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Foreign Aid, Government Policies and Economic Growth



Name : Y. Meulblok*/**Address : Hoendervogellaan 14

4451 EM Heinkenszand The Netherlands

Student number : 308013E-mail address : [email protected] date : Academic year : 2008-2009University : Erasmus University Rotterdam, Erasmus

School of EconomicsMaster : International Economics and Business

StudiesSupervisor1 : Dr. J. Emami Namini

Erasmus School of Economics

1 I would like to thank my supervisor, Dr. J. Emami Namini, for all his valuable comments and suggestions on earlier drafts of this paper

*The author declares that the text and work presented in this master thesis is original and that no other sources other than those mentioned in this text and its references have been used in creating this Master Thesis

**The copyright of this Master Thesis rests with the author. The author is responsible for its contents. The Erasmus University is only responsible for the educational coaching and beyond that cannot be held responsible for the content.

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AbstractIs economic growth affected positively by foreign aid? And when this is the case, what role

does a good policy environment play? This is a heavily debated topic. While Burnside and

Dollar (1997) show that foreign aid only contributes to growth if recipient governments have

good policies, others disagree with this result and show that aid always contributes to

economic growth and that a good policy environment has no effect.

This paper presents another analysis on the already large literature of the aid-growth

nexus. It proposes new variables that might affect the relationships that exist between foreign

aid, government policies and economic growth. This paper produces OLS and TSLS

regressions for eight panels of four-years covering 107 countries between 1970-2001 while

taking into account more data that has become available through the years.

After controlling for the possibility of aid endogeneity, this paper shows that foreign

aid positively affects economic growth. However, the policy environment did not empirically

contribute to this positive effect. In addition, this paper examines the effects of the domestic

savings rate interacted with foreign aid and the results were very promising, producing highly

significant coefficients. The final hypothesis examined, was whether aid works in good policy

environments when taking diminishing returns on aid into account. Results show that even

when diminishing returns are added, the policy environment did not have any affect.

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Table of contents

1 Introduction...................................................................................................5

2 Theoretic Framework...................................................................................7

2.1 Macroeconomic impact of foreign aid: absorption and spending............7

2.1.1 Aid is absorbed and spent..................................................................9

2.1.2 Aid is spent, but not absorbed.........................................................10

2.1.3 Aid is neither absorbed nor spent....................................................12

2.1.4 Aid is absorbed, but not spent.........................................................12

2.2 Macroeconomic impact of foreign aid: growth......................................16

2.2.1 Aid has a positive impact on growth...............................................17

2.2.2 Aid has no affect on growth.............................................................18

2.2.3 Aid has a conditional relationship with growth..............................20

3 Data and empirical strategy.......................................................................24

3.1 Data description......................................................................................24

3.2 Empirical model specification................................................................27

4 Regressions and results...............................................................................30

4.1 OLS Growth Regressions.......................................................................30

4.2 Two-Stage Least Squares Growth regressions.......................................33

5 Conclusion and remarks.............................................................................35

6 References....................................................................................................37

7 Tables...........................................................................................................46

Appendix A1: List of variables........................................................................48

Appendix A2: List of countries........................................................................49

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1 IntroductionToday, almost one billion people are living on less than $1 a day (World Bank, 2008). As can

be seen in table 1 below, developed countries spend more than $100 billion on Official

Development Assistance, further in this paper denoted as (foreign) aid.

Figure 1: Net Official Development Assistance in 2008

Source: Organisation for Economic Co-operation and Development Data

A major objective of foreign aid is to spur economic growth in the recipient nation through

various channels in order to close the gap between developed and developing countries.

Despite the high aid inflows to developing economies and the numerous econometric studies,

the various conclusions about the relationship between foreign aid and economic growth are

not without controversy (World Bank, 2008).

The traditional view is that foreign aid is an important instrument for countries to stimulate

development. Many developing countries are dependent on foreign aid programs as it brings

not only the desirable financial resources, but also the right arguments on how to spend those

resources. A combination between those two factors is necessary for economic development.

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However this view has stirred a lot of criticism. Empirical proof is required to clear up this

discussion.

Probably the most influential paper that investigates the relationship between aid and

growth was written by Dollar and Burnside (1997). They set out an empirical model including

an index of inflation, budget balance and openness to measure policy. They find that although

foreign aid does not significantly affect economic growth in developing countries, aid

interacted with policy produces a positive effect on growth.

Their results has also had a tremendous impact on the way donor countries act

(Easterly, 2003). Poor countries know that foreign aid will only be addresses to countries with

a good policy environment and are at risk of losing foreign assistance. Since Burnside and

Dollar, many papers tries to review the robustness of this particular policy view, as well as to

assess the aid-growth relationship in this light. Research by the World Bank (1998), Collier

and Dollar (1999) and Svensson (1999) support the findings of Burnside and Dollar, while

Lensink and White (1999), Guillaumont and Chauvet (2001), Hansen and Tarp (2001), Lu

and Ram (2001), Easterly et al. (2004) and Dalgaard and Hansen (2005) to name a few,

oppose these results on statistical grounds and provide evidence that aid raises growth

regardless of the policy environment.

This paper examines four different hypotheses; firstly, aid has a positive impact on

economic growth. Secondly, aid works better in a good policy environment. Thirdly, aid

works better in good policy environments when taking diminishing returns on aid into

account and fourthly, domestic saving via foreign aid and FDI lead to higher growth.

Considering previous literature, this paper reexamines the aid-growth nexus

introduced by Burnside and Dollar (1997). It will critically evaluate the effects of foreign aid

on economic growth taking the role of a good policy environment into account. This paper

expands the dataset with 51 countries, increases observations to 451 and expands the time

period by eight years to 2001. New variables are included such as domestic saving and

Foreign Direct Investment.

The organization of this paper is as follows. Chapter two discusses the theoretical

background. Chapter three sets out the model and describes the data sources. Chapter four

discusses the results and the explanations behind the results. Finally, chapter five provides the

conclusions followed by some remarks.

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2 Theoretic FrameworkA variety of studies have intended to address the issue of whether foreign aid has an effect on

the macro economy in the long run, as well as the effect on institutions and policies. However

the literature on the short-run effect of foreign aid on key macroeconomic aggregates is

mostly limited to fiscal response literature. Nevertheless a 2005 IMF study examined the

impact of foreign aid in five relatively large African studies.

2.1 Macroeconomic impact of foreign aid: absorption and spendingThe key point in managing aid inflows is the coordination of fiscal policy with the exchange

rate and monetary policy. To accentuate this relationship, it is useful to distinct between two

concepts: absorption and spending.

“Absorption is defined as the widening of the current account deficit (excluding aid)

due to incremental aid. It measures the extent to which aid engenders a real resource transfer

through higher imports or through a reduction in the domestic resources devoted to producing

exports. Spending is defined as the widening of the fiscal deficit (excluding aid)

accompanying an increment in aid.” (IMF, 2005)

The importance of this distinction is that foreign aid only gives a country the

possibility to increase the level of consumption and investment more by financing higher

imports. When foreign aid is only used to finance local goods and services, it does not help to

build up their supply. This will lead to inflationary pressures, except when an economy has

spare capacity (Foster and Kilick, 2006).

Because spending expresses the widening of the fiscal deficit, it depends on fiscal

policy. In addition absorption hinges upon exchange rate and monetary policy. Spending and

absorption could be equivalent if a government uses aid directly to finance imports or receives

aid-in-kind (aid received as charity, so with no money or debt in return). It is however

common that the government sells the received aid to the central bank and uses the local

currency counterpart to finance domestic goods.

The response of the central bank is consequential for absorption, because the foreign

exchange sales influence the exchange rate and interest rate policy that form aggregate

demand, including for imports. The combination of spending and absorption chosen by an

economy defines the impact of aid to macroeconomic aggregates.

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Figure 2 generally shows how governments can respond to aid inflows in the short run:

Figure 2 Absorption and government spending responses to aid flows

Source: Hansen and Heady (2007)

Notes: FEX = foreign exchange or foreign exchange reserves; LC = local currency; M = Imports; C =

Consumption; I = Investment; ER = Exchange rate; IR = Interest rate; π = inflation; nX = net exports.

Outcome 1. Aid-in-kind or aid that is completely used to finance imports is directly absorbed

and will not affect the ER or the IR (absorption and spending are equivalent). A similar outcome can

be achieved if aid is used to buy domestic goods and services after being converted to local currency.

This will lead to an appreciation, but indirectly to a depreciation when the demand for imports has

risen.

Outcome 2. If aid is spent but not absorbed, the aid will be used in the domestic market after

being converted to local currency. However, this does not give rise to higher imports, but will put

upward pressure on the exchange rate or interest rate. This will crowd out the private sector.

