AI Article Synopsis
- This paper introduces a new regression-based method for analyzing socioeconomic health inequality, offering a more straightforward approach than existing methods.
- The methodology can be applied to evaluate both rank-dependent and level-dependent measures of inequality.
- The authors demonstrate their technique using Australian health and income data, showcasing how the results can be interpreted through marginal effects and importance values.
Article Abstract
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.
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| http://dx.doi.org/10.1002/hec.3891 | DOI Listing |
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