CDI-2014-03-001

Official Development Assistance and Foreign Direct Investment:

How Are They Affecting Economic Growth? 1

CDI-2014-03-001

Official Development Assistance and Foreign

Direct Investment: How Are They Affecting

Economic Growth?

Jinhwan Oh

Assistant Professor

Graduate School of International Studies

Ewha Woman’s University

Nara Lee

Graduate School of International Studies

Ewha Woman’s University

May16, 2014




How Are They Affecting Economic Growth?

Jinhwan Oh

May 16, 2014

Abstract

Both Official Development Assistance and Foreign Direct Investment have been thought ofasimportant sources of foreign capital inflow,which could help economic growth for many developing countries. Hence, the current studyinvestigates the role of ODA and FDI in promoting economic growth in developing countries by using a panel data of 166 developing countries from 1980 to 2011. We empirically show that ODA and FDI have positive impacts on economic growth, butbecome negative when interacted. Our result demonstrates the possibility that ODA and FDI are substitutes for each other in promoting growth.



1.Introduction

Both Official Development Assistance (ODA) and Foreign Direct Investment

(FDI) have been considered as important sources of foreign capital inflow, which could

helpeconomic growth for many developing countries.Based on this factor, the

international community has madeefforts into raisingthe capital flowof ODA and FDI

from developed countries to developing countries. ODA has been disbursed in various

sectors for the purpose of promoting theeconomic and social development of

developing countries, particularly insocial and economic infrastructure and servicesas

well as in manufacturing sectors. On the other hand, FDI usuallycomes from private

sectors, such as multinational corporations,in order to provide technology and capital to

a host country. Moreover, FDI reportedly works asa catalyst fortheeconomic growth of a

host country with the help of technology spillovers and capital. The sectors where FDI is

distributed are plant and equipment, and infrastructures; especially, there are growing

needs of infrastructure investment in developing countries, as emphasized in Funget

al.(2011).

Having the general information ofODA and FDI, there have been questions

regarding theireffectiveness; do ODA and FDI really work? In order to answer these

questions, a large number of studies have been trying to examine as to whether ODA

and FDI have positive impacts on economic growth, and in what condition they are

effective.Svensson(1999) found that aid is positively working for democratic recipients,

where political and civil liberties are guaranteed.Burnside and Dollar (2000) revealed that

aid is effective only whenthe recipients have sound fiscal, monetary, and trade

policies;Borensztein, De Gregori, and Lee (1998) found that FDI has positive impacts on

economic growth only when the host country has a sufficient capability to absorb the

advanced technologies. Blomstrom, Lipsey, and Zejan (1994) showed that depending on

the income levels of developing countries, the impact of FDI varies; FDI has a positive

impact on growth for higher income developing countries, but not for lower income



ones. Kosack and Tobin (2006) discoveredthatODA and FDI have a conditional

relationship with economic growth and human development;FDI has no impact on

economic growth, and could have anegative impact on human development in countries

with low levels of human capital. Furthermore, for the impact of aid whena high level of

human capital is guaranteed, aid is highly effective in achieving higher growth and human

development while it works against development in countries without ahigh level of

human capital.

The purpose of this paper is to investigate the impact of ODA and FDI on

economic growth along with their interactivity.In spite of a number of theabove-

mentioned studies,this studyisstill worth investigating because a very few of them have

used both theODA and FDI simultaneously by making their interaction term at an

international context1. This approach will allow us to examine the impact of ODA onthe

economic growth of recipient countries, where FDI is associated, and vice versa, which

could ultimately engender insights on aid effectiveness and investment effectiveness.

Malik(2013) also used this approach; however, the dependent variable in his study is

trade, which is different from the one used here.

This study is organized as follows:the next section introducestheresearch design

and data, followed bya provision of themain results regarding the empirical analysis.The

last section concludes the study.

1. Research Design and Data

In order to analyze the role of ODA and FDI on economic growth in developing

countries as well as to examine how ODA and FDIinteract with each other, we employ a

panel data of 166 developing countries for a period from 1980to 2011. The ODA data of

the dataset is obtained from OECD Statistics; allother data are from theWorld Bank’s

World Development Indicators (WDI). All data used in this study is in constant U.S.

dollars. The regression model is as follows:

Growthit = 0 + 1ODAit-1 + 2FDIit-1 + 3ODAit-1*FDIit-1 +4lnPGDPit + 5Opennessit +

6Inflationit + 7Popgrowthit + 8Region + it (1)

1Wang and Balasubramanyam (2011) used this interaction term, but only for a single country’s case.



where Growth is theGDP growth rate, which works as a dependent variable; ODA

istheratio of ODA to GDP; FDI isthe ratio of FDI to GDP;ODA*FDI is the interaction

term of the ratio of ODA to GDP and the ratio of FDI to GDP. One year lagged

variablesare used in orderto reducethe issue of endogeneity. Next, in order to control the

other factors that may affect a country’s growth, thelog of per capita GDP

(lnPGDP),Trade openness 2 ,inflation rate (Inflation),and Population growth (Popgrowth) are

used. Lastly, aregion dummy3 is used to check forany region-specific differences.