Outcome 3. If aid is neither absorbed nor spent, the FEX aid is put aside and accumulated in

order to increase the FEX reserves.

Outcome 4. If aid is absorbed but not spent, then aid could be spent to cut back on the current

fiscal deficit or to decrease debt. This may lead to the ‘crowding in’ of the private sector.

There are four possible combinations of absorption and spending. These four combinations

together with their macroeconomic impact will be described in the next four sections.

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2.1.1 Aid is absorbed and spentThis is the situation assumed in most scenarios (Outcome 1). The government uses foreign aid

to buy domestic goods and services. In addition, the central bank sells the foreign exchange

and resulting in a widening of the current account deficit as the aid flows are absorbed by the

economy. Both spending and absorbing permits reallocating resources from the traded goods

sector to public spending. This reallocation of resources results in a foreign exchange gap,

that will be filled by foreign aid that has been received (Bevan, 2005).

Spending aid will generally result in more import. To import more goods and services

into a country, there must be a higher aggregate demand together with a decrease of the

exchange rate. This decrease of the exchange rate is required to switch the demand from

domestic to imported goods and services. The higher demand can only be served when a

country has sufficient capacity and employment (Foster and Kilick, 2006).

However there could arise a situation when output may not be fixed and there is no

sufficient employment. A fiscal expansion could lead to a higher output. In the short run this

is established by the higher aggregate demand that will increase spending. In the long run this

is established by a higher capital stock. Through these two channels the current account does

not suffer a deterioration, but no aid is required to initiate the increase in aggregate demand

and capital stock. So aid is not fully absorbed, because to be absorbed aid has to finance the

changes in the current account deficit which was caused by the higher demand, investment

and output due to the aid inflows (Aiyar et al., 2008).

The absorption of aid depends on the level of decrease in the exchange rate. How large

this level must be is dependent on the amount at which aid is spent on imports and on how an

economy will react on the changes. For example, the decrease of the exchange rate is higher

when aid is mostly used to finance expenditures on non-traded goods. The decrease of the

exchange rate is lower when higher incomes result in an increase of import demand and the

prices strongly affect the non-traded goods supply (Berg, 2005).

In countries where the non-traded goods supply quickly can react to the changes, there

could occur an increase in production and employment when demand increases too. This is

accommodated with only a small appreciation and a small price increase. Investments that

result in higher productivity can cause the real exchange rate appreciation to reduce or even to

vanish in the long run (IMF, 2005).

The exchange rate regime is the key factor behind the mechanism for real

appreciation. In a pure floating regime, the central bank imposes an exchange rate

appreciation by selling foreign exchange that is related to the aid inflows. In a peg, the central

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bank accommodates the real appreciation with a rise in public expenditures during a period of

inflation. The real appreciation results in an increase of net import demand, whereupon the

central bank must defend the peg by selling foreign exchange (Buffie et al., 2004).

Countries can choose to spend the total amount of received aid on imports or goods

that are typically exported. This policy will have little effect on prices unless the country is

very large, but most countries are too small to have any influence on the international price

level. However, additional spending on non-traded goods and services is likely to lead to price

increases (inflation). Nevertheless there are various ways to avoid price increases when

foreign increase real resource availability.

Foreign aid is usually given in a foreign currency (FEX), which is normally converted

to local currency and used to expand government spending or lower taxes. By appreciating

however, a government can make its exports less competitive. In addition productivity and

growth may fall or slow down. This is known as the Dutch disease effect (Corden & Neary,

1982; Rajan and Subramanian, 2005; Bulir and Lane, 2002; Prati and Tressel, 2006).

Countries with a good economic environment could however partly offset the Dutch disease

effects by spending foreign aid on domestic resources. This should increase imports and

should compensate for the loss in export competitiveness. Smaller countries would be

expected to spend most FEX on imports. This should result in an increase in net imports as

well as in domestic demand (C+I).

2.1.2 Aid is spent, but not absorbedThis appears to be the most frequent outcome and is equivalent to deficit financing. This

scenario occurs when the government increases expenditures, but the central bank saves the

foreign aid as reserves and does not finance the arisen fiscal deficit. It can be seen as a fiscal

expansion. The macroeconomic impact of this scenario is equivalent to a situation when aid

does not flow in, apart from the higher FEX reserves. The aid inflows do thus not serve to

support the fiscal expansion. Due to the increasing expenditures, there will float more money

into the economy (Foster and Kilick, 2006).

However, there is no reallocation of real resources, because there are no increasing net

imports. Instead of financing these additional net imports, aid is used as an alternative for

domestic tax revenue. To finance their expenditures, the government does not use aid, but

simply borrows money from the central bank, i.e. enlarges the money supply. The aid rather is

aimed at providing the foreign exchange that is necessary to meet the increased demand for

foreign currency as a result of the increased import demand. (IMF, 2005)

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There are several monetary policy responses to a situation in which aid is being spent

by the government but not absorbed in the economy. When there is no selling of foreign

exchange, the best option is to monetize the fiscal expansion. The disadvantages of this

scenario are that inflation tends to increase and the nominal exchange rate tends to depreciate.

In addition, the larger money supply will increase the price of foreign exchange. As a result

there will be an inflation tax that initiates a lower private demand and will decrease the

absorption of aid and will decrease the real exchange rate. If the authorities instead withstand

nominal exchange rate depreciations, then the following inflation will give rise to a real

appreciation, the demand for imports will boost up in due course and exports will fall (IMF,

2005).

Eventually the foreign aid will be sold to finance the increasing net imports demand.

This will defend the nominal exchange rate and suppress inflation as it has a stabilizing effect.

In time aid thus will be used and absorbed. However, inflation is very high the period before

the aid inflows are absorbed. During this period a country can bear high costs (Aiyar et al.,

2008).

A second strategy for governments is to sell treasury bills in order to sterilize the

monetary expansion. The money supply will become smaller, but the interest rates will

increase. This will crowd out private investment. As a result the country will notice a switch

from private to public investment. However this strategy is expected to be difficult to realize

and will carry high costs. It is difficult to realize, because when the interest rate increases,

international capital will flow into the country and appreciate the exchange rate (IMF, 2005).

The spent-but-not-absorbed case (Outcome 2) is thus a less favorable scenario,

because aid is converted to the local currency and spent domestically, but import demand fails

to increase. When public expenditures do not affect import demand, an appreciation of the

exchange rate may occur (Hansen and Headey, 2007).

If aid is spent but not absorbed, the effect on the real exchange rate can either be

positive or negative. This effect depends on miscellaneous factors. On the on hand there

occurs an appreciation when the non-traded goods demand increases due to the fiscal

expansion. On the other hand does the fiscal expansion result in a depreciation, because

import demand increases which will decrease the export supply. The key factors that affect

the net effect are the price and income elasticity of a country’s import demand and export

supply(Aiyar et al., 2008).

Moreover, the net effect will depend on the exchange rate regime. In a float the real

exchange rate will depreciate in the short run due to liquidity injections that are aid-related.

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In the long run, the real exchange rate will appreciate due to the increased inflation and the

related inflation tax that decreased private demand. A similar outcome occurs when selling

treasury bills (IMF, 2005).

When the exchange rate is pegged, the only strategy is to sterilize through selling

treasury bills. The nominal exchange rate has to be fixed, so the authorities have to enlarge

the money supply which will increase the interest rate. This outcome may also ensue when the

foreign aid is not converted to local cuurency, but held as foreign exchange. The rise in public

expenditures will then be financed by increasing the money supply. This will result in

inflation, but is regarded by Foster and Killick (2006) as the only policy response which is not

well motivated.

2.1.3 Aid is neither absorbed nor spentThis scenario (Outcome 3) is the direct opposite of outcome 1. Aid inflows are used to

accumulate FEX reserves or to smooth volatile aid inflows. In this scenario aid does not have

any macroeconomic impact except some indirect effects such as a higher confidence due to

the increased FEX reserves (Aiyar and Ruthbah, 2008).

As aid is fully used on FEX reserves, the public expenditures and taxes will remain

their current level. Therefore the exchange rate or prices will remain stable and aggregate

demand will not increase. Nevertheless, not spending the aid is not favorable in the long run,

because donors are responsible for their expenditures. However, money is fungible, and not

spending the aid inflows coincides with engaging in donor’s favored projects. This is of

course dependent on the moderation of expenditures in other areas (Aiyar et al., 2008).

Although this scenario may seem extreme, it might be relevant if a country

experiences FEX shortages or excessive aid volatility. FEX shortages, excessive aid volatility

or homogeneous exports could cause problems in small countries, so that the accumulation of

FEX reserves may be provident for when a country exhibits problems.. However, a poor

macroeconomic climate might also result in this outcome as FEX shortages may be the

consequence of a weak policy environment, e.g. taxes on exports (Hansen and Headey,

2007).

