Structural equation modeling for decomposing rank-dependent indicators of socioeconomic inequality of health: an empirical study

Roselinde Kessels*, Guido Erreygers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Article number56
Number of pages13
JournalHealth Economics Review
Publication statusPublished - 7 Dec 2016
Externally publishedYes

JEL classifications

  • c36 - Multiple or Simultaneous Equation Models: Instrumental Variables (IV) Estimation
  • d63 - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
  • i00 - Health, Education, and Welfare: General


  • Inequality measurement
  • Generalized health Concentration Index
  • Decomposition methods
  • Structural Equation Modeling

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