Attrition bias and inferences regarding earnings properties

51 Pages Posted: 21 Sep 2017 Last revised: 8 Jul 2021

See all articles by Peter D. Easton

Peter D. Easton

University of Notre Dame - Department of Accountancy

Martin M. Kapons

University of Amsterdam - Amsterdam Business School

Peter Kelly

University of Notre Dame

Andreas Neuhierl

Washington University in St. Louis - John M. Olin Business School

Date Written: August 18, 2020

Abstract

On average, across the years 1980 to 2019, almost 8.4 percent of firms on the Compustat Annual data set, which had earnings and return observations in year t-1, did not have earnings observations in year t. Because these disappearances were not random, there is attrition bias in estimates of fundamental properties of earnings including: earnings persistence, mean reversion, accuracy of earnings forecasts, asymmetric timeliness, and market pricing of earnings persistence. We show that conclusions about these properties change when we impute the disappeared earnings observations using four parsimonious methods and when we use inverse probability weighting in least squares regressions.

Keywords: earnings, forecasts

JEL Classification: G14

Suggested Citation

Easton, Peter D. and Kapons, Martin M. and Kelly, Peter and Neuhierl, Andreas, Attrition bias and inferences regarding earnings properties (August 18, 2020). Available at SSRN: https://ssrn.com/abstract=3040354 or http://dx.doi.org/10.2139/ssrn.3040354

Peter D. Easton

University of Notre Dame - Department of Accountancy ( email )

Mendoza College of Business
Notre Dame, IN 46556-5646
United States
574-631-6096 (Phone)
574-631-5127 (Fax)

Martin M. Kapons

University of Amsterdam - Amsterdam Business School ( email )

Spui 21
Amsterdam, 1018 WB
Netherlands

Peter Kelly (Contact Author)

University of Notre Dame ( email )

251 Mendoza
South Bend, IN 46637
United States

Andreas Neuhierl

Washington University in St. Louis - John M. Olin Business School ( email )

St. Louis, MO
United States

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