proxy for the growth rate of labor
force, and the investment/GDP ratio represents the growth rate of capital stock. Regional dummies,
income level dummies, a dummy variable representing ethnic wars, and a variable representing the
economic freedom are also introduced. We are interested in testing whether the marginal impact of
foreign aid on growth, ?3 , is positive or negative and statistically significant. The expected signs of the
coefficients 1
? and ?2 are positive and that of ?3 either positive or negative, ?4 is negative, and that
of ?5 and ?5 are negative.

Variable Description and Data Sources

In order to test the implications of our models, we collected a panel of aggregate data on foreign aid on a
large number of developing countries. The entire data set includes 85 countries for which foreign aid and
all other relevant variables are reported over the 1980–2007 period. The sample of countries consists of
25 low-income countries, 29 low-middle-income countries, 22 high-middle-income countries, and 7 high-
income countries. The list of countries used in the empirical analysis is given in Appendix Table 1.

The economic growth rate is measured in this study as the growth of real GDP per capita in constant
(2000) U.S. dollars. The data on real GDP are from the World Bank, World Development Indicators
database. The growth rate of population is used as a proxy for the growth rate of the labor force. The data
on population are from the World Bank, World Development Indicators database. The investment/GDP
ratio is used as a proxy for the growth rate of the capital stock. Since the investment/GDP ratio is not
reported for the majority of the developing countries, gross fixed capital formation as a share of GDP is
used to represent investment/GDP ratio. The data on foreign aid are from the Organization for Economic
Corporation and Development (OECD), OECD.Stat online database and from the United Nations
Conference on Trade and Development (UNCTAD), Handbook of Statistics 2008 database. Inflation rate
is defined as the annual percentage change in Consumer Price Index (CPI). The data on inflation rate are
from the International Monetary Fund, World Economic Outlook database, October 2008. The data on
ethnic war variable are from the World Bank. The data on economic freedom are from the Freedom
House, The Freedom in the World 2008 database.

EMPIRICAL RESULTS

The results of our empirical analysis are presented in Tables 1, 2 and 3. First, we estimated model (3) for
four different time periods: 1980-1989, 1990-1999, 2000-2007 as well as for the entire period of 1980-
2007. The results of this analysis are presented in Table 1. Then we estimated the model for different

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regions, namely, Asia, Africa, and Latin America and the Caribbean. The results of this analysis are
presented in Table 2. Finally we estimated the model for different income levels, namely, low income,
low middle income, upper middle income and all income levels. The results of this analysis are presented
in Table 3.

Table 1. Effects of Foreign Aid on Growth in Developing Countries
Dependent variable: Real GDP per capita growth

Variable
1980-1989
1990-1999
2000-2007
1980-2007
Constant
-0.5478
0.4523
-1.3279
0.0545
(-0.404)
(0.371)
(-1.452)
(0.071)
Capital Growth
0.1264***
0.1209***
0.1477***
0.1268***
(5.151)
(6.447)
(9.574)
(9.174)
Labor Growth
0.0043
0.1062
0.9326***
0.0075
(0.237)
(0.642)
(6.611)
(0.707)
AID/GDP
-0.0766
-0.0205
0.0284
-0.0057
(-1.291)
(-1.606)
(1.142)
(-1.241)
(AID/GDP)2
-0.0016
-0.0003
-0.0001
-0.0001
(1.157)
(-0.448)
(-0.199)
(1.214)
Initial GDP
-0.0249
-0.1337
-0.5262***
-0.2606***
(-0.187)
(-1.525)
(-8.524)
(-4.325)
Inflation
-0.0005***
-0.0006***
-0.0012***
-0.0006***
(-2.599)
(-2.416)
(-2.270)
(-4.899)
Economic Freedom
-0.4223*
-0.0106
-0.1406
-0.2352*
(-1.891)
(-1.066)
(-1.078)
(-1.918)
Ethnic Wars dummy
-0.4406
-1.2079***
-1.6847***
-0.7747***
(-1.224)
(-3.990)
(-4.287)
(-3.672)
Asia dummy
3.4375***
0.5084
1.1357***
1.1671***
(5.514)
(0.817)
(3.253)
(2.967)
Latin America dummy
0.3825
-0.6367
0.0273
-0.6332*
(0.593)
(-1.042)
(0.823)
(-1.666)
Sub-Saharan Africa
1.9021**
-1.1370**
0.6995***
0.0282
dummy
(3.211)
(-1.968)
(2.253)
(0.772)
Low Income countries
0.1955
0.9688
-1.7293***
0.5309
dummy
(0.202)
(1.263)
(-3.015)
(1.063)
Low Middle Income
0.8231
0.8838
-1.4763***
0.6129
countries dummy
(0.993)
(1.430)
(-3.209)
(1.529)
Upper Middle Income
1.0617
0.6541
-1.5764***
0.2874
countries dummy
(1.392)
(1.084)
(-3.317)
(0.742)
Number of countries
83
83
83
83
Number of observations
830
830
664
2324
Adjusted R2
0.348
0.649
0.627
0.379

Note: Figures in parentheses are t-values. ***, ** and * indicate the statistical significance at the 1%, 5%
and 10% level, respectively.

