What does this research mean for the field?

Two newly developed measures, analogous to R-squared in regression analysis, can effectively quantify the proportion of inequality explained by individual or grouped population characteristics. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This research aims to develop measures to quantify how much inequality can be attributed to various population characteristics.

March 1, 1995

How Much Inequality Can we Explain? A Methodology and an Application to the United States

Key Points

This research aims to develop measures to quantify how much inequality can be attributed to various population characteristics.
Developed two measures analogous to R2 for inequality explanation.
Utilized alternative theoretically consistent approaches for inequality decomposition.
Applied measures to US Panel Study of Income Dynamics (PSID) income data.
Demonstrated the effectiveness of the proposed measures in explaining inequality.
Identified significant population characteristics contributing to income inequality.
Results provide insights into the complexity of socio-economic disparities in the US.

Abstract

We develop two simple measures of how much inequality is explained by individual population characteristics or groups of characteristics, analogous to R2 in regression analysis. We investigate the measures' empirical implementation using several alternative theoretically consistent approaches to inequality decomposition. Results are illustrated using US PSID income data.

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Cite This Study

Cowell et al. (Wed,) studied this question.

synapsesocial.com/papers/6a072626616fd0436a843162 https://doi.org/https://doi.org/10.2307/2235501

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