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

European Accounting Review 27(1), pp. 173-183, 2018

Posted: 23 Feb 2018 Last revised: 19 Dec 2018

See all articles by Michael J. Peel

Michael J. Peel

Cardiff University - Cardiff Business School

Date Written: February 16, 2018

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.

Keywords: Unobserved (endogenous) selection bias, propensity score matching, bias minimization method, Heckman treatment model, empirical illustration

JEL Classification: C10, C21, M40, M41

Suggested Citation

Peel, Michael J., Addressing Unobserved Selection Bias in Accounting Studies: The Bias Minimization Method (February 16, 2018). European Accounting Review 27(1), pp. 173-183, 2018 , Available at SSRN: https://ssrn.com/abstract=3124865

Michael J. Peel (Contact Author)

Cardiff University - Cardiff Business School ( email )

Cardiff
United Kingdom

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