This study usesthe fixed effect for the first model withouta dummy based on the

result obtained from the Hausman Test(See Appendix 2), and the random effect for the

second model witha dummy.

ODA and FDI are known to have a positive impact onthe economic growth of

recipient countries; hence, the coefficients of each variable are expected to be positive.

The coefficient of the interaction term would be positive if ODA and FDI are

complements to each other; ODA works better in a country that hasan abundant volume

of FDI, and vice versa. Malik (2013) revealedthis notionwhen thetrade data was used as a

dependent variable. On the other hand, this variable is expected to be negative if ODA

and FDI are substitutes to each other,implyingthat they are disbursed in similar sectors;

moreover, each one will contribute more tothe growth of the developing countrywhen

the other is scarce.

3. Results

Table1 about Here

2Trade openness=

Export +Import

GDP

3 Europe, North Africa, Sub-Saharan Africa, Middle East & North America, South America, East Asia,

South & Central Asia, Middle East and Oceania (See Appendix 1 for country classification)



As shown in Table 1, both ODA and FDI are positively associated with the

growth rate of the recipient countries; thecoefficients of these two variables are

significantly positive in both models, which is consistent with our expectation.

However, the coefficients of their interaction terms of ODA and FDI are

significantly negative in both models. The fact, that the individually positive effect turns

out to be negative when combined with the other one,suggests that the impact of ODA

on a country’s growth depends on the amount of FDI, and vice versa. In order to further

investigate thisimportant finding, the current study adopts Malik’s (2013) approach,

which differentiatesadependent variable with respect to an explanatory variable. First,

partial differentiation of Equation (1) with respect to ODA produces the following

equation with thecorresponding figure.

𝜕𝐺𝑟𝑜𝑤𝑡 ℎ

𝜕𝑂𝐷𝐴= 𝛽1 + 𝛽3𝐹𝐷𝐼(2)

where 1 is positive and 3is negative. A visual illustration between FDI and the

derivative of growth is provided in the left-hand side of Figure 1. Note that the vertical

axis measures the changing rate of growth as ODA increases by one unit,whereasthe

horizontal axis, which measures the amount of FDI, is given to developing countries.

The diminishing marginal growth in terms of ODA, which is expressed asa downward

sloping linear relationship between the two, indicates that the growth rate continues to

rise as ODA increases, but only whenFDIis at a relatively low level. This means that

ODA is more effective in the growth of a recipient country only when it has a

smalleramount of FDIin it. More specifically, providing too much ODA to a country

thatalready has anabundant volume of FDI negatively affects its growth.

A partial differentiation of Equation (2) with respect to FDI produces a similar

equation to Equation (2)a long with a similar figure.

𝜕𝐺𝑟𝑜𝑤𝑡 ℎ

𝜕𝐹𝐷𝐼= 𝛽2 + 𝛽3𝑂𝐷𝐴 (3)

Figure 1 about Here

where 2 is positive and 3 is negative, which is the same as the above case. As a

result, thegraphical explanation is identical to both graphs in Figure 1.



This finding suggests the possibility that ODA and FDI may be a substitute to

each other. As aforementioned, there are casesin which ODA and FDI are disbursed to

similar sectors, such as a large size of infrastructure building, transport,

telecommunication and water. (For the disbursement of FDI to cross-border

infrastructures, See Fung, Garcia-Herrero, and Ng(2011))Given this interpretation, their

effectiveness may diminish when they are duplicated to overlapping.

The result in this study is quite different from Kosack and Tobin’s finding. In

Kosack and Tobin’s study, ODA has apositive impact and FDI has anegative impact on

growth, whereas ODA and FDI havea positive impact on growth in this study. This

difference may come from the different data coverage-Kosack and Tobin used thedata of

103 countries from 1970 to 1999 and here, we used theannual data of 166 countries from

1980 to 2011. Furthermore, the control variables used in each study are different.

This finding is in line with Acharya (2006) and Oh and Kim’s (2013), in the sense

that too much could be worse than too little. Having focused on aid fragmentation, these

studies found that having too much aid agencies in a recipient country reduces theaid

effectiveness due to the transaction costs among donors and/or aid projects. Assuming

that FDI is similar to ODA, in that they help in thedevelopment of developing countries

by being disbursed in various infrastructures, over-flowing ODA and FDI may

eventually negatively affect a country’s growth. This would be consistent with the main

finding of Oh and Kim (2013), in particular, in which a growing amount of aid may

benefit a country’s growth initially; yet, too much fragmentation eventuallynegatively

affects when diseconomies of scale outweighs theincreasing returns to scale from

learning-by-aiding.

