Elsevier

Journal of Econometrics

Volume 112, Issue 1, January 2003, Pages 207-223
Journal of Econometrics

On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam

https://doi.org/10.1016/S0304-4076(02)00161-6Get rights and content

Abstract

Inequalities across the income distribution in a variable y can be decomposed into their causes, and changes in inequality in y can be decomposed into the effects of changes in the means and inequalities in the determinants of y, and changes in the effects of the determinants of y. Inequalities in height-for-age in Vietnam in 1993 and 1998 are largely accounted for by inequalities in consumption and in unobserved commune-level influences. Rising inequalities are largely accounted for by increases in average consumption and its protective effect, and rising inequality and general improvements at the commune level.

Introduction

The large inequalities that exist in the health sector—between the poor and better-off—continue to be a cause for concern, in both the industrialized and the developing worlds. These inequalities are manifest in health outcomes (see, e.g. Van Doorslaer et al., 1997; Gwatkin et al., 2000; Wagstaff, 2000), the utilization of health services (see, e.g. Gwatkin et al., 2000), and in the benefits received from public expenditures on health services (see, e.g. Castro-Leal 1999, Castro-Leal 2000; Sahn and Younger, 2000).

In this paper, we present and apply some decomposition methods relevant to addressing three types of question. The first concerns the causes of health sector inequalities at a point in time. These inequalities stem from inequalities in the determinants of the variable of interest. For example, inequality in health sector subsidies presumably reflects inequalities in determinants of health service utilization (e.g., the quality of local health facilities, access to them, opportunity costs, etc.) and inequalities in the per unit subsidy (e.g. because of inequalities in liability for user fees). The issue arises: what is the relative contribution of each of these various inequalities in explaining subsidy inequalities? The second type of question concerns differences and changes in health sector inequalities. Countries vary substantially in the degree of inequality in different health sector outcomes (see, e.g. Gwatkin et al., 2000), and there is evidence that these inequalities have changed over time (see, e.g. Schalick et al., 2000; Victora et al., 2000). The obvious question is why these differences exist and why these changes have occurred. The third type of question in which we are interested concerns the impacts of policies and programs. The fact that inequalities appear to have widened over time in some countries does not mean necessarily that policies have been ineffective, let alone that they have caused the growth of inequality. The decomposition we present below can be useful in situations like this where one wants to separate out the effects on inequality of various changes, including the effects associated with programs that—inadvertently or otherwise—have effects on health sector inequalities.

In addition to presenting methods for unraveling the causes of health inequalities, we illustrate their use by analyzing the causes of levels of and changes in inequalities in child malnutrition in Vietnam over the period 1993–98. Whilst its child mortality figures are low by the standards of East Asia, Vietnam has a relatively high incidence of child malnutrition—albeit one that is falling (World Bank et al., 2001). By contrast, malnutrition inequalities were fairly small in Vietnam in 1993 by international standards (Wagstaff and Watanabe, 2000), but they have been rising (World Bank et al., 2001). The two empirical questions we seek to address, therefore, are: Why do inequalities in child malnutrition exist in Vietnam? And why did inequality in child malnutrition rise between 1993 and 1998?

The plan of the paper is as follows. In Section 2, we present the methods for decomposing the causes of health sector inequalities, focusing initially on levels and subsequently analyzing changes in inequality. In Section 3, we outline the empirical model and data we use to decompose the causes of levels of and changes in malnutrition inequalities in Vietnam. Section 4 presents and discusses our decomposition results, and Section 5 contains our conclusions.

Section snippets

Measuring health sector inequalities

We denote by y the variable in whose distribution by socioeconomic status (SES), we are interested.1 The concentration curve, labeled L in Fig. 1, plots the cumulative

Model, data and variable definitions

Our data are from the 1993 and 1998 Vietnam Living Standards Surveys (VLSS). We focus on inequalities in stunting (low height-for-age), which we measure using the negative of the child's height-for-age z-score, with the US National Center for Health Statistics (NCHS) data providing the reference.3

Regression results

Table 1 shows the regression results for 1993 and 1998. The (joint) hypothesis of time-invariant slope coefficients is rejected at just over the 5% level, and the hypothesis of time invariance in the commune fixed effects is decisively rejected. The mean of the commune fixed effects falls considerably between 1993 and 1998, and in each year the hypothesis of zero commune fixed effects is decisively rejected. Child's age has a significant inverted u-shaped relationship in both years (reaching

Conclusions and discussion

Our main aim in this paper has been to present some decomposition methods to enable researchers to unravel the causes of health sector inequalities, and their change over time, or variations across countries. Inequalities are caused by inequalities in the determinants of the variable of interest, and our decomposition in Eq. (3) allows one to assess the relative importance of these different inequalities in generating inequalities in the variable of interest. Changes over time in inequality in

Acknowledgements

Without wishing to implicate them in any way, we are grateful to the following for the helpful comments on an earlier version of the paper or research leading up to it: three anonymous referees; Anne Case, Angus Deaton, Christina Paxson and other participants at a seminar at Princeton; participants at the 2001 International Health Economics Association Meeting in York; Harold Alderman, Alok Bhargava, Deon Filmer, Berk Ozler, Martin Ravallion and Tom Van Ourti. The findings, interpretations and

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