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Addressing Unobserved Selection Bias in Accounting Studies: The Bias Minimization Method

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  • Michael J. Peel

Abstract

This note explains the minimum-biased estimator (MBE), which accounting researchers can use to analyze the robustness of regression or propensity score-matched treatment estimates to unobserved selection (endogeneity) bias. Based on the principles of the Heckman treatment model, the MBE entails estimating matched treatment effects within a range of propensity scores that minimizes unobserved selection bias. A major advantage of the MBE is that an instrumental variable is not required. The potential utility of the MBE in accounting studies is highlighted, and a familiar empirical illustration is provided.

Suggested Citation

  • Michael J. Peel, 2018. "Addressing Unobserved Selection Bias in Accounting Studies: The Bias Minimization Method," European Accounting Review, Taylor & Francis Journals, vol. 27(1), pages 173-183, January.
    • Handle: RePEc:taf:euract:v:27:y:2018:i:1:p:173-183
    DOI: 10.1080/09638180.2016.1220322
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