2.1.4 Aid is absorbed, but not spentThis scenario (Outcome 4) substitutes aid for domestic financing of the government deficit. In

this scenario the government uses aid to finance the government deficit. The government

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finances an increase of net imports after having converted the aid flows in local currency, so

does not lower taxes or increase its expenditures. This outcome is relevant when government

goals contain lowering debt, attaining stabilization or when excessive spending results in the

crowding out of the private sector. Applying this scenario should result in an appreciation of

the exchange rate, a decline in monetary growth and in decreasing inflation (Gupta et al.,

2006).

As the inflation decreases, aggregate demand will increase which will result in

increasing private investment and more private consumption. This stabilization often

corresponds with a weakening of the trade balance, but the aid flows will defend the trade

balance and will finance the difference. (Buffie et al., 2004).

Aid also can be used as an instrument to reduce debt. This is the case in countries

where the government bears a large domestic debt. This would apt to affect private investment

and consumption positively, which would result in increased net imports via higher private

after-tax income on import demand. This increase in net imports demand would be financed

by the extra foreign exchange sold by the central bank. This rise in net imports should

however be accommodated by a real exchange rate appreciation to mediate the effects. The

success of this scenario is dependent on the consequences of lowering interest rates. If they

are accommodated by higher domestic consumption and investment than it could be a

success. In order to succeed there must be good private investment opportunities (Aiyar et al.,

2008).

When effective import demand is impeded by government crowding out, then there is

the possibility of an indirect effect on imports due to a decrease in debt. This eventually

would prevent a Dutch disease to occur. On the other hand, when a decrease in debt does not

result in affecting effective import demand, a Dutch disease still could arise, although the

effects on inflation and the domestic interest rates are usually ambiguous.

If the aid inflows are converted in local currency, private consumption and investment

could increase due to increasing interest rates, but it is also possible that imports are not

affected. This could result in an upward pressure on the exchange rate. When having a fixed

exchange rate regime, the government needs to react by using monetary policy. The exchange

rate will decrease, but the interest rates will be affected by an upward pressure. Thus the net

effects on the interest rates are ambiguous and could either be negative or positive (Hansen

and Headey, 2007).

To conclude there is a brief summary of what is entailed by different combinations of

absorption and spending. In this summary the macroeconomic consequences of policy choices

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involving different mixes of absorption and spending are outlined in figure 3. A note should

be made for the fact that these four outcomes, and the miscellaneous channels by which such

outcomes are reached, are not commonly exclusive. Aid can be spent partially on domestic

spending (with mixed effects on import demand), partially on imports, partially used to

accumulate FEX reserves and partially used to lower the government deficit or to retire debt.

Figure 3 Macroeconomic impact of different mixes of absorbing and spending

Absorbed Not absorbed

Spent

Central bank sells foreign exchange and fiscal deficit increases as aid is spent

Aid finances public consumption and investment

Money supply unchanged. Dutch disease may occur

Central bank accumulates foreign exchange as reserves; fiscal deficit increases as aid is spent

No real resource transfer

Unsterilized: money supply increases. Inflation may occur

Sterilized: crowding out of private sector. Domestic debt accumulates

Not spent

Central bank sells foreign exchange, but fiscal deficit does not change

Instrument to attain stabilization, provides resources to finance private investment

Central bank accumulates foreign exchange as reserves; no change in fiscal deficit net of aid

No real resource transfer

No Dutch disease

Equivalent to saving aid, or to rejecting aid (in the long-run)

Source: Aiyar and Ruthbah (2008)

The main questions remain: which of these combinations is best and how do they affect

growth ?

This depends on many factors, including the existing debt burden, the exchange rate

regime, the level of official reserves, the current level of inflation and the degree of aid

volatility. The IMF (2005) states that some situations require other responses than others:

Absorbing and spending: this scenario is under “normal” circumstances the first-best

response. In this scenario aid finances the rise in net imports, which will cause a real

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resource transfer. As a result government expenditures will increase.

In this scenario, aid may positively affect growth via government expenditures. These

expenditures increase growth in the short run through the effects of associated spending

on aggregate demand and in the long run through the increase in the capital stock

permitted by the associated investment (IMF, 2005).

Absorbing and no spending: This scenario would appear to be the best response when

inflation is too high (fiscal policy might be too expansionary), private investment is low

due to scarce resources and the return on government expenditures is relatively low. Not

spending the aid however is difficult, because donors have certain interests when granting

aid. Not spending is only possible when the government budget is fungible.

In this scenario, aid might positively affect growth due to the fact that aid is used to

achieve stabilization. Authorities sell foreign exchange to sterilize the monetary impact of

domestically-financed fiscal deficits. This will result in slower monetary growth and

lower inflation. As the inflation tax declines, demand will rise corresponding with an

increase in private consumption and investment. However the impact on growth depends

whether there are good private investment opportunities (IMF, 2005).

Neither absorbing nor spending: this scenario is a good response in the short run when

governments want to accumulate their FEX reserves or smooth volatile aid. When the

amount of received aid is high, but will fall in the short run, building up FEX reserves will

help to stabilize the real exchange rate. Nevertheless, this scenario is not appropriate when

the amount of received aid remains high in the long run. However this scenario could be a

good response when a Dutch disease seems to occur that will fully outweigh the gains of

the aid absorption.

This scenario only has a positive effect on growth in the long run. This scenario

simply implies that aid is used for saving. These savings may later be used to finance

investment, but in the short run this has no effect (IMF, 2005).

Spending and not absorbing: This scenario is the least attractive one. It indicates the lack

of coordination between fiscal and monetary policy. It is inappropriate to accumulate

reserves and to finance the government expenditures by increasing the money supply.

Applying sterilization by selling treasury bills will also not have the desirable effect as it

will cause a switch in resources from the private to the public sector.

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This scenario is unlikely to have a positive effect on growth. Fiscal deficits rise, there

is a chance on inflation and domestic debt accumulates. These effects all have a negative

impact on growth (IMF, 2005).

2.2 Macroeconomic impact of foreign aid: growthMost literature concerning foreign aid is focusing on the relationship between foreign aid and

economic growth. The question whether foreign aid helps countries growing in a sustainable

way is therefore one of the most important topics in economics. However, this question has

been discussed for years and no one came up with a final solution. Some researchers conclude

that foreign aid has no positive impact on growth or even has a negative impact under the

wrong circumstances. Others found that aid has a positive effect on growth or that growth in

the absence of aid would have been much worse.

Nevertheless it is not surprising that this research has various outcomes for several

reasons. Some observers just look at the facts and see that aid misses its objective, namely

spurring economic growth. However, others indicate that other factors also may affect both

aid and growth. Countries that suffered an endemic disease or a lengthy civil war may have

received a large aid inflow which positively affected economic growth, although the overall

growth rate was low or even negative (Radelet, 2006). Moreover, one could point out that

growth is not the main objective of aid at all. For example, countries which are suffering from

natural disasters. In that case, aid is aimed at humanitarian needs and supporting direct

consumption, not at building productive capacity. In addition, aid can also be aimed to

countries that try to build political systems, support a democracy or can flow for political

reasons (Alesina and Dollar, 2000).

Other studies showed that the conditions also play an important role when it comes to

the positive impact of aid on growth. Aid might tend to increase growth in countries with a

good economic policy environment, but might fall short in countries in which this is not the

case, for example when there is a high level of corruption (Burnside and Dollar, 1997).

The debate on whether aid helps spurring growth or not, the conditions under which

aid works or does not work and on what steps can be taken to make aid more effective, has

been ongoing for decades and will continue in the future. The empirics on these issues are

mixed, reaching different conclusions under various scenarios (time frame, countries and

other factors). However, three views have become widely accepted. These three views will be

discussed in the next sections.

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2.2.1 Aid has a positive impact on growth There are three main channels through which aid might stimulate growth:

• First, early studies assumed that foreign aid increases savings, finances investment and

raises the capital stock. Chenery and Strout (1966) incorporated this idea into a theoretical

framework, the so-called “two-gap” theory. This model used the growth process of the

Harrod-Domar growth model, which considers the level of investment in physical capital

(measured by the ratio of physical capital to GDP) and the incremental capital output ratio

(ICOR) as the key factors to spur growth. Developing countries have surplus labor but their

ability to invest is constrained by a lack of domestic savings (saving gap) and foreign

exchange availability (trade or foreign exchange gap). Thus there are not enough relevant

resources to lead to the achievement of higher levels of growth. In this context, the two-gap

model illustrates that aid inflows would supplement domestic savings and foreign exchange

earnings one-for-one. Therefore, more aid inflows will lead to higher investment and

ultimately to higher growth.

