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Do covariates explain why these groups differ? The choice of reference group can reverse conclusions in the Oaxaca-Blinder decomposition

Manuel Quintero, Advik Shreekumar, William T. Stephenson, Tamara Broderick

arXiv 31 Mar 2026 · Statistics — Methodology

arXiv:2603.29972 · PDF · DOI · OpenAlex · Extracted main text

Abstract

Scientists often want to explain why an outcome is different in two groups. For instance, differences in patient mortality rates across two hospitals could be due to differences in the patients themselves (covariates) or differences in medical care (outcomes given covariates). The Oaxaca--Blinder decomposition (OBD) is a standard tool to tease apart these factors. It is well known that the OBD requires choosing one of the groups as a reference, and the numerical answer can vary with the reference. To the best of our knowledge, there has not been a systematic investigation into whether the choice of OBD reference can yield different substantive conclusions and how common this issue is. In the present paper, we give existence proofs in real and simulated data that the OBD references can yield substantively different conclusions and that these differences are not entirely driven by model misspecification or small data. We prove that substantively different conclusions occur in up to half of the parameter space, but find these discrepancies rare in the real-data analyses we study. We explain this empirical rarity by examining how realistic data-generating processes can be biased towards parameters that do not change conclusions under the OBD.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Fortin, Nicole M. and Lemieux, Thomas and Firpo, Sergio (2011) Decomposition Methods in Economics1.00063100%
2Jann, Ben (2008) The Blinder–Oaxaca Decomposition for Linear Regression Models0.84333100%
3Bach, Philipp and Chernozhukov, Victor and Spindler, Martin (2024) Heterogeneity in the US gender wage gap0.7373367%
4Goldberger, Ary L and Amaral, Luis A N and Glass, Leon and Hausdorff… (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals0.7373367%
5Parada-Contzen, María and Jara, Francisco (2025) Gender wage gap among the educated: evidence from fields of study in Chile0.73732100%
6Rahimi, Ebrahim and Hashemi Nazari, Seyed Saeed (2021) A Detailed Explanation and Graphical Representation of the Blinder–Oaxaca Decomposition Method with its Application in Health In…0.73732100%
7Sharaf, Mesbah Fathy and Rashad, Ahmed S (2016) Regional inequalities in child malnutrition in Egypt, Jordan, and Yemen: a Blinder–Oaxaca decomposition analysis0.73732100%
8O'Neill, June and O'Neill, Dave (2006) What Do Wage Differentials Tell Us about Labor Market Discrimination?0.64422100%
9Bachan, Ray and Bryson, Alex (2022) The Gender Wage Gap Among University Vice Chancellors in the UK0.64422100%
10Cotton, Jeremiah (1988) On the Decomposition of Wage Differentials0.64422100%

Showing the top 10 of 55 scored citations.