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A direct regression approach to decomposing socioeconomic inequality of health
Author(s) -
Kessels Roselinde,
Erreygers Guido
Publication year - 2019
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.3891
Subject(s) - socioeconomic status , econometrics , inequality , regression , regression analysis , rank (graph theory) , mathematics , cross sectional regression , statistics , variables , health equity , simple linear regression , economics , health care , polynomial regression , medicine , environmental health , population , mathematical analysis , combinatorics , economic growth
Summary This paper presents a new regression‐based decomposition of socioeconomic inequality of health that is more direct than other approaches. The method can be applied to both rank‐dependent and level‐dependent indicators of inequality. The response variable of our regression model is a simple reformulation of the measure of overall performance of an individual in the health and socioeconomic domains. Regression results are described in terms of marginal effects of the explanatory variables, but also in terms of their logworths or importance values. We illustrate our method, and compare it with alternatives, using Australian health and income data.