However, this theoretical view has been challenged on various grounds. Poor countries

are incompetent to generate sufficient amounts of saving to finance investments that are

essential to spur growth (Sachs et al., 2004). Furthermore there is criticism on the assumption

of the two-gap model which states that aid inflows will be matched by a one-for-one increase

in investment. Much of the aid effectiveness literature points out that there are possibilities

that this assumption may be incorrect (White, 1998).

• Second, aid might help financing health or education projects that may lead to an increase in

worker productivity. Health is one of the building blocks for human capital. With a better

health status, workers can increase their productivity as their physical capability such as

endurance or strength and mental capability such as awareness, insight, faster process of

information grows (Bloom and Canning, 2005).

Moreover, education is important to build human capital. Workers that have had a

better education generally have a higher rate of literacy and numeracy. Better-educated

workers have less problems adapting to more difficult assignments. Countries with well-

educated labor have a better chance of catching up with more advanced economies when they

have a stock of labor with the necessary skills to develop new technologies themselves or to

adopt and use foreign technology (World Bank, 2004).

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• Third, aid could finance the import of capital by transferring new technologies or assistance

in how to use the technical equipment. Therefore there will be a transfer of knowledge or

technology from donor to recipient countries (Radelet, 2006).

In early literature many researchers found a positive relationship between aid and growth. In a

cross-country analysis Papanek (1973) showed that aid fills both the savings as well as the

exchange gap and is best given to countries with a small balance-of-payment. Singh (1985)

and Snyder (1993) extended his model with state intervention and country size respectively,

and came to the same conclusion. However in the mid 1990s researchers started to test not

only for a linear relationship, but also focused on diminishing returns or on conditional

relationships. Numerous studies also found a positive relationship in the aid-growth nexus

when taking these two matters into account (Hadjimichael et al., 1995; Durbarry et al., 1998;

Dalgaard and Hansen 2000; Hansen and Tarp, 2000; Lensink and White, 2001; Dalgaard and

Tarp, 2004; and Clemens et al., 2004). Nevertheless, the overall conclusion was not that aid is

effective in every single country, but that an increase in aid in combination with other factors

on average resulted in a higher growth rate. This research shows that other factors, for

example geography (Gallup, Sachs and Mellinger, 1999), political instability (Oechslin,

2006), policy environment (Burnside and Dollar, 1997 and World Bank, 1998 among others),

institutions (Knack, 2001) and government interventions in the private sector

(Ruhashyankiko, 2007) account for the differences in growth rates among countries that

receive aid.

2.2.2 Aid has no affect on growth One of the first researchers who questioned the positive relationship between aid and growth

was Bauer (1972). However, he could not emphasize his argument with systematic empiric

evidence. Later, many empirical studies agreed on Bauer’s view, which incorporated the

empirics to show that there was no relationship between aid and growth (Mosley, 1980;

Mosley et al., 1987; Dowling and Hiemenz, 1982; Singh, 1985; Boone, 1994; Rajan and

Subramanian, 2005).

These studies came up with miscellaneous reasons why aid might not affect economic

growth:

18


• First, aid simply could be wasted, for example on benefits for government members

(luxurious cars and houses) or it could promote corruption (Tavares 2001 and Kasper 2006)

• Second, aid can assist incompetent governments to maintain control. In other words, serving

to continue leading the country with a poor economic policy climate without intentions to

reform this climate. Some researchers even lay out that aid flowing into countries which are

suffering from war might support the war, because aid is used to buy weapons. This leads to

further instability (Radelet, 2006).

• Third, countries may have problems to use aid efficaciously due to absorptive capacity

constraints. These absorptive capacity constraints are factors which limit the ability of

recipient countries to put aid flows to good use. These factors include relatively few skilled

workers, weak infrastructure or constrained delivery systems. It implies that there are

diminishing returns to aid after it reaches a certain level (Guillaumont and Jeanneney, 2007).

• Fourth, foreign aid can decrease domestic savings, both private saving (through a decline in

interest rates/rate of return on investment) and government saving (through a fall in tax

revenue). Furthermore financing of the returning projects costs, for example, would lead to

higher government consumption and thus a fall in government savings. Ceteris paribus, this

would tend to reduce domestic savings (Ouattara, 2004). Nevertheless, there is some criticism

on this point, because aid inflows could also be aimed at stimulating consumption and not at

investment. For example food aid, immunization programs, purchase of textbooks and

technical assistance (Radelet, 2006).

• Fifth, foreign aid inflows could weaken private sector incentives for improvements in

productivity or investment. When aid flows are spent on the non-traded sector rather than on

imports, it could lead to an appreciation of a country’s real exchange rate in the short run.

This will make export less competitive, so exports will fall. If aid does not lead to a rise in the

non-traded goods supply, the real exchange rate could be higher. This could lead to a long-run

loss of competitiveness proportional to the aid received and spent. Because these tradable

activities are the main reasons behind increasing productivity, economic growth might be

affected negatively in the long run. As mentioned before, these effects are called Dutch

disease (Corden & Neary, 1982; Rajan and Subramanian, 2005; Bulir and Lane, 2002; Prati

and Tressel, 2006).

19


These are the main five reasons found in literature why there is no relationship between aid

and growth. Nevertheless, not many studies have reached this conclusion. This is due to the

fact that most research does not take diminishing returns into account and instead uses a

model with the restriction of a linear relationship between aid and growth.

Furthermore, most studies only analyze aggregate aid, assuming that all aid effects

economic growth in a similar way. This is not realistic, since famine relief, immunization

programs, and infrastructure projects tend to effect economic growth in different ways

(Radelet, 2006).

2.2.3 Aid has a conditional relationship with growth

This view has had most support in literature. It holds that under certain circumstances aid

works better than under others. Furthermore this view looks for main characteristics to

explain the difference. This view has three subcategories which determine aid effectiveness:

recipient country characteristics, the donor practices and procedures, or the type of aid.

Recipient country characteristics

The first researchers emphasized this conditional view were Isham, Kaufmann and Pritchett

(1995). They questioned the effect of civil liberties in the aid-growth nexus. Their results

show that aid spent on World Bank projects in countries with stronger civil liberties had

higher rates of returns. However, the most influential paper on this conditional strand came

from Burnside and Dollar (1997). In “Aid, Policies and Growth” they concluded that aid

promotes growth in countries with good fiscal, monetary and fiscal policies. Their model was

further examined by the World Bank (1998), Collier and Dollar (1999) and Svensson (1999)

who support the Burnside-Dollar view. However, their conclusion also resulted in some

criticism. Lensink and White (1999), Guillaumont and Chauvet (2001), Hansen and Tarp

(2001), Lu and Ram (2001), Akhand and Gupta (2002), Easterly et al. (2004) and Dalgaard

and Hansen (2005) to name a few, oppose these results on statistical grounds and provide

evidence in favor of the hypothesis that aid raises growth regardless of the quality of the

policy environment. Easterly, Levine and Roodman (2004) stand out for using the same

econometric technique, specification and data. They conclude that Burnside and Dollar’s

results do not hold up to modest robustness checks.

After Burnside and Dollar (1997) many researchers addressed different country

characteristics that might affect the aid-growth relationship. For example, export price shocks

20


(Collier and Dehn, 2001) , climatic shocks (Guillaumont and Chauvet, 2001), the terms of

trade (Guillaumont and Chauvet, 2002), institutional quality alone (Burnside and Dollar,

2004), policy and warfare (Collier and Hoeffler, 2002), type of government (Islam, 2003) and

location in the tropics (Dalgaard, 2004).

Nevertheless, Burnside and Dollar’s view that aid is more effective in countries with a

sound policy environment has widely been adopted by donors. The popularity of this

approach is that it illustrates why aid seems to have a positive impact on growth in countries

with a good policy regime. Furthermore this approach has been adopted by the World Bank in

their Performance Based Allocation (PBA) system for allocating concessional International

Development Association (IDA) funds and was the foundation for the United States’ new

Millenium Challenge Account (Radelet, 2003).

Donor practices and procedures

Numerous studies have showed that donor practices and procedures have a strong impact on

the effectiveness of aid. For example, multilateral aid (aid given a country to an international

agency, such as the World Bank or IMF) might have a stronger impact than bilateral aid (aid

given by one country directly to another), since countries normally spend bilateral aid on

military, political and economic interests which tend to have lower returns on aid than

multilateral aid which has weaker donor control and neutralized ulterior motives (Ram, 2003).

