Back to Search
Start Over
Accrual earnings management, real earnings management, and information uncertainty
- Publication Year :
- 2022
- Publisher :
- Kingston University, 2022.
-
Abstract
- The aim of this thesis is to contribute to the research on earnings management, by first investigating models of real earnings management, then extending the literature by examining both accrual and real earnings management within the context of information uncertainty. The thesis comprises of three main studies which analyse secondary data of firms with available data that are listed on the London Stock Exchange during the period from 1992 to 2018. In the first empirical chapter, the relative performance of models to detect accrual earnings management and real earnings management is evaluated by comparing the power of widely used models. The power of test statistics of earnings management detection models is evaluated through examining the frequency with which detection models of accrual earnings management and real earnings management generate type II errors. I adopt a similar approach to that used by Dechow et al. (1995)and Brown and Warner (1985)in which I randomly select a sample of firm-year observations and artificially add accrual manipulation and real earnings management with the magnitude ranging from 0 percent to 10 percent of lagged assets. I compare the bias in the estimates of accrual earnings management generated by Dechow et al. (1995),Kothari et al. (2005),Modified Dechow and Dichev (2002)model and real earnings management produced by the Roychowdhury (2006)models. The results show that the detection models for real earnings management generates larger biased estimates of real earnings management activities compared to models to detect accrual-based earnings management. Among the three types of real earnings management activities, the power of the model for detecting real-based sales manipulation is lowest due to the biased estimates. Moreover, the power of the model for uncovering abnormal research and development (R&D) expenditure is improved when lagged R&D expenditures is added to the existing model. The second empirical chapter investigates the role of information uncertainty in explaining the opportunistic behaviour of managerial discretion when firms have high incentives to manage earnings (i.e., meeting/beating earnings benchmarks). To address endogeneity, in which there are potential differences in characteristics of suspect firms (i.e., those beating earnings expectations) and non-suspect firms (i.e., those missing earnings expectations), I apply propensity score matching (PSM) developed by Rosenbaum and Rubin (1983)(Shipman et al., 2016).More specifically, suspects are matched with non-suspects (by one- to-one matching without replacement) that have the closest propensity-matching score. These scores are based on a range of different firm characteristics. In addition, this study also uses Heckman (1979)selection model that depends on a particular functional form to give an indirect estimate of suspect firms' treatment effects. This empirical evidence contributes to the existing literature by determining the condition in which accrual-based earnings management occurs. Under the condition of high information uncertainty, managerial opportunistic behaviour is unobservable and difficult to detect by market participants; hence, the result shows that when facing high information uncertainty, managers of firms beating earnings expectation are more likely