Average Gaps and Oaxaca's Blinder Decompositions: A Cautionary Tale about Regression Estimates of Racial Differences in Labor Market Outcomes

Tymon Słoczyński

No 12041, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: In this paper I demonstrate, both theoretically and empirically, that the interpretation of regression estimates of between-group differences in economic outcomes depends on the relative sizes of subpopulations under study. When the disadvantaged group is small, regression estimates are similar to its average loss. When this group is instead a numerical majority, regression estimates are similar to the average gain for advantaged individuals. I analyze black–white test score gaps using ECLS-K data and black–white wage gaps using CPS, NLSY79, and NSW data, documenting that the interpretation of regression estimates varies dramatically across applications. Methodologically, I also develop a new version of the Oaxaca–Blinder decomposition whose unexplained component recovers a parameter referred to as the average outcome gap. Under a particular conditional independence assumption, this estimand is equivalent to the average treatment effect (ATE). Finally, I provide treatment-effects reinterpretations of the Reimers, Cotton, and Fortin decompositions.

Keywords: decomposition methods; black-white gaps; treatment effects; test scores; wages (search for similar items in EconPapers)
JEL-codes: C21 I24 J15 J31 J71 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2018-12
New Economics Papers: this item is included in nep-ecm and nep-lma
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Published - published in: Industrial and Labor Relations Review, 2020, 73 3), 705–729

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Related works:
Working Paper: Average Gaps and Oaxaca–Blinder Decompositions: A Cautionary Tale about Regression Estimates of Racial Differences in Labor Market Outcomes (2018)
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