Furthermore it is argued that ‘untied’ aid (aid given to developing countries which can

be used to buy goods and services in all countries) is thought to have higher returns than ‘tied’

aid (aid given to developing countries which can be used to purchase goods and services in

the donor country or in a limited selection of countries). These limitations hinders a country in

finding the most cost-effective way to spend the received aid. In addition, tied aid is mostly

spent on capital-intensive goods that are coming from the donor country’s sector that is most

profitable. This may result in purchases that are not necessary for realizing their development

goals. Furthermore untied aid is much more efficient than tied aid, which needs larger

bureaucracies in both the recipient and the donor country to administrate the aid activities.

Moreover, untied aid gives countries greater freedom to allocate their received aid. They can

purchase goods and services in the most cost-effective way (OECD, 2007).

Similarly, it is argued that donors with large bureaucracies, a lack of coordination with

other donors or ineffective monitoring and evaluation systems receive lower returns on their

aid programs (Radelet, 2006). To make aid more effective the World Bank organized a

meeting in order to improve aid effectiveness. This resulted in the Paris Declaration (2005).

21


The Paris Declaration states that countries are responsible for their own development. They

should establish partnerships with other countries, while donors might support them with

better coordination among them, capacity development and more predictable aid flows. This

resulted in five principles: ownership, alignment, harmonization, managing for results and

mutual accountability. In short, this means that countries need to strengthen their capacity to

manage development and need to establish effective partnerships with donors.

Type of aid

There are various types of aid that might influence economic growth in several ways.

Clemens, Radelet and Bhavnani (2004) divide aid into three categories that are most or least

likely to have an impact on growth. The three categories are:

Emergency and humanitarian aid: this type of aid would have a negative simple

relationship with growth, since an economic shock would simultaneously cause growth to

fall and aid to increase. Aid is aimed at humanitarian needs and supporting direct

consumption, not at building productive capacity.

Short-impact aid: this type of aid will positively affect growth rates fairly quickly. Aid

that will build infrastructure, support productive sectors and support the balance-of-

payments should be expected to positively affect growth immediately if it is to do so at

all. Research shows that there exists a strong positive relationship between this type of aid

(about half of all aid) and growth, a result that remains intact after testing for robustness.

Long-impact aid: this type of aid might affect growth, but if so only indirectly and over a

long period of time. Aid that supports democracy or protects the environment is unlikely

to affect growth in the short-run. Similarly, aid that strengthens health and education is

likely to affect labor productivity over many years, but not immediately.

Figure 4 shows the relationship between the three categories of aid and economic growth as

constructed by Clemens, Radelet and Bhavnani (2004).

Figure 4 The relationship between three types of aid and growth

22


Source: Clemens, Radelet and Bhavnani (2004).

To sum up the aid and growth research, there is not yet established consensus on the

relationships between aid and growth. Aid is dependent on many factors to be effective.

However, must studies show that aid positively affects growth when taking various

circumstances into account. A different model, data or countries of analysis may result in very

different conclusions. Since the debate continues about the determinants of economic growth,

it is not surprising that the aid-growth relationship is left open to further research.

As this study is motivated by the influential paper of Burnside and Dollar (1997), it

will reexamine their research and test four hypotheses:

Does aid affect growth?

Does aid affect growth when it is dependent on good policies?

Does aid affect growth when it is dependent on good policies and is being controlled

for diminishing returns?

Do domestic saving via foreign aid and FDI lead to higher growth?

3 Data and empirical strategyThis chapter will elaborate on the methodological approach used to find support for any of the

four hypotheses by using ordinary least squares (OLS) and Two-Stage least squares (TSLS)

23


regressions with input of empirical data. The methodological approach is based on the study

of Burnside and Dollar (1997). The results of the used methodology are shown in the next

chapter.

3.1 Data descriptionThe regressions are based on data of the 20th century. Since data on various control variables

is scarce and in most cases only available in national databases, this paper makes use of a

already existing set of data from different sources collected by Roodman (2004). Their dataset

contains, in addition to self gathered data, data on openness, assassinations, institutional

quality and fractionalization taken from datasets of Sachs and Warner (1995), Banks (2002)

Knack and Keefer (1995) and Roeder (2001). This adds up to a dataset existing of 458

observations covering 107 countries over the period 1970-2001.

Dependent variable

The dependent variable in this dataset is GDP per capita growth. This variable is used as a

measure of economic growth and indicates the level of total economic output. It reflects changes

in the amount of goods and services produced. Data are obtained from the World Bank’s World

Development Indicators (2008).

Independent variables

The choice of the control variables is mainly based on the findings of Burnside and Dollar.

Their set of control variables is expanded with two additional variables. All included variables

are averaged over four years per country. The following paragraph will elaborate on the

choice of control variables.

Aid is measured by total aid as a share of recipient GDP, but there is a split in defining

numerator and denominator. Burnside and Dollar (1997) use Effective Development

Assistance in the numerator while others use net Official Development Assistance. However

Dalgaard and Hansen (2002) show that there exists a correlation of 0.98 between EDA and

ODA and that they yield approximately similar results. Furthermore there is no consensus

which denominator to use. Burnside and Dollar (1997) use real GDP from the Penn World

Tables, while others use GDP converted to dollars using market exchange rate. This paper

will follow the line of Burnside and Dollar, thus will be using EDA as a share of real GDP.

24


This paper also includes a quadratic term in aid to capture the possible presence of

diminishing returns.

The initial GDP per capita indicates the conditional rate of convergence, i.e. closing

the gap between low-income and middle- income countries. To close this distance between

the poor and less poor, the very poor countries have to grow much faster than the less poor.

Thus countries with a higher initial GDP per capita will grow less than countries with a lower

initial GDP per capita. This variable is thus ought to be negative.

Institutional/political variables

Knack and Keefer (1995) indicated that security of property rights and efficiency of

government bureaucracy are good instruments to measure institutional quality. Governmental

institutions are important for a stable economic climate where economic activity,

inventiveness, growth and development can flourish. Intuitively this variable will have a

positive effect on growth.

Another variable which remains relatively constant over a long period is an index of

ethno-linguistic fractionalization and has been used by Easterly and Levine (1997). A high

level of this ethno-linguistic fractionalization often means that there is no sound policy

environment and the growth performance is poor.

In addition, the “assassination” variable is used, since numerous studies have shown

that this variable involves civil discontent. Furthermore there will be an interaction between

ethnic fractionalization with assassinations (Burnside and Dollar, 1997). These variables are

included to capture the effects of political and social conditions on growth, which will

intuitively have a negative effect. Data are obtained from the dataset of Roodman (2004).

Missing values for ethno-linguistic fractionalization are filled in from Roeder (2001).

Economic policy variables

This paper will follow the line of Burnside and Dollar (1997) and will construct a policy

index. This index is defined as the weighted sum of budget surplus/deficit, inflation rate and

the Sachs-Warner openness index where each component is weighted by its coefficient in the

growth regression. Data for the budget balance and inflation rate are obtained from the World

Bank’s World Development Indicators (2008). Data on openness are obtained from the

dataset of Roodman (2004).

Openness is used to indicate international trade. Various channels, such as access to

foreign technology, greater access to miscellaneous production inputs and access to broader

25


markets which are specialized and increase the efficiency of domestic production have a

psotive impact on economic growth. Economies are considered closed when average tariffs on

machinery and materials are above 40%, or when the black market premium is above 20%, or

when key tradables are strictly controlled by the government.

Fiscal policy is measured by the budget surplus (fiscal balance) as a percentage of

GDP. This indicator was first introduced by Easterly and Rebelo (1993) and later used by

Dollar and Burnside (1997). The budget surplus is ought to be a stabilizing instrument for the

government. Furthermore, monetary policy is represented by inflation as suggested by Fischer

(1993), as it is considered to be an indicator of stability. A stable government is ought to

affect growth positively.

Other variables

The total government expenditure as a percentage of GDP indicate the share of the public

sector in the economy. This variable is ought to be negatively related to economic growth,

because poorly operating public firms and large bureaucracies create impediments to the

process of spurring growth.

Moreover the money supply (M2) as a share of GDP is used, to proxy for distortions

in the financial system (King and Levine, 1993). To overcome the problem of endogeneity

this variable is lagged one period. Small values are associated with repression and large

values with liberalism. Small values are expected to be detrimental to economic growth. Data

are obtained from the World Bank’s World Development Indicators (2008).

Two additional variables

In this paper FDI is introduced as a new control variable. FDI has a positive impact on growth

through various channels. First, FDI increases the export of manufactured products when a

country can utilize its comparative advantage. Second, productivity may increase through a

technology spillover effect as the result of FDI. Third, FDI can bring better market conditions

and better management knowledge as domestic firms observe these new activities, this is also

known as the demonstration effect (Campos and Kinoshita, 2002).

