Measurement Error and Bias in Causal Models in Accounting Research

43 Pages Posted: 8 Jan 2021

See all articles by Jared N. Jennings

Jared N. Jennings

Washington University in St. Louis

Jung Min Kim

University of Pennsylvania - The Wharton School

Joshua A. Lee

Brigham Young University

Daniel J. Taylor

The Wharton School, University of Pennsylvania

Date Written: November 1, 2020

Abstract

“Measurement error biases against [finding results]” is an often-repeated phrase used to dismiss validity threats arising from measurement error. As a general rule, this phrase is false. We provide examples of commonly encountered circumstances where the variable of interest is exogenous––the gold standard for causal inference––but where measurement error in empirical proxies nonetheless bias in favor of rejecting a true null hypothesis. In addition, we show that the common practice of including high-dimensional fixed effects, specifically firm fixed effects, can exacerbate this bias and lead researchers to spuriously estimate a causal effect when none exists. Finally, we show that measurement error pervades the accounting literature, and illustrate the effect of measurement error on causal inferences in a popular quasi-natural experimental setting where we can observe the measurement error in the treatment variable. We encourage researchers to triangulate inferences across multiple empirical proxies and to report results from specifications with and without high-dimensional fixed effects.

Keywords: measurement error, fixed effects, causal models, accounting research

Suggested Citation

Jennings, Jared N. and Kim, Jung Min and Lee, Joshua A. and Taylor, Daniel, Measurement Error and Bias in Causal Models in Accounting Research (November 1, 2020). Available at SSRN: https://ssrn.com/abstract=3731197

Jared N. Jennings

Washington University in St. Louis ( email )

One Brookings Drive
Campus Box 1208
Saint Louis, MO MO 63130-4899
United States

Jung Min Kim

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

Joshua A. Lee

Brigham Young University ( email )

United States
801-422-3154 (Phone)

HOME PAGE: http://https://marriottschool.byu.edu/directory/details?id=37414

Daniel Taylor (Contact Author)

The Wharton School, University of Pennsylvania ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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