Measure of Intentional Manipulation: A Structural Approach

• In Event: Methodologies in Earnings Management Research

Abstract

Using a sample of about 1,500 CEOs in the post-SOX period, I estimate the extent of intentional manipulation and manipulation costs using a dynamic finite-horizon structural model that features a risk-averse manager who receives cash and equity compensation. I find that the expected cost of manipulation is low. The probability of detection is estimated at 9.76% and 7.91%, and the average misstatement results in a 13.13% and 20.78% loss in the manager's wealth depending on a definition of an intentional misstatement. According to the estimated parameters, the implied fraction of manipulating firms is around 65% and 55% and the value-weighted bias in the stock price is 17.93% and 20.03% across manipulating CEOs; whereas for all CEOs, the value-weighted bias in the stock price is 5.83% and 4.43%. Among five proxies for earnings management used in the extant literature, the four of them have a negative association with the model-implied measure of intentional manipulation.

Author

• Anastasia A Zakolyukina, The University of Chicago