A second newly added variable is domestic saving. Early literature pointed out that

domestic savings spur economic growth via investment. As most countries are importers of

capital, a higher level of domestic saving is required to bring more capital from abroad into

the country in order to stimulate investment (Carroll and Weil, 1994). Data for both variables

are obtained from the World Bank’s World Development Indicators (2008).

26


Following Burnside and Dollar (1997), regional dummy variables for East Asia and

sub-Saharan Africa are also used.

Definitions and sources for all the variables used in the data sample are provided in appendix

A1. A list of all included countries is given in appendix A2. A data set covering the eight

four-year periods from 1970-2001 for 107 aid-receiving countries is used. Data is mainly

obtained from the World Development Indicators (WDI, 2008). As some data are missing for

some countries, because they are either not available or not disclosed, the total number of

observations is reduced.

3.2 Empirical model specificationThe empirical model applied to estimate the relationship between foreign aid, the policy

environment and economic growth can be written as follows:

git= β0 + β1Yit + β2ait + β3Pit + β4aitpit + β5a²itpit + β6xit + μit (1)

where

git represents the real per capita GDP growth rate,

Yit is the initial level of real per capita GDP,

ait is the foreign aid as a share of GDP,

Pit is the P x 1 vector of policies that influence growth,

Xit is the K x 1 vector of other exogenous variables that might influence growth and

the allocation of aid,

Aitpit is the interaction term which measures aid effectiveness in a good policy climate

μit denotes the error term which captures all the unobservable factors that affect the

growth rate

a²itpit is the quadratic aid term interacted with policy to measure diminishing effects of

aid conditional on good policy

β represent the coefficients of the various independent variables

i and t index country and time respectively.

Equation (1) is similar to the growth model that Burnside and Dollar (1997) estimated. The

27


main objective of this paper is to analyze whether aid works better in a good policy

environment. Therefore the coefficient of (Aid*Policy) must be strongly significant as

Burnside and Dollar found or not as others like Easterly, Levine and Roodman (2004) found.

Following Knack and Keefer (1995), Easterly and Levine (1997), Burnside and Dollar (1997),

World Bank (1998), Hansen and Tarp (2001) and Easterly et al. (2003), this paper also

captures a vector of exogenous variables (Xit). The per capita growth rate or foreign aid do

not affect these variables. This vector contains include various institutional and political

variables that might have an impact on growth.

To illustrate the impact of foreign aid on economic growth when accounting for a

good policy environment, the first order derivative of the economic growth model is taken:

∂git / ∂git = β2 + β4pit (2)

This derivative expresses hypothesis two, which states that the impact of aid on growth

depends on a good policy environment.

As the empirical growth model is set out to run OLS regressions, the concern over

endogeneity has not been tackled yet. Endogeneity occurs when the independent variables are

correlated with the error term. This implies that the regression coefficient is biased in the OLS

regression. In this case, it is possible that the aid variable is not completely endogenous and

therefore uncorrelated with the error term. To solve this problem instrumental variables can

be used to create a source of exogenous variation in the aid variable. A valid instrument must

meet two conditions: relevance and validity. Firstly, the instrument that may be used has to

be correlated with aid, and secondly this instrument must be exogenous i.e. uncorrelated with

growth and the error term (μit).

The first stage equation yields the following outcome:

Âit = β0 + β1Yit + β2pit + β3Xit + β4Zit + μit (3)

where μit expresses all the unobserved factors that have an impact on foreign aid. Yit

represents the initial level of real GDP per capita, Pit is a constructed policy index and Xit is a

28


vector which denotes all the exogenous variables. The Zit variable expresses the instruments

that are required in the TSLS regressions to instrument for aid. The outcome of the OLS

regression of equation (3) is used to create TSLS model:

git= β0 + β1Yit + β2âit + β3Pit + β4âitpit + β5â²itpit + β6xit + μit (4)

Equation (4) is practically similar to equation (1), except that the original aid variable is now

replaced by an instrumented aid variable. Equations (1) and (4) will be used to examine the

effects of aid on economic growth empirically.

A concern when applying TSLS regressions is the robustness. This relies on the

availability and quality of the instruments. However, it is hard to find variables that are

correlated with foreign aid, but uncorrelated with economic growth. Nevertheless, previous

literature (Boone, 1996) has offered various appropriate instruments. The first instrument is

the natural logarithm of population. This instrument accounts for the fact that countries with a

larger population need to have more foreign aid. However, institutions prefer to give foreign

aid to smaller countries, because this is cheaper. As Boone (1996) exclaims, “minimal

amounts can be transferred due to fixed costs of entry.” Similarly, the infant mortality rate is

used as an instrument to account for growth-inducing characteristics.

Other instruments are the proxies for donors’ strategic interest. The specific donor

interest variables that will be used are dummies for Central American countries (which are in

the U.S. sphere of influence), the France Zone in Africa and Egypt. These instruments are

included to capture the political ideas behind the allocation of aid. The strategic interest of

donors will be uncorrelated with growth only if the recipient country is given aid only for

historical and political reasons.

4 Regressions and resultsThe following chapter will describe the empirical research which is conducted in line with the

strategy described in chapter three.

29


4.1 OLS Growth RegressionsFirst, following Burnside and Dollar (1997), equation (1) is estimated excluding aid and the

policy index by using a simple OLS model for an unbalanced panel of 107 aid receiving

countries across eight four-year periods. The regression results are presented in column 1 of

table 1.

Regression (1.1) is run to examine whether the independent variables have a

significant impact on growth. The independent variables explain 33.2% of the variation in the

real GDP per capita growth rate with a R² of 0.332. Variables that are very robust in

regression (1.1) are institutional quality, inflation, initial level of per capita GDP, domestic

saving and the dummy for Sub-Saharan Africa which are generally significant in the growth

regression. Various other studies show similar results concerning coefficients of these

variables. The initial level of GDP for example, which has a negative coefficient (-1.27). This

implies that on average, whilst controlling for other variables, a 1% increase in the initial level

of GDP results in a 1.27% decrease of the growth rate. This supports the theory that a high

initial level of GDP has a negative impact on economic growth.

The next step is to construct a measure for policy. Therefore a policy index is built, which

consists of budget balance, inflation and openness. To form the index, regression coefficients

are used from column 1 of table 1:

Policy = 1.55 + 4.45 Budget Balance – 2.36 Inflation + 0.39 Openness

Thus regression (1.1) gives weight to the three different components of the policy index. The

constant indicates the effect of the remaining variables when the mean of these variable is

taken to run the regression. The policy index expresses the forecasted growth rate of a country

given its budget, inflation and openness policies, assuming that the other variables had their

mean values. The index can either be negative if inflation is high or if the budget deficit is

very large.

In comparison with Burnside and Dollar (1997) the budget balance (coefficient of

5.35) and openness (coefficient of 2.07) of a country have less impact on policy, but inflation

(coefficient of -1.41) has a larger effect. This as the result of expanding the dataset with more

countries. Openness for example does not have a large impact, due to the fact that

30


globalization has even more expanded and countries tend to be more and more open, so that

there is less difference between countries.

In regression (1.2) aid is included to test the hypothesis that foreign aid has a positive

effect on economic growth. This hypothesis is tested against a two-tailed alternative.

H0 : βa = 0 (5)

HA : βa ≠ 0 (6)

The regression results reveal that aid has a significant positive effect on economic growth.

Aid has a t-statistic of 2.34 which means that is significant at the 5% level. Therefore the null

hypothesis can be rejected showing that aid has indeed affects economic growth. This is not

consistent with the results of Burnside and Dollar (1997) which state that aid alone has no

effect on growth. Other significant variables are the initial level of GDP per capita,

assassinations, institutional quality, inflation and the Sub-Saharan Africa dummy.

Regression (1.3) tests the hypothesis that aid effectiveness increases when a country

has a sound policy climate. Again, this hypothesis is tested against a two-tailed alternative:

H0 : βap = 0 (7)

HA : βap ≠ 0 (8)

Column three in table 1 however shows that the term Aid x Policy is insignificant. The null

hypothesis cannot be rejected, which indicates that foreign aid does not depend on a good

policy environment to be effective. Inserting the interacted Aid x Policy term vanishes the

significance of aid on its own. Furthermore it is interesting that this is also the case with the

budget balance. This result opposes the outcome of Burnside and Dollar (1997). Their

regression showed that aid interacted with policy was significantly positive. The result of this

paper however are in line with papers that showed that aid interacted with policy has no

influence on growth (Easterly et al., 2004; Hansen and Tarp, 2000; Dalgaard and Hansen,

2005 among others).