Additionally, ananalysis witha region dummy is provided. The second column in

Table 1 finds that thecoefficients of South and Central Asia and East Asia are positive

while that of Oceania is negative4 . For a given level of other explanatory variables,

thegrowth rate is the highest in South and Central Asia, followed by East Asia, Europe,

and then the regions with negative signs. It seems that ODA and FDI are effectively

contributing in North and Central Asia as well as in the South Asian region compared to

others.

4 The result of Europe drops due to multi-collinearity; the coefficients of North Africa, Sub-Saharan

Africa, North and Central America, South America, and the Middle East are not significant.



Lastly,the results for thecontrol variables are all as expected. The growth rate

increases as a country’s degree of openness and population growth increases. Inflation

has a negative impact, as usual. The positive coefficients for per capita GDP look

unintuitive, as higher income nations had already arrived at steady states of growth in

which their economies slow down. However, given that the country sample in this study

is only for developing countries, it would not be too surprising to find that higher

income developing countries achieve ahigher levelof growth.

4. Conclusion

In this study, it is proved that both ODA and FDI positively affect the economic

growth ofdeveloping countries. On the other hand, when ODA and FDI are associated,

ODA has apositive impact only when FDI is disbursed below the maximum level, and

vice versa. This result implies that there is apossibility that ODA and FDI play

asubstitute role to each other in promoting economic growth in developing countries.

Given the negative coefficients for theinteraction term, it would be desirable if

funding agencies could provide FDI where ODA is scarce, and vice versa. Given their

characteristics, it would be better if FDI could be provided to higher income developing

countries that are already equipped withthe basic social infrastructure and therefore,

receiving asmaller amount of aid. Those countries would be ready to absorb the benefits

of investment from foreign countries that would havean immediate impact on their

growth. On the other hand, aid donors could consider disbursing ODA to lower income

countries, where basic social needs are yet met, before investing capital from FDI. Also,

from therecipients’ perspectives, they need to have a policy that regulate ODA and FDI

rather than try to attract ODA and FDI blindly.

As a further research topic, a sectoral analysis of ODA and FDI could be

considered to have more insight on their reciprocal effectiveness. Incorporating with

more factors, such as human capital and democracy, as was used by Kosack and Tobin

(2006), can also be an asset, which will be reserved for further study. Lastly, the impact

of the interaction term of ODA and FDI on poverty reduction and human development

could be investigated.



References

Acharya, A., De Lima, A. T. F., & Moore, M. (2006). Proliferation and fragmentation:

Transactions costs and the value of aid. The Journal of Development Studies, 42(1), 1-21.

Blomstrom, M., Lipsey, R. E., & Zejan, M. (1994). What explains developing country growth?

(No. w4132). National bureau of economic research.

Borensztein, E., De Gregorio, J., & Lee, J. W. (1998). How does foreign direct investment

affect economic growth?. Journal of international Economics, 45(1), 115-135.

Burnside, C., & Dollar, D. (2000). Aid, policies, and growth. American economic review,

847-868.

Burnside, A. C., & Dollar, D. (2004). Aid, policies, and growth: revisiting the evidence.

World Bank Policy Research Paper.

Fung, K. C., Garcia-Herrero, A., & Ng, F. (2011). Foreign direct investment in cross-border

infrastructure projects.

Kosack, S., & Tobin, J. (2006). Funding self-sustaining development: The role of aid, FDI

and government in economic success. International Organization,60(1), 205.

Malik, H. (2013). Foreign Aid, Foreign Direct Investment, and International Trade: Some

International Evidence.

Moreira, S. (2003). Evaluating the impact of foreign aid on economic growth: A cross-

country study (1970-1998)."15th Annual Meeting on Socio-Economics.

Oh, J.,& Kim, Y. (2014).Proliferation and Fragmentation: Uphill Struggle of Aid

Effectiveness. CDI Working Papers.

Svensson, J. (1999). Aid, growth and democracy. Economics & politics, 11(3), 275-297.



10

Wang, C., & Balasubramanyam, V. N. (2011). Aid and Foreign Direct Investment in

Vietnam. Journal of Economic Integration, 26(4), 721-739.

