Understanding the "Numbers Game"

• In Event: Earnings Management - II

Abstract

We model the earnings management decision as the manager’s tradeoff between the costs and capital market benefits of meeting earnings benchmarks. Using a regression discontinuity design, we estimate these benefits and the realized earnings distribution as model inputs. Estimated model parameters yield the percentage of manipulating firms, magnitude of manipulation, noise in manipulation, and sufficient statistics to evaluate proxies for “suspect” firms. Finally, we use SOX as a policy experiment and find that, by increasing costs, it reduced earnings management by 36%. This occurred despite an increase in benefits, as the market rationally became less skeptical of firms just-meeting benchmarks.

Authors

• Stephen Adam Karolyi, Carnegie Mellon University

• Andrew Bird, Carnegie Mellon University

• Thomas Ruchti, Carnegie Mellon University