Health Care Expenditure and GDP in African Countries: Evidence from Semiparametric Estimation with Panel Data

Hindawi Publishing Corporation e Scientific World Journal Volume 2014, Article ID 905747, 6 pages http://dx.doi.org/10.1155/2014/905747 Research Article Health Care Expenditure and GDP in African Countries: Evidence from Semiparametric Estimation with Panel Data Zhike Lv and Huiming Zhu School of Business Administration, Hunan University, Changsha 410082, China Correspondence should be addressed to Zhike Lv; Received 28 December 2013; Accepted 4 February 2014; Published 6 March 2014 Academic Editors: M. Saez and M. Tsionas Copyright © 2014 Z. Lv and H. Zhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A large body of literature studies on the relationship between health care expenditure (HCE) and GDP have been analyzed using data intensively from developed countries, but little is known for other regions. This paper considers a semiparametric panel data analysis for the study of the relationship between per capita HCE and per capita GDP for 42 African countries over the period 1995–2009. We found that infant mortality rate per 1,000 live births has a negative effect on per capita HCE, while the proportion of the population aged 65 is statistically insignificant in African countries. Furthermore, we found that the income elasticity is not constant but varies with income level, and health care is a necessity rather than a luxury for African countries. 1. Introduction It is important for policymakers to know the relationship between health care expenditure and income, knowing this relationship helps them to make wise judgments, plan health reforms, and allocate resources efficiently. It is generally believed that there is a strong and positive relationship between health care expenditure and income, which is well established in the literature. However, there is no consensus on whether the income elasticity of health expenditure is greater or less than 1, Baltagi and Moscone [1] and Santiago et al. [2] provide excellent overview of it. The income elasticity of health expenditure can be defined as the percentage change in health expenditures in response to a given percentage change in income. If the elasticity is less than one, health care will be classified as a “necessary” good; that is, health expenditures increase more slowly than income. While if the elasticity is greater than 1, then health care will be defined as “luxury” good. There is already a substantial literature on studying the link between HCE and GDP, but almost without exception, these studies have been limited to OECD countries or developed countries, and we will review this literature in the following section. As it can be seen, most of previous studies have been performed at OECD countries. Very little literature has been done for African countries, this maybe because of data availability. To the best of our knowledge, Gbesemete and Gerdtham [3] and Jaunky and Khadaroo [4] are the only two studies in the literature that examine this link in African countries. And this paper seeks to contribute to filling this gap by exploring panel data from 42 African countries during the period 1995–2009. Compared with previous studies, this study contributes to the literature in the following aspects. First, as we all know, most of early studies use parametric techniques that assume a functional form, like a linear one. In fact, this may be unavoidable to obtain the estimator inconsistent, if their true relationship is nonlinear [5–7]. Therefore, the adoption of a semiparametric partially linear panel data approach has the advantage that it does not impose a specific functional form on the relationship between HCE and GDP. Second, Crémieux et al. [8] find that lower health care expenditures is associated with significantly higher infant mortality rate, and Gupta et al. [9] show some evidences that health expenditure reduce childhood mortality. In addition, considering the fact that the infant mortality rate (IMR) is relatively higher in Africa than other regions, we consider this variable (IMR) in our model. Finally, we reconsider the relationship between income and health expenditure for countries at different levels of development. 2 The remainder of this paper is organized as follows. The next section reviews the literature. Section 3 presents the data description and econometric model. Section 4 discusses estimation results. Finally, Section 5 draws up policy recommendation and concludes the paper. 2. Literature Review In this section, we review the existing papers and their main result about the income elasticity of health care expenditure. Since the seminal paper by Newhouse [10], who observed that over 90 percent of the variation between countries in per capita health care expenditure could be explained by variations in per capita GDP, it has become popular to investigate whether the income elasticity of health care expenditure is more or less than 1. Throughout the existing research studies, Past researches in this field may be classified into three results, one found the elasticity was higher than 1 [11–14] and others believed that the elasticity was less than 1 [1, 4, 15–17], still others obtained a result that the elasticity was around one [2, 3, 18, 19]. The discrepancy of income elasticity in this literature could be attributed to a variety of reasons like using different econometric methods, different data, and explanatory variables. Early studies on this topic usually used a single crosssection data, Parkin et al. [20] found that the income elasticity was 0.90 using cross-section data for 18 OECD countries. While Gerdtham et al. [21] estimated an income elasticity of 1.33 using cross-section data for 19 OECD countries. Later on, some researchers doubt their results because using a single year’s cross-sectional data ignored the presence of unobservable country specific effects and also may exhibit other variables playing a key role to influence the result. To remedy these drawbacks, researchers have used panel data model or time series data model to analyze the relationship between HCE and GDP [18, 22, 23]; they also used a richer set of explanatory variables, such as the percentage of the population over the age 65, the percentage of the population under 15, and the proportion of HCE that is publicly funded [13, 24, 25]. But still they do not reach a consensus whether the income elasticity is larger than 1 or less than 1. More recently, much attention has been focused on the question whether health care and GDP are stationary or not. Hansen and King [22] studied the time series from each separately and found that one can only rarely reject the unit root hypothesis for either GDP or HCE. McCoskey and Selden [26] revisited the question of unit roots in the OECD data proposed by Hansen and King [22], and they rejected the presence (...truncated)