research paper

The Effects of Foreign Direct Investment and Foreign Aid on Gross Domestic Product in Developing Countries: A Case for the Democratic Republic of the Congo

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Author Note

Mathew A. Schulz, Department of Economics, Salem State University.

Mathew A. Schulz will be attending Boston University for his master’s degree in city planning, focusing on development and public policy. Correspondence concerning this article should be addressed to [email protected].

Abstract

Prompting this analysis was the International Monetary Fund’s 2010 report of gross domestic product purchase power parity per capita, where the Democratic Republic of the Congo (D.R. Congo) ranked last, at a meager $328 (U.S.) annually. With the recent debates concerning whether or not sub-Saharan African countries have benefited from capital inflows, this paper explores the effects of foreign direct investment and foreign aid on the D.R. Congo’s gross domestic product. In the D.R. Congo, empirical evidence suggests that a slight positive correlation exists between capital inflows and gross domestic product. However, due to the volatility of foreign direct investment and aid, comprehensive policies promoting economic and political stability should be examined.

The Effects of Foreign Direct Investment and Foreign Aid On Gross Domestic Product in Developing Countries: A Case for the Democratic Republic of the Congo

The history of the effectiveness of capital inflows to Africa has raised much debate as to whether or not any contributions have increased development. The literature overviews of the area, particularly in regards to sub-Saharan Africa (SSA), have identified many determinant variables of growth. Highlighting several forms such as foreign direct investment (FDI), official development assistance (ODA), domestic savings, improved infrastructure, debt relief, and reinvestment, among others, many economists conclude that the first two are most important for increasing economic growth. It is FDI and foreign aid (AID), both external sources, which benefit economic expansion in less developed countries (LDCs). This phenomenon, despite not always being true, has gained recent momentum. According to Collier and Gunning (1999) their study for the period between 1960-1989 found one explanatory variable, investment to GDP ratio, statistically significant in explaining growth in Africa. They concluded that African countries with higher investment to GDP ratios had higher economic growth rates. Another study, Loots (2003) found similar results. The study, covering the period from 1995-2000, found that per-capita growth during the period was directly related to external capital inflows. In particular, Loots (2003) noted that FDI and ODA flows were important in understanding the growth of African countries in the mid to late 90s.

The objective of this paper is to further explore the explanatory power of capital flows to developing countries. In particular, it will cover the two decades on either side of the centuries turn, from 1990-2009. Instead of looking at several SSA countries it will focus specifically on the Democratic Republic of the Congo (D.R. Congo). Why? Because in the International Monetary Fund’s 2010 list of countries GDP purchase power parity per capita, it ranked 183rd, or more notably, last. For this reason, if any developmental growth from external capital flows can explain and ultimately increase the D.R. Congo’s meager $328 (U.S.) per capita, then it should be beneficially important to understand. Furthermore, closer examination of the empirical evidence will assist in determining whether or not any exogenous variables are determinants in explaining the D.R. Congo’s growth. In other words, are there underlying foundations of FDI and AID that can help enhance and support economic development for the country?

The format this paper will take is as follows: (1) a methodology section that previews the data with a research design that explains the two regression models, (2) an analysis section that details the data of the two models and accompanying graphs, noting any inconsistencies and potential for further research, and (3) a discussion section that summarizes the findings and identifies possible policy initiatives.

Methodology

In order to understand if a correlation exists among capital flows to the D.R. Congo, in particular, an increase in gross domestic product as measured against foreign direct investment and foreign aid, several analyses were completed. Using 1990-2009 time-series data from the World Bank and United Nations Conference on Trade and Development, regression analyses utilizing the ordinary least squares (OLS) method, were run to explain the relationship among variables.

Data

Table 1 displays the data used within the regressions.

Table 1: Democratic Republic of the Congo: GDP, Foreign Aid, and FDI; 1990-2009
Year	Gross Domestic Product	Foreign Aid	Direct Investment
1990	$9,349,764,580	$895,790,000	-$14,460,000
1991	$9,087,965,282	$475,280,000	$12,390,000
1992	$8,206,227,134	$268,520,000	-$730,000
1993	$10,707,792,340	$177,820,000	$6,870,000
1994	$5,820,383,306	$244,810,000	$1,500,000
1995	$5,643,439,262	$194,750,000	-$22,350,000
1996	$5,771,454,884	$166,110,000	$24,790,000
1997	$6,090,840,527	$157,610,000	-$44,350,000
1998	$6,217,806,275	$125,460,000	$61,330,000
1999	$4,711,272,704	$132,380,000	$11,160,000
2000	$4,305,797,176	$177,120,000	$72,000,000
2001	$4,691,816,707	$245,310,000	$80,300,000
2002	$5,547,714,815	$1,174,950,000	$141,100,000
2003	$5,673,197,494	$5,416,900,000	$391,300,000
2004	$6,569,986,940	$1,918,810,000	$409,000,000
2005	$7,103,539,717	$1,881,450,000	$0
2006	$8,543,323,220	$2,197,070,000	$256,100,000
2007	$9,977,079,383	$1,356,380,000	$1,808,000,000
2008	$11,668,379,642	$1,768,520,000	$1,726,800,000
2009	$11,204,139,345	$2,353,560,000	$663,800,000
NOTE: Data courteous of the World Bank and the United Nations Conference on Trade and Development.

