We present a unified structural equation modelling framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with a simple ordinary least squares regression. The structural equation modelling framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the bivariate multiple regression model for two-dimensional decomposition. Within the structural equation modelling framework, the two-dimensional decomposition integrates the feedback mechanism between health and socioeconomic status and allows for different sets of determinants of these variables. We illustrate the structural equation modelling approach and its outperformance of ordinary least squares using data from the 2011 Ethiopian Demographic and Health Survey.
Kessels, R.; Erreygers, G. A Unified Structural Equation Modelling Approach for the Decomposition of Rank-Dependent Indicators of Socioeconomic Inequality of Health. UNU-WIDER, Helsinki, Finland (2015) 21 pp. [WIDER Working Paper No. 2015/017]
A Unified Structural Equation Modelling Approach for the Decomposition of Rank-Dependent Indicators of Socioeconomic Inequality of Health