Regression (1.3) is expanded in regression (1.4) with quadratic aid interacted with the

policy term. This variable implies whether aid is effective in a good policy climate if the

possibility of diminishing returns is taken into account. The null and alternative hypothesis

are as follows:

31


H0 : βa²p = 0 (9)

HA : βa²p ≠ 0 (10)

It can be seen from column 4 in table 1, that aid indeed is effective in a good policy

environment when controlling for diminishing returns. It is remarkable that including the Aid²

x Policy term changes the sign of the Aid x Policy term. It is turned from a insignificant

positive variable into a negative significant variable. This results now that on average, holding

the other variables constant, 1% more foreign aid results in a decline of 0.24% of economic

growth when foreign aid being directed is aimed at countries with a good policy climate. This

is not in line with the conclusion reached by Burnside and Dollar which states that the policy

environment has a positive impact on aid effectiveness.

The variables which differ from Burnside and Dollar, FDI and domestic saving, show

mixed results. FDI is insignificant and has no effect on economic growth. Due to its low

explanatory power, FDI will be dropped in the TSLS regressions. In addition government

consumption will be left out, because this variable is also insignificant. Excluding these two

variables do not affect results. Domestic saving however has a positive coefficient and is

highly significant. This is in line with the theoretical literature regarding this matter.

Two variables that show a high level of significance in all four OLS regressions are

inflation and institutional quality. This result implies that financial stability and the fact that

there are stable and good institutions do help in attaining economic growth. Moreover, both

the Sub-Saharan Africa and East Asian dummy are significant. This is conform theory, that

countries located below the Sahara have lower economic growth and countries in East Asia

have higher growth in comparison to countries located elsewhere.

Another variable that stands out in the OLS regressions is the initial level of GDP per

capita. It is revealed that the initial level of income is statistically significant, thus indicating

conditional convergence among the countries in the sample, which contradicts the general

findings of previous studies.

Previous research has had some problems with the endogeneity of the results of the

OLS regressions. Section 4.2 will examine whether the endogeneity is an important concern

and tries to address it.

32


4.2 Two-Stage Least Squares Growth regressionsThere are several reasons to be skeptical about the OLS results presented above. The likely

endogeneity of aid was not taken into account. This section will try to address whether there

are unobserved factors that are correlated with foreign aid and have an impact on economic

growth. Not only the endogeneity of aid is a problem, but also the endogeneity of the policy

index. The belief that aid effectiveness increases when it is allocated to countries with a good

policy environment becomes weaker when it is known that the allocation of aid is influenced

by the policy level. In other words, countries that do not have sound institutions and a good

policy environment are maybe not granted aid at all. However it is difficult to find policy

instruments, so the assumption is made that the policy level is totally exogenous.

TSLS regression (2.1) mainly follows the line of the original OLS regression results.

Remarkable is that the financial quality variable (M2/GDP) has turned from a negative to a

positive sign. Conventional wisdom states that as financial liberalization increases, a country

is able to spur growth (King and Levine, 1993). Previous studies all showed that this variable

is significantly positive and this paper is no exception. This adds that the TSLS results are

more robust in comparison with the OLS results. Similarly ethnic-linguistic fractionalization

stands out. In the OLS regression this variable was already significant at the 10% level, but

applying TSLS this becomes significant at the 1% level, which increases the robustness of the

result.

In addition the aid variable remains statistically significant. This empirical evidence

gives a positive answer to hypothesis 1 which assumes that aid positively affects growth. On

average, whilst controlling for the other variables, increasing the amount of foreign aid with

1% results in an 0.54% increase of economic growth. This is consistent with the majority of

previous literature.

OLS regressions refuted the belief that aid granted to countries with a good policy

environment works better in spurring growth. When applying TSLS regressions the same

result pops up. The TSLS regression also does not provide any significant evidence that aid

works better in a good policy environment. Regression (2.2) tests the hypothesis that a stable

policy environment promotes more effective foreign aid. The test statistic (1.42) in regression

(2.2) is smaller than the critical values at the 10%, 5% and the 1% levels and is therefore

insignificant. This implies that aid effectiveness is not conditional on good policies.

33


As can be seen in column 3 of table 2, this result still holds if aid is controlled for

diminishing returns. This variable is also not significant and follows the line of the many

criticasters of the results of Burnside and Dollar, that aid does not help spurring growth in a

good policy environment.

A variable that was very significant in the OLS regressions and that remains

significant applying TSLS, is domestic saving. The level of the domestic savings rate thus

positively affects growth. On average, holding everything else constant, a 1% increase in the

domestic savings rate corresponds to a 0.25% increase in growth. This is in line with the

theory of Carroll and Weil (1994).

5 Conclusion and remarks

34


Many papers have yet tried to solve the aid-policy-growth nexus. Nevertheless, a common

conclusion has not been established yet. Results so far have been ambiguous and this paper

joins other work that has not come up with an overall conclusion. This paper examines the

aid-policy-growth nexus on the basis of four important hypotheses: firstly, aid has a positive

impact on growth. Secondly, the impact of aid depends on a good policy environment.

Thirdly, foreign aid helps in a good policy environment when taking diminishing returns into

account and finally, domestic saving and FDI lead to economic growth

The first hypothesis is whether aid positively affects growth. When applying OLS, this

paper shows that on average, foreign aid has a small explanatory power which is in line with

other studies such as Easterly, Levine and Roodman (2004) that tried to reestablish the

Burnside and Dollar estimates. When applying a TSLS approach this power becomes even

stronger, implying aid on its own has a positive effect on growth. However, it is incorrect to

claim that aid positively affects growth in all cases. Aid can take many forms - like bilateral

or multilateral and tied or untied – but the model do not use these forms as estimators.

Furthermore, EDA does not register all foreign aid flows. This may also had impact on the

outcome.

The second hypothesis states that aid granted to countries with good policy climates

causes growth to spur more rapidly. Unlike the results of the first hypothesis, the results of the

second hypothesis are mixed The OLS regressions show that aid in a good policy

environment has a detrimental effect (when taking the Aid² x Policy term into account), but

the TSLS regressions show that policy conditions have no explanatory power at all. This

result is not consistent with the conclusions reached in Burnside and Dollar, but is in line with

the main criticasters of their paper like Easterly, Levine and Roodman (2004) and Hansen and

Tarp (2000). A possible explanation for this is that this paper expanded the Burnside and

Dollar dataset with new data that might have an influential impact in reaching different

results. In addition, policy was set to be exogenous in my model and thus did not correct for

endogeneity. This may have influenced the robustness of the results.

The third hypothesis states that foreign aid helps in a good policy environment when

accounting for diminishing returns. Including this variable does not change results. This term

remains insignificant in both the OLS and TSLS regressions and thus has no effect. This gives

rise to a negative answer to hypothesis three.

Finally, this paper hypothesized that FDI and aid directed to countries with a higher

rate of domestic saving would positively affect the growth rate of GDP per capita. Including

these two variables gave mixed results. FDI had no explanatory power at all and proves

35


empirically to have no significant effect on growth when implementing it as an additional

variable in the Burnside and Dollar model. On the other hand aid is more effective if given to

countries with a higher domestic savings rate. It is however hard to compare this result,

because no other paper has implemented this variable in an aid-policy-growth model.

Although this paper did not find any statistical evidence for the results of Burnside and

Dollar that aid spurs growth in a good policy environment, it does not imply that aid should

be ignored as an instrument for policy makers. As shown in both the OLS and TSLS

regression, aid on its own has a positive effect on growth, thus can be effective.

One problem that occurs while examining the aid-growth-policy nexus is the lack of

cohesion between the various papers on this matter. Each paper differs from another by using

different variables and different definitions, that no robust conclusion can be set yet. Further

empirical research, where a critical note can be made to the lack of cohesion between

previous studies, need to occur for setting an overall conclusion.

This lack of cohesion and the lack of an overall conclusion imply that a different

approach needs to be adopted. However, there is one variable that appears to be significant in

almost every study: the policy variable. This implies that a stable government adds to

increasing economic growth. This gives rise to maybe an important question: is it not better to

put emphasis on aid inflows that improve the political environment in a country instead of

direct financial flows?

This current situation where countries are just given cash is not a sustainable solution.

Recipient countries become dependent on these aid inflows and will not give an incentive to

governments to start positively affecting growth. As set out in the theoretic frame, aid can be

wasted easily on the enrichment of the government itself, but not on the country as a whole.

There has to be a reform concerning the targeting of aid before sustainable growth could

become realistic.

