Two essays on discretionary accruals |
| Posted on:2000-08-30 | Degree:Ph.D | Type:Thesis |
| University:Hong Kong University of Science and Technology (People's Republic of China) | Candidate:Chau, Derek Koon-Yee | Full Text:PDF |
| GTID:2469390014962134 | Subject:Business Administration |
| Abstract/Summary: | PDF Full Text Request |
| This thesis contains two essays. Essay 1 entitled “Big Bath and Dress Up in the Course of Chapter 11 Reorganization” investigates whether managers manipulate accruals to help their firms emerge from Chapter 11 reorganization. I argue that since the earnings test is one of the most common tests used to decide whether a reorganization plan is confirmed, managers have the incentives to take a “big bath” at the filing of Chapter 11 and inflate the earnings when the firms try to have their plan confirmed and to emerge from Chapter 11 bankruptcy. The empirical results support the hypotheses. I find significant negative abnormal accruals in the year of filing Chapter 11 and the years of operating under Chapter 11. Both the discretionary operating accruals and the discretionary total accruals are positive in the year before the confirmation of the reorganization plan. However, only the discretionary operating accruals are significant. The evidence also shows that there is a relationship between discretionary accruals and managers' ownership. Essay 2 entitled “Financial Analysts' Assessment of Discretionary Accruals” investigates whether financial analysts can anticipate managers' routine discretionary-accruals choices. It extends and links two major streams of research in accounting: earnings management and analysts' forecasts. It provides evidence that financial analysts do incorporate managers' earnings management incentives in their forecasts and the predictability of discretionary accruals varies across firms. However, measurement errors in discretionary accruals may provide an alternative explanation for the results. |
| Keywords/Search Tags: | Discretionary, Accruals, Chapter |
PDF Full Text Request |
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