Let us first discuss the estimated results that are presented in Table 1. The conventional variables behave
very much the same way as the model predicts, and the estimated coefficients are statistically significant.

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The adjusted
2
R values range from a low of 0.348 to a high of 0.649. These values, though relatively
low, are acceptable for a cross-sectional study and are comparable to those obtained in other studies.

The coefficients of the first two variables in model (3) are expected to be positive and our results are
consistent. Although the capital growth variable is statistically significant, labor growth variable is
statistically significant only during the period 2000-2007. Foreign aid variable has a negative sign in three
out of four cases, indicating that foreign aid appears to have an adverse effect on economic growth in
developing countries. This coefficient is not statistically significant in any of the four cases. The square
term is also found be statistically insignificant. The coefficient of the initial GDP variable has the
expected negative sign and is statistically significant during the periods of 2000-2007 and 1980-2007.

Inflation rate variable has the expected negative sign and it is statistically significant at the 1% level of
significance in all four cases. These findings are also consistent with the findings of previous studies. The
variable representing the economic freedom has a negative sign in all four cases but it is statistically
significant in periods 1980-1989 and 1980-2007. This variable is defined as follows: 1 if free; 2 if partly
free; and 3 in not free. Therefore, the negative sign can be interpreted as countries which are relatively
free tend to have a higher economic growth. The ethnic war dummy variable has a negative sign in all
cases and highly statistically significant in three of the four cases, implying that ethnic wars have an
adverse effect of economic growth.

Of the three regional dummy variables used in the model, Asia dummy variable consistently has a
positive sign and statistically significant in three of the four cases. Dummy variables for the other two
regions have missed results. The dummy variables representing the different income levels indicate that
the estimated coefficients are mostly positive for all income levels but negative during 2000-2007 period.

Let us now discuss the estimated results of our second set of models. The conventional variables behave
very much the same way as the model predicts, and several estimated coefficients are statistically
significant. The adjusted
2
R values range from a low of 0.147 to a high of 0.619. These values, though
relatively low, are acceptable for a cross-sectional study and are comparable to those obtained in other
studies.

The coefficients of the first two variables in model (3) are expected to be positive and our results are
consistent. Although the capital growth variable is statistically significant in all four regions, labor growth
variable is statistically significant only for Latin American region. Foreign aid variable has a negative
sign in three out of four cases, indicating that foreign aid appears to have an adverse effect on economic
growth in developing countries. However, this variable is positive for African region indicating that
foreign aid have a positive effect on economic growth in African countries. This coefficient is not
statistically significant in any of the four cases. The square term is also found be negative and statistically
insignificant. The coefficient of the initial GDP variable has the expected negative sign and is statistically
significant for Asia and for all countries.

Inflation rate variable has the expected negative sign and it is statistically significant at the 1% level of
significance in three of the four cases. It is not statistically significant for Asian region. These findings are
also consistent with the findings of previous studies. The variable representing the economic freedom has
a negative sign in all four cases but it is statistically insignificant for Asian countries. This variable is
defined as follows: 1 if free; 2 if partly free; and 3 in not free. Therefore, the negative sign can be
interpreted as countries which are relatively free tend to have a higher economic growth. The ethnic war
dummy variable has a negative sign in all cases and highly statistically significant in African countries,
implying that ethnic wars have an adverse effect of economic growth. This finding is not surprising given
the fact that Africa countries suffer the most from ethnic wars than any other region.

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Finally, let us now discuss the estimated results of our third set of models. In this case also the
conventional variables behave very much the same way as the model predicts, and several estimated
coefficients are statistically significant. The adjusted
2
R values range from a low of 0.213 to a high of
0.429. These values, though relatively low, are acceptable for a cross-sectional study and are comparable
to those obtained in other studies.