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7 TablesTable 1: OLS panel growth regression

44


Dependent Variable: per capita GDP growth Time dimension: eight four-year periods, 1970-1973 to 1998-2001 Regression Number (1.1) (1.2) (1.3) (1.4) Observations 451 446 446 446 Constant 9.6781 8.1065 8.0309 10.0135 (4.2540) (3.3416) (3.3080) (3.9534)

Initial GDP per capita -1.2771 *** -1.0666 *** -1.0710*** -1.3074 ***

(-3.9004) (-3.1102) (-3.1222) (-3.7030) Ethnic fractionalization -1.4253 ** -1.3032 * -1.2920 * -1.3701 * (-2.0104) (-1.8235) (-1.8072) (-1.9271) Assassinations -0.3527 -0.3898 * -0.3930 -0.3432 (-1.4970) (-1.6537) (-1.6667) (-1.4600) Ethnic x Assassinations 0.2745 0.3152 0.3104 0.2423 (0.5368) (0.6165) (0.6068) (0.4761)

Institutional quality 0.3249 *** 0.3192 *** 0.3171*** 0.3506 ***

(3.2880) (3.1610) (3.1391) (3.4635) M2/GDP (lagged) -0.0141 -0.0161 -0.0156 -0.0158 (-1.3672) (-1.5395) (-1.4878) (-1.5149) Budget balance 4.4470 * 5.7830 * 5.2282 6.3495 * (1.7228) (1.7290) (1.5379) (1.8643)

Inflation -2.3613 *** -2.3226 *** -2.0375*** -2.5463 ***

(-5.5056) (-5.5229) (-3.8962) (-4.5785) Openness 0.3888 0.4184 0.3636 0.3875 (1.1191) (1.1388) (0.9764) (1.0472) Government consumption 0.0362 0.0041 0.0075 0.0098 (1.0790) (0.1110) (0.2010) (0.2649) FDI inflow 0.1088 0.0562 0.0065 0.0628 (1.4423) (0.7062) (0.8106) (0.7875)

Domestic saving 0.0883 0.1018 *** 0.1009*** 0.1038 ***

(2.8327) (3.1804) (3.2839) (3.6751)

Sub-Saharan Africa -2.0650 *** -2.2237 *** -2.2479*** -2.1008 ***

(-3.9293) (-4.1714) (-4.2109) (-3.9378) East-Asia 1.0174 * 1.0039 * 1.0751 * 0.8437 (1.7352) (1.7146) (1.8199) (1.4208) Aid/GDP 0.2565 ** 0.1857 0.0954 (2.3447) (1.3874) (0.6931) Aid x Policy 0.0724 -0.2446 * (0.9173) (-1.6712) Aid² x Policy 0.0500 ** (1.5653) R-squared 0.3312 0.3207 0.3121 0.3126 Adjusted R-squared 0.3087 0.2863 0.2860 0.2853 a T-statistics (in parentheses) have been calculated with White’s heteroskedasticity-consistent standard errors, for all regressions in this paperb *** significant at <0.01, ** significant at <0.05, * significant at <0.1Table 2: TSLS panel growth regression

Dependent Variable: per capita GDP growth

45


Time dimension: eight four-year periods, 1970-1973 to 1998-2001 Regression Number (2.1) (2.2) (2.3) Observations 446 446 446 Constant 11.2754 11.4165 13.3354 (3.4947) (4.0937) (4.1086)Initial GDP per capita -1.8638 -1.6290 -1.8734 (-2.1359) * (-2.2136) * (-2.2578) *Ethnic fractionalization -1.5146 -1.4807 -1.5668

(-2.6822)*** (-2.7055)

*** (-2.8117) ***

Assassinations -0.2839 0.4962 -0.4507 (-1.9362) * (-2.0562) ** (-1.4600)Ethnic x Assassinations 0.1956 0.1109 0.0644 (0.4485) (0.6156) (0.4378)Institutional quality 0.2851 0.3359 0.2136

(2.8265)*** (3.3499)

*** (3.1157) ***

M2/GDP (lagged) 0.0491 0.0867 0.0938 (-1.6648) * (-1.7549) * (-1.6183) *Domestic saving 0.2114 0.2345 0.2199

(3.2661)*** (3.1794)

*** (3.4641) ***

Sub-Saharan Africa -1.3601 -1.4460 -1.3112 (-2.3655) ** (-2.3098) ** (-2.3160) **East-Asia 0.9232 0.9127 0.9053 (1.2256) (1.3967) (1.3431)Policy 0.8340 0.5941 0.5172

(3.9042)*** (1.9341) * (1.5025)

Aid/GDP 0.5364 0.8369 0.3427

(2.8630)*** (1.5347) (0.8984)

Aid x Policy 0.1978 0.2784 (1.2278) (-0.0056)Aid² x Policy -0.0962 (1.2451)R-squared 0.28569 0.29257 0.2846 Adjusted R-squared 0.26743 0.27432 0.2615

Instruments: Pop (Ln population), Pop², Inf (infant mortality beginning of period), Inf², Pop x Policy, Inf x Policy, arms imports (lagged), dummies for Egypt, franc zone countries, Central American countries

46


Appendix A1: List of variablesAll World Bank Data is taken from the WDI Online statistic database. Organisation for

Economic Cooperation and Development Data, from the OECD statistic database and the

other variables are taken from the Roodman (2004) Dataset.

Variable Description Source(s)Growth Per-capita GDP growth World Bank dataInitial GDP per capita* Natural logarithm of GDP/capita for

first year of period; constant 1985 dollars

Summers and Heston Penn World Tables, World Bank data

Aid (Effective Development Assistance)/ GDP*

Effective development assistance as a share of GDP

Chang, Fernandez-Arias, and Serven 1998; OECD-DAC 2002; IMF 2003;

Fractionalization* Probability that two randomly chosen individuals differ ethnically

Roeder 2001

Assassinations* Number of assassinations per 100,000 population

Banks 2002

Institutional quality* Security of property rights and efficiency

PRS Group’s IRIS III data set (see Knack and Keefer 1995)

M2/GDP (lagged) M2 as a share of GDP, lagged one period

World Bank data

Budget balance* Budget surplus as a share of GDP International Monetary Fund data, World Bank data

Inflation Natural logarithm of 1 + inflation rate World Bank dataOpenness* Dummy variable for trade openness Sachs and Warner 1995; Easterly, Levine,

and Roodman 2004; Wacziarg and Welch 2002

Government consumption Government consumption as a share of GDP

World Bank data

FDI inflow Foreign direct investment as a share of GDP

World Bank data

Domestic saving Domestic saving as a share of GDP World Bank dataSub-Saharan Africa* Dummy variable for Sub-Saharan

AfricaWorld Bank data

East-Asia* Dummy variable for East-Asia World Bank dataCentral Emerica* Dummy variable for Central America World Bank dataFranc zone* Dummy variable for Franc Zone World Bank dataEgypt* Dummy variable for Egypt World Bank dataArms imports* Arms imports as a share of total

imports, lagged one period U.S. Department of State, various years

Population* Natural logarithm of population World Bank dataInfant mortality Initial level of infant mortality World Bank data

*Taken from the Roodman (2004) dataset

47


Appendix A2: List of countriesAn economy is defined as low income, middle income (subdivided into lower middle and

upper middle), or high income on the basis of GNI per capita.. Economies are classified

according to 2007 GNI per capita, calculated using the World Bank Atlas Method. The groups

are: low income, $935 or less; lower middle income, $936 - $3,705; upper middle income,

$3,706 - $11,455, and high income $11,456 or more (World Bank). High income countries

are left out in this study.

Low-income economies (41)Bangladesh Haiti Papua New Guinea Benin Kenya Rwanda

Burkina Faso Lao PDR Senegal Burundi Liberia Sierra Leone

Central African Republic Madagascar Solomon Islands

Chad Malawi Somalia

Comoros Mali Tanzania

Congo, Dem. Rep Mauritania Togo

Côte d'Ivoire Mozambique Uganda

Ethiopia Myanmar Vietnam

Gambia, The Nepal Yemen, Rep. Ghana Niger Zambia

Guinea Nigeria Zimbabwe

Guinea-Bissau Pakistan

Lower-middle-income economies (40)Algeria Guatemala Paraguay Angola Guyana Peru

Bhutan Honduras Philippines

Bolivia India Samoa

Cameroon Indonesia Sri Lanka

Cape Verde Iran, Islamic Rep. Sudan

China Iraq Swaziland

Colombia Jordan Syrian Arab Republic

Congo, Rep. Lesotho Thailand

Djibouti Maldives Tonga

Dominican Republic Mongolia Tunisia

Ecuador Morocco Vanuatu Egypt, Arab Rep. Namibia El Salvador Nicaragua

48


Upper-middle-income economies (27)Argentina Grenada Seychelles Belize Jamaica South Africa

Botswana Lebanon St. Kitts and Nevis

Brazil Libya St. Lucia

Chile Malaysia St. Vincent and the Grenadines

Costa Rica Mauritius Suriname

Dominica Mexico Turkey

Fiji Panama Uruguay

Gabon Romania Venezuela, RB

49

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