Jim A. Seida

Applying reverse regression techniques in earnings–return analyses ☆

Abstract Measurement error in unexpected earnings is recognized as a source of bias in examinations of the relation between earnings and returns. Reverse regression procedures are commonly used as a means of coping with this bias. This study examines the properties of reverse regression procedures in multi-interacted variable settings with a specific focus on the earnings response coefficient (ERC) analysis of Collins and Kothari (J. Account. Econom. 11 (1989) 143.). It shows that both conventional reverse regression techniques and novel techniques employed by Collins and Kothari are not robust. It also demonstrates how reverse regression techniques can be successfully employed in such settings using non-interacted-variable designs.