Table 1. Regression Results for Growth Rate

(1) (2)

Lag of ODA/GDP 10.420*** 8.890***

(1.707) (1.707)

Lag of FDI/GDP 12.632*** 15.011**

(2.340) (6.890)

Lag of (ODA/GDP)*(FDI/GDP) -26.305*** -30.767**

(5.249) (13.056)

Log of per capita GDP 2.148*** 0.534**

(0.413) (0.237)

Openness 1.179*** 0.939***

(0.359) (0.335)

Inflation -0.001*** -0.001***

(0.000) (0.000)

Popgrowth 0.476*** 0.387**

(0.126) (0.172)

North Africa 0.516

(0.637)

Sub-Saharan Africa 0.158

(0.768)

North & Central America -0.726

(0.535)

South America -0.421

(0.576)

East Asia 1.911**

(0.864)

South & Central Asia 2.979***



11

(0.705)

Middle East -0.074

(0.665)

Oceania -1.283**

(0.609)

_cons -14.332*** -2.435

(3.018) (2.262)

Note: (1) White robust standard errors are represented in parenthesis to handle heteroskedasticity.

(2) ***, ** and * indicate statistical significance at the 1, 5 and 10 percent level

Figure 1. The impact of ODA and FDI on Growth

𝜕𝐺𝑟𝑜𝑤𝑡ℎ

𝜕𝑂𝐷𝐴

FDI

𝜕𝐺𝑟𝑜𝑤𝑡ℎ

𝜕𝐹𝐷𝐼

ODA 0 0



12

Appendix 1.Country Classification by Region

Region 1

Europe

Region 2

North Africa

Region 3

Sub-Saharan Africa

Region 4

Middle East

&North America

Albania Algeria Angola Malawi Antigua and

Barbuda

Belarus Egypt Benin Mali Aruba

Bosnia-

Herzegovina Libya Botswana Mauritania Bahamas

Croatia Morocco Burkina Faso Mauritius Barbados

Cyprus Tunisia Burundi Mozambique Belize

Kosovo

Cameroon Namibia Bermuda

Macedonia, FYR

Cape Verde Niger Cayman Islands

Malta

Central African

Rep. Nigeria Costa Rica

Moldova

Chad Rwanda Cuba

Montenegro

Comoros Sao Tome &

Principe Dominica

Serbia

Congo, Dem. Rep. Senegal Dominican

Republic

Slovenia

Congo, Rep. Seychelles El Salvador

Turkey

Cote d'Ivoire Sierra Leone Grenada

Ukraine

Djibouti Somalia Guatemala

Equatorial Guinea South Africa Haiti

Eritrea South Sudan Honduras

Ethiopia Sudan Jamaica

Gabon Swaziland Mexico

Gambia Tanzania Nicaragua

Ghana Togo Panama

Guinea Uganda St. Kitts-Nevis

Guinea-Bissau Zambia St. Lucia

Kenya Zimbabwe

St.Vincent &

Grenadines

Lesotho

Trinidad and

Tobago

Liberia

Turks and Caicos

Islands

Madagascar

Virgin Islands (UK)

Region 5

South America

Region 6

East Asia

Region 7

South & Central

Asia

Region 8

Middle East

Region 9

Oceania



13

Argentina Brunei Afghanistan Bahrain Fiji

Bolivia Cambodia Armenia Iran French Polynesia

Brazil China Azerbaijan Iraq Kiribati

Chile Hong Kong, China Bangladesh Israel Marshall Islands

Colombia Indonesia Bhutan Jordan New Caledonia

Ecuador Korea Georgia Kuwait Northern Marianas

Guyana Korea, Dem. Rep. India Lebanon Palau

Paraguay Laos Kazakhstan Oman Papua New Guinea

Peru Macao Kyrgyz Republic Qatar Samoa

Suriname Malaysia Maldives Saudi Arabia Solomon Islands

Uruguay Mongolia Myanmar Syria Tonga

Venezuela Philippines Nepal United Arab

Emirates Tuvalu

Singapore Pakistan

West Bank & Gaza

Strip Vanuatu

Thailand Sri Lanka Yemen

Timor-Leste Tajikistan

Vietnam Turkmenistan

Uzbekistan

Source: World Bank

Appendix 2. Results for the Hausman Test

Coefficients with

fixed effects (1)

Coefficients with

random effects (2)

Difference

(1)-(2) S.E.

L.ODA 10.41967 8.040785 2.378884 1.004629

L.FDI 12.6315 14.95752 -2.32602 1.134633

L.ODA*FDI -26.30473 -30.26631 3.961581 2.152979

lnPGDP 2.148141 0.3059328 1.842208 0.3902057

Openness 1.17873 1.301948 -0.1232184 0.2641452

Inflation -0.0006062 -0.0006801 0.0000739 0.0000184

Popgrowth 0.4764623 0.3324859 0.1439764 0.0740866

Note: X2=32.06, prob>X

2=0.0000

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CDI-2014-03-001