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The importance of individual heterogeneity in the decomposition of measures of socioeconomic inequality in health: An approach based on quantile regression

Andrew Jones () and Ángel López-Nicolás
Authors registered in the RePEc Author Service: Ángel López Nicolás ()

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: This paper shows how recently developed regression-based methods for the decomposition of health inequality can be extended to incorporate individual heterogeneity in the responses of health to the explanatory variables. We illustrate our method with an application to the Canadian NPHS of 1994. Our strategy for the estimation of heterogeneous responses is based on the quantile regression model. The results suggest that there is an important degree of heterogeneity in the association of health to explanatory variables which, in turn, accounts for a substantial percentage of inequality in observed health. A particularly interesting finding is that the marginal response of health to income is zero for healthy individuals but positive and significant for unhealthy individuals. The heterogeneity in the income response reduces both overall health inequality and income related health inequality.

Keywords: Health inequalities; unobserved heterogeneity; quantile regression (search for similar items in EconPapers)
JEL-codes: C13 C15 D72 (search for similar items in EconPapers)
Date: 2002-06
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Working Paper: The importance of individual heterogeneity in the decomposition of measures of socioeconomic inequality in health: An approach based on quantile regression (2002) Downloads
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