Foreign aid and human development: the impact of foreign aid to the health sector.

• Author: Williamson, Claudia R.

1. Introduction

   International aid is one of the most powerful weapons in the war against poverty. Today that weapon is underused and badly targeted. There is too little aid and too much of what is provided is weakly linked to human development. (United Nations Development Programme 2005, p. 75) According to the 2005 Human Development Report (United Nations Development Programme 2005), there is a general consensus that foreign aid's first objective should be human development. In 2000, governments from various countries met at the United Nations and signed the Millennium Declaration, a pledge "to free our fellow men, women and children from the abject and dehumanizing conditions of extreme poverty." One way of achieving these goals is through development assistance (United Nations Development Programme 2005). This advice has been widely accepted in the donor community during the past five years because total aid to the health sector has more than doubled. For example, as illustrated in Figure 1, from 1999 to 2004 aid to the health sector rose from $1930 to $4435 millions of 2004 dollars (OECD 2007).

   With growing intensity given to international human development aid, an analysis of its effectiveness is worthwhile. Both conceptual and empirical literature debates the effectiveness of foreign aid for economic development without a general consensus on the role of foreign assistance in economic development. Two contrasting hypotheses have emerged. One is a public interest argument where some authors state that aid can and should be used to assist in the development process (Sen 1999; Sachs 2005). The other is a public choice hypothesis that presents arguments indicating that foreign assistance is ineffective and has the potential to damage future growth opportunities (Bauer 2000; Easterly 2001).

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   These two competing hypotheses lead to different predictions on the use of foreign aid for human development. For a clear answer, one must turn to empirical analysis. Current empirical literature primarily supports the public choice perspective, indicating that foreign aid is ineffective in promoting economic development (Filmer and Pritchett 1999; Svensson 1999; Filmer, Hammer, and Pritchett 2000, 2002; Knack 2001; Brumm 2003; Brautigam and Knack 2004; Economides, Kalyvitis, and Philippopoulos 2004; Djankov, Montalvo, and Reynal-Querol 2005; Hartford and Klein 2005; and Heckelman and Knack 2005). In these studies, the authors focus on the impact of foreign aid on economic development and find no significant impact. However, in a recent study by Gomanee, Girma, and Morrissey (2005), the authors show that aid can improve human welfare through increases in certain public expenditures, supporting the public interest predictions. Their methodological approach neglects to control for endogeneity, and this could lead to biased results. Thus, further analysis is required.

   With the recent shift in the promotion of aid from economic to human development, it is timely to investigate the role of foreign aid for human development purposes. This paper provides the next step in the literature by establishing the link between foreign aid and human welfare. This is the first examination to utilize aid earmarked specifically to the health sector (health aid) to determine its effect on human development. Other studies have generally analyzed the impact overall foreign aid has had on human welfare, but none uses aid specifically to the health sector. To effectively perform this analysis, I build off the existing development literature and extend the same empirical methodology, including instrumental variable estimation to control for reverse causality. My results support the public choice perspective, indicating that international aid to the health sector is ineffective in improving human welfare. My findings are robust to different model specifications and a variety of health indicators. This suggests that foreign aid may not be an effective way of improving health in developing countries.

   The next section outlines the empirical model and data used in the analysis. A fixed effects model is the benchmark specification. The core analysis builds off of this basic specification by implementing an instrumental variable to control for possible reverse causality issues. A detailed discussion of the validity of the instruments is provided. Section 3 presents the results of the fixed effects model and the instrumental variable model. Section 4 presents three different robustness checks that confirm my results. Also, results are presented that strengthen the legitimacy of my instruments. Section 5 concludes.

2. Empirical Model and Data

   The first model presented is a fixed effects regression that is used as the baseline specification. Next, instrumental variable estimation is implemented as the core analysis. A detailed description of the data is also provided in this section, including defining all variables, listing the data sources, and providing the descriptive statistics.

   Benchmark Specification

   The strategy employed is a fixed effects model that controls for country and year effects with robust standard errors: (1)

   [Y.sub.i,t] = [mu] + [beta][AID.sub.i,t] + [Z'.sub.i,t][delta] + [[epsilon].sub.i,t],

   where Y = health indicators, AID = health aid, and Z = control vector. The main variable of interest is foreign aid to the health sector. Health aid over the past five years accounts for roughly 7% of all official development assistance granted. The data for this variable was taken from OECD's Credit Reporting System that gives detailed breakdowns of official development assistance and official aid in developing and transitioning countries by sector (in 2004 dollars). I collected foreign aid to the health sector for all countries that received this type of aid. Detailed flow analysis is only available from 1973 onward, so this has limited my data set for the period 1973 to 2004.

   Five main health indicators are used to capture the overall quality of health in a country. These include infant mortality, life expectancy, death rate, and immunizations (DPT and measles). These variables were collected from the 2006 World Development Indicators. The death rate is a crude measure that estimates the number of deaths occurring during the period. It is estimated per 1000 of the population at midyear. If aid is effective on human development, it should have a negative relationship with the death rate: As more aid flows to the health sector, the death rate should fall. Life expectancy at the time of birth, reported in years, is another variable we would expect effective health aid to affect, raising the expectancy of one's life. Immunizations (DPT and measles) are the percent of children 12-23 months that receive the vaccine before reaching one year of age. Health aid should increase this percentage, especially because immunizations are easier to administer than other health projects and specific programs have been established especially for this purpose. Infant mortality (per 1000 of births) is the number of infants dying before one year of age in a given year. This number should decrease as foreign aid flows to the health sector increase.

   A variety of control variables are included in the model: percentage urban population, number of physicians, gross domestic product (GDP), the Fraser freedom index, and a political freedom index (Freedom House Organization). Gross domestic product, percentage urban population, and the number of physicians were taken from the 2006 World Development Indicators. GDP per capita is based on purchasing power parity and is reported in constant 2000 international dollars. GDP represents the overall level of economic development and should exhibit a positive relationship with human development. The number of physicians (per 1000) is any graduate from a medical school or facility practicing medicine in the country. This should have a positive influence on health, while urban population may provide mixed results.

   To control for the institutional environment, I include the Fraser freedom index or the political freedom index in the regression. The Fraser freedom index captures the economic institutions, while the political freedom index controls for political rights and civil liberties. The Fraser freedom index is scaled from 1 to l0 with 10 representing the highest level of freedom. This index measures the degree to which a country allows personal choice over collective choice, voluntary exchange, the freedom to compete, and security of private property (Gwartney and Lawson 2005). The political freedom index is collected from Freedom House (2007) and is scaled from 1 to 7, with 1 representing the highest level of freedom. This index averages scores from an index on political rights and an index on civil liberties to calculate one comprehensive measure of political freedom. It has been shown that increases in economic and political freedom positively impact economic development (Gwartney, Lawson, and Holcombe 1999; Acemoglu, Johnson, and Robinson 2001, 2002). Thus, a country's institutional environment may influence human development as well and should be included in the analysis.

   Because of the importance of controlling for the quality of institutions and the level of income, several different regression specifications are necessary. It is well documented that GDP is highly correlated with institutional indices and is usually not included in the same regression. (2) In my sample, GDP has a correlation of 0.62 with both the Fraser freedom index and with the political freedom index. Including both GDP and either one of the freedom indices may cause inaccurate results; however, it is crucially important that both growth and institutional quality be accounted for in the model specification. Therefore, I estimate my model with five different regression specifications: (1) GDP only, (2) Fraser freedom index...