The coefficients of the first two variables in model (3) are expected to be positive and our results are
consistent. Although the capital growth variable is statistically significant in all income levels, labor
growth variable is statistically significant only in low income and upper-middle income countries.
Foreign aid variable has a positive sign in three out of four cases, indicating that foreign aid appears to
have a positive effect on economic growth in developing countries. However, this variable is negative for
low-middle income countries indicating that foreign aid have a negative effect on economic growth in
these countries. This coefficient is not statistically significant in any of the four cases. The square term is
also found be negative and statistically insignificant. The coefficient of the initial GDP variable has the
expected negative sign and is statistically significant for all income levels except for upper-middle income
countries.

Inflation rate variable has the expected negative sign and it is statistically significant at the 1% level of
significance in all four cases. These findings are also consistent with the findings of previous studies. The
variable representing the economic freedom has a negative sign in all four cases but it is statistically
significant only for upper-middle income countries. This variable is defined as follows: 1 if free; 2 if
partly free; and 3 in not free. Therefore, the negative sign can be interpreted as countries which are
relatively free tend to have a higher economic growth. The ethnic war dummy variable has a negative sign
in all cases and highly statistically significant in all cases except for upper-middle income countries,
implying that ethnic wars have an adverse effect of economic growth. This finding is not surprising given
the fact that upper-middle income countries suffer the least from ethnic wars than low-income countries.

CONCLUDING REMARKS

This paper analyzes the effects of foreign aid on the economic growth of developing countries. We
analyze these effects using panel data series for foreign aid, while accounting for regional differences in
Asian, African, Latin American, and the Caribbean countries as well as the differences in income levels.
One of the contributions of this paper is its contribution to the existing empirical literature on the effects
of foreign aid on economic growth of developing countries through its thorough analysis covering a large
number of developing countries as well as a longer time period. The study focuses on the time period
1980-2007 and 83 aid-receiving developing countries. In order to better understand the effect of aid on
growth as well as any change of its effect over time, we also estimated three separate models for shorter
time periods, namely, 1980-1989, 1990-1999, and 2000-2007. Then we estimated the model for different
regions, namely, Asia, Africa, and Latin America and the Caribbean. Finally, we estimated the model for
different income levels, namely, low income, low middle income, upper middle income and all income
levels.

The major point emerging from this work is that foreign aid has a mixed impact on economic growth of
developing countries. First, when the model was estimated for different time period, foreign aid variable
has a negative sign in three out of four cases, indicating that foreign aid appears to have an adverse effect
on economic growth in developing countries. In addition, this coefficient is not statistically significant in
any of the four cases. Second, when the model was estimated for different regions, foreign aid variable
has a negative sign in three out of four cases, indicating that foreign aid appears to have an adverse effect
on economic growth in developing countries. However, this variable is positive for African region
indicating that foreign aid have a positive effect on economic growth in African countries. This is not
surprising given that Africa is the largest recipient of foreign aid than any other region. Finally, when the

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model was estimated for different income levels, foreign aid variable has a positive sign in three out of
four cases, indicating that foreign aid appears to have a positive effect on economic growth in developing
countries. However, this variable is negative for low-middle income countries indicating that foreign aid
have a negative effect on economic growth in these countries. Thus, the findings of this study are, for the
most part, consistent with findings of previous studies on the effects of foreign aid on economic growth.

References

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Appendix Table 1. List of Developing Countries Included in the Study

Income Group
Countries
Low-Income Countries
Bangladesh, Burundi, Central African Republic, Congo, Dem. Rep., Gambia,
Ghana, Guinea-Bissau, Haiti, Malawi, Mali, Mauritania, Mozambique,
Myanmar, Nepal, Niger, Pakistan, Papua New Guinea, Senegal, Sierra Leone,
Solomon Islands, Tanzania, Togo, Uganda, Vietnam, Zambia, and Zimbabwe.
Low-Middle-Income
Algeria, Bolivia, Cameroon, China, Colombia, Congo, Rep. of, Dominican
Countries
Republic, Ecuador, Egypt, El Salvador, Guatemala, Guyana, Honduras, India,
Indonesia, Iran, Jordan, Kenya, Lesotho, Nicaragua, Paraguay, Peru,
Philippines, Sri Lanka, Sudan, Swaziland, Syrian Arab Republic, Thailand,
and Tunisia.
Upper-Middle-Income
Argentina, Belize, Botswana, Brazil, Chile, Costa Rica, Dominica, Fiji,
Countries
Jamaica, Libya, Malaysia, Mauritius, Mexico, Panama, Seychelles, South
Africa, South Korea, St. Kitts and Nevis, St. Lucia, St. Vincent and the
Grenadines, Turkey, Uruguay, and Venezuela.
High-Income Countries Antigua and Barbuda, Bahrain, Barbados, Kuwait, Singapore, Trinidad and
Tobago, and United Arab Emirates.


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