Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/175621
Authors: 
Kessels, Roselinde
Erreygers, Guido
Year of Publication: 
2016
Citation: 
[Journal:] Health Economics Review [ISSN:] 2191-1991 [Volume:] 6 [Year:] 2016 [Issue:] 56 [Pages:] 1-13
Abstract: 
We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM 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 SEM 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 SEM approach and its outperformance of OLS using data from the 2011 Ethiopian Demographic and Health Survey.
Subjects: 
Inequality measurement
Generalized health Concentration Index
Decomposition methods
Structural Equation Modeling
JEL: 
C36
D63
I00
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/4.0/
Document Type: 
Article
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