Research Design

To begin, the first regression evaluated the 1990-2009 annual gross domestic product (GDP) with annual foreign direct investment (FDI). The following model was created to explain the variation between those two variables:

Y = β0 + β1 X1 + u

GDP = β0 + β1 (FDI) + u

where Y is the dependent variable, annual gross domestic product; β0 is the intercept of the regression line; β1 is the slope of the regression line; X1 is the independent variable, annual foreign direct investment; and u is the error term, or deviation from the average.

The second, regression evaluated the 1990-2009 annual gross domestic product (GDP) with annual foreign aid. The following model was created to explain the variation between those two variables:

Y = β0 + β1 X1 + u

GDP = β0 + β1 (AID) + u

where Y is the dependent variable, annual gross domestic product; β0 is the intercept of the regression line; β1 is the slope of the regression line; X1 is the independent variable, annual foreign aid; and u is the error term, or deviation from the average.

Analysis

The two regressions address the hypothesis that the Democratic Republic of Congo’s gross domestic product will rise as capital inflows increase. Increases in capital flows will be defined by the dependent variable. That is, the first regression measures any increases from foreign direct investment and, the second, any increases from foreign aid. Following the models, further explanation of the correlation between capital inflows and gross domestic product will be generated through two graphs. The first graph outlines GDP with FDI and the second graph GDP with AID.

Regression I:

SUMMARY OUTPUT (FDI)
Regression Statistics
Multiple R	0.56457136
R Square	0.31874082
Adj R Sqr	0.280893088
Std Error	1959904146
Observations	20
ANOVA
	df	Sig F
Regression	1	0.009504043
Residual	18
Total	19
	Coefficients	Std Error	t Stat	P-value
Intercept	6670880562	495940571.3	13.45096761	7.86886E-11
FDI	2.412783393	0.831418	2.90201005	0.009504043

The summary output for the first regression produced the following model:

GDP = $6.671 billion + $2.417 million (FDI)

The model rejects the null hypothesis, Ho: β1 = 0, accepting .01 error, or at a confidence level of 99%, thus showing that FDI matters in explaining GDP. The D.R. Congo can expect to have a GDP of $6.671 billion with zero FDI. Each time FDI increases by one unit, $1 million in this instance, they can expect an increase in GDP by $2.417 million. The model’s goodness of fit, the R-square, tells us that 32% of the variation in GDP is explained by FDI. Furthermore, the p-value for coefficient X1, FDI, is .0095, which tests the statistical significance of the term, indicating that it is highly significant.

Regression II:

SUMMARY OUTPUT (AID)
Regression Statistics
Multiple R	0.183393923
R Square	0.033633331
Adj R Sqr	-0.02005370
Std Error	2334262103
Observations	20
ANOVA
	df	Sig F
Regression	1	0.43895921
Residual	18
Total	19
	Coefficients	Std Error	t Stat	P-value
Intercept	6995968728	682970126.3	10.24344764	6.1600E-09
AID	0.326910635	0.413027364	0.791498732	0.43895921

The summary output for the second regression produced the following model:

GDP = $6.996 billion + $326,910 (AID)

The model rejects the null hypothesis, Ho: β1 = 0, accepting .44 error, albeit at a lower confidence level, still showing that AID matters in explaining GDP. The D.R. Congo can expect to have a GDP of $6.996 billion with zero AID. Each time AID increases by one unit, $1 million in this instance, they can expect an increase in GDP by $326,910. The model’s goodness of fit, the R-square, tells us that only 3.4% of the variation in GDP is explained by AID. Furthermore, the p-value for coefficient X1, AID, is .4390, which tests the statistical significance of the term, indicating that it may not be significant.

Graph I:

Charting GDP with FDI produced the outcome above. Looking at the graph, the D.R. Congo’s GDP appears to have fluctuated over the two decades, dipping as low as nearly $4 billion at the turn of the century and reaching its peak of almost $12 billion in 2008. Following a U-shaped curve, GDP for the D.R. Congo decreased consistently in the 90s while increasing in the 00s. FDI, on the other hand, follows a much more linear, horizontally stagnate line, only showing a slight uptick in 2006 and decreasing two years later. Moreover, FDI throughout the 90s, specifically in 1990, 1995, and 1997, respectively, was negative.

