The core determinants of health expenditure in the African context: Some econometric evidence for policy
Introduction
This paper identifies and empirically tests some of the major theoretical determinants of health care expenditure in a large sample of African countries using more recent cross-sectional data. The macroeconomic multiplier impacts of a well-targeted rise in health care spending are multi-dimensional. Since health care is a core component of human capital investment, rising national health care spending would tend to raise labor productivity, quality of life, and general welfare. Health care spending has also been credited for prolonging life expectancy, reducing morbidity, and reducing infant mortality rates (health outcomes). Thus, greater health spending is capable of reducing disease epidemics. Madison [1], Pritchett and Summers [2], and Weil [3] reported a positive association of health status with per-capita gross domestic product (GDP) growth, and health spending that enhances human capital is a potent catalyst for economic progress including through greater foreign direct investments of the multinational corporations [4], [5]. Consequently, health care expenditure study findings using data of the developing African countries would tend to carry broad implications for human development and multi-pronged economic growth policies.
The findings discussed above suggest that the benefits of a well-targeted rise in health care expenditure could especially be more important for the developing countries in Africa. Disease epidemics, including prevalence of tuberculosis and malaria, and location in tropics create major health problems that account for one of the factors driving anaemic productivity and high work absenteeism among school children and workers [6]. Per-capita health expenditure during 2001 was $29 in Sub-Saharan Africa and $4887 for the US. On average in 2001, the GDP percent devoted to health in Sub-Saharan Africa was 6% and almost 14% in the US. Furthermore, there is a high degree of variation in the health care per-capita expenditure in African countries. In designing policies to eradicate diseases and ensure adequate population health, policy makers in African countries, international aid agencies, and foreign investors can benefit from using information contained in reliable econometric estimates of the core determinant of health care spending.
An exhaustive literature search reveals that econometric studies of health spending of the developed countries (OECD, the EU, Canada, and the US) proliferate (see, e.g., Refs. [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]). There is, however a striking dearth of macro-data econometric models of health care spending using data of the African countries. Major studies that rely on data from the African setting include Okunade [18], Gbesemete and Gerdtham [19], Murthy [20], and Okunade [21]. The Gbesemete and Gerdtham [19] study, based on 1984 cross-sectional data of 30 Sub-Saharan and N. African countries, had limited observations and other econometric challenges. Murthy's [20] work is too brief, and the latest published work, Okunade [21], using 1995 cross-sectional data of 26 African countries, is also limited in the degrees of freedom for estimating the econometric model.
Controlling for demographic, epidemiological, socio-economic, and public health factors, the current study, using robust econometric methods and a cross-sectional sample of 44 African countries (or 83% of all the African countries) for the year 2001, empirically tests whether real per-capita GDP (PGDP) elasticity of real per-capita health expenditure (HEXP) implies that health care at the margin is a necessity or a luxury good. The paucity of panel data, typically arising from an insufficient number of years and countries and an inadequate time-series data length for any of the countries included in the sample, precluded data modeling using the panel unit root testing and cointegration techniques. Specifically, the core correlates of HEXP in this study include per-capita real GDP (PRGDP), per-capita foreign aid (FAID), physicians per thousand population (DOC), percent of population aged 65 years of age (AGE65), and maternal mortality rate (MMR). During 2001, official development assistance (ODA) per-capita as percent of GDP per-capita in the African countries was about 6.4%. FAID, representing resource inflows, supplements domestic incomes and originates from multilateral and bilateral sources, NGOs and Foundations [22, p. 283]. Therefore, FAID, irrelevant in the context of modeling the determinants of HEXP of the developed countries, augments the GDP resource base for health development in the African setting [21]. Moreover, DOC captures the supply of the gate-keeping medical personnel, AGE65 is the proxy for old-age population dependency, and MMR is a measure of population health status measure.1
The novel contributions of our research to the relevant literature are many. Foremost, and for the first time in this line of work, the specified model is subject to a set of alternative econometric estimators to test for robustness across methods. These estimators are the OLS, TSLS (two-stage least squares), and the robust LAE (least absolute error). Second, no past study estimated the TSLS and LAE, despite econometric rationale (e.g., in case of outliers) justifying their usage. Third, use of 2001 cross-sectional data comprising a panel of 44 African countries, the largest so far tested in the context of African health expenditure models, raises inferential confidence in the study findings. Fourth is introducing and testing the relevance of MMR as an indicator of population health status in this line of work. A fifth innovation of this paper is implementing an econometric methodology to derive individual country elasticity estimate of per-capita real health expenditure (HEXP) with respect to per-capita real income (PRGDP). Consequently, this paper makes several methodological advances, tests a rarely used theoretical determinant, and discusses policy implications for the African countries.
The balance of this paper proceeds as follows. Section 2 discusses the model, methodology and data. Section 3 focuses on the empirical econometric tests and findings, and Section 4 covers summary, conclusion, policy implications, and suggestions for future research.
Section snippets
The model, methodology and data
Gerdtham and Jonsson [13] and Okunade [21] confirm that econometric models of health care spending based on aggregate data are largely atheoretical. Therefore, drawing from received theories and past studies of the developed countries, and in light of the well-known paucity of panel (and more recent cross-sectional) data for the model variables of interest for the African setting, this paper uses 2001 annual cross-section data covering 83% (fairly large compared with past studies) of all the
Discussion of empirical results
Table 1 contains summary statistics of the basic data for this study. The regression coefficient estimates of model (1), using the OLS and robust LAE (least absolute error) estimators, are arrayed in Table 2. Since the sample data used in this analysis covers countries of different sizes, the risks for encountering heteroskedasticity and outliers rise. Consequently, the White heteroskedasticity-consistent standard errors are used in computing the t-values for statistical inference. The LAE is a
Summary, conclusion and implications
This paper, using a fairly more recent cross-sectional data set, has confirmed empirically that in African countries, the major determinants of real per-capita health care expenditure (HEXP) are real GDP per-capita (PRGDP) and real per-capita foreign aid (FAID). These two variables exert statistically significant and positive effects on health care expenditure. Health care is a necessity, rather than a luxury good, in the countries studied and the empirical results derived from various
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