Graph II:

Charting GDP with AID produced the outcome above, where GDP stayed consistent with Graph I. AID, however, while never negative over the 20-year period, did stay relatively linear throughout the 90s. At the turn of the century a sharp increase in foreign aid, roughly $5.5 billion can be seen. Despite decreasing rather quickly it remains consistent for the rest of the 00s, hovering near $2 billion.

Results

Although these analyses show positive correlations they do not prove causation. Simple regression analysis does not consider the several variables that influence GDP. In addition to the common four components of GDP: consumption, investment, government spending, and net exports, some omitted variables for future research should be considered. For instance, as mentioned in the introduction, variables such as domestic savings, improved infrastructure, debt relief, and reinvestment should be considered. Multiple regressions utilizing these additional variables may prove more beneficial as they might create a clearer understanding of important relationships between GDP and capital inflows.

Outliers, another source of data discrimination, are another concern. Despite having run both regressions with outliers, a judgment call, I felt that removing them from the analysis would distort a significant piece of data. That is, any capital inflows from a previous year, regardless of size, can have a significant impact on GDP; both in its ability to boost an economies growth rate within an individual year as well as the compounding results of investment on following years.

Discussion

Do capital inflows, specifically foreign direct investment and foreign aid, to the Democratic Republic of the Congo affect gross domestic product? Clearly, in the two decades between 1999-2009, there appears to be at least some positive correlation. GDP in the D.R. Congo certainly seems to follow a similar trend in direction to that of incoming capital inflows to the country. In other words, while FDI and AID in the 90s stayed relatively flat, showing minimal inflow even negative at times, GDP decreased. On the other hand, beginning near the turn of the century when FDI and AID increased, so did the D.R. Congo’s GDP. Trending together, GDP to FDI and AID lends one to believe that capital inflows do matter.

These trends, however, do appear to have inconsistencies. In particular, is the volatility in FDI and AID. Over the two-decade period, FDI had large swings ranging from three years of negative flow, negative $44 million at its lowest, to a high of nearly $1.8 billion. AID, while never negative, swung from a low of $125 million to a high of $5.5 billion. Volatility of that magnitude makes growth very difficult to sustain, especially when FDI, the more explanatory of the two variables, inconsistently fluctuates.

Because of this, foundationally, more must be understood in order to create sustainable growth for the D.R. Congo. Policy initiatives that support continued FDI and AID inflows must be set in place. In order to minimize the capital inflow volatility towards the country, the D.R. Congo needs to reduce the risk associated with investing. By reducing political setbacks caused by rebellious militants, eliminating fraudulent officials, implementing trade liberalization policies, and reinforcing safe and profitable returns for investors, the D.R. Congo can begin to realize sustainable economic growth.

References

Collier, P., & Gunning, J. W. (1999). Explaining African Economic Performance. Journal of Economic Literature, 37(1), 64-111.

Collier, P., & Gunning, J. W. (1999). Why Has Africa Grown Slowly? Journal of

Economic Perspectives, 13(3), 3-22.

Loots, E. (2003). Nepad: An Economic Exploration of the African Peer Review

Mechanism. The Economic Society of South Africa: Paper Presented at the

Conference of the Economic of South Africa, Conference September 2003.

Retrieved from http://www.essa.org.za/download/papers2003.htm.

Todaro, M. P., & Smith, S. C. (2009). Economic Development. Boston, MA: Pearson Education, Inc.

United Nations Conference on Trade and Development. (2010). Inward and Outward Foreign Direct Investment Flows, Annual, 1970-2010 [Data file]. Retrieved from http://unctadstat.unctad.org/TableViewer/tableView.aspx?ReportId=88

The World Bank. (2010). Net Official Development Assistance and Official Aid Received [Data file]. Retrieved from

http://data.worldbank.org/indicator/DT.ODA.ALLD.CD?display=default

�nice

�I have enjoyed reading your minim research paper, which is thoroughly done in an organized format. Usually empirical analysis is not visible within this short time span without conducting extensive survey, which also need IRB approval. But you were able to get away with it by collecting relevant data from a secondary source as a public information. Very nice job!

�Is this your introduction? Need to indicate that. Any research paper must start with introduction with statement of objectives and literature review in a separate section or chapter plus methodology analysis (qualitative or quantitative) and sources of data. These are the steps to take before you do the analysis.

�good approach!

�the format of …..?

�very good!

�excellent point!

�the scope for multiple regression analysis may be limited by this paper.

�I suppose this is your conclusion. If so, need a separate sub-title of your discussion section. But analysis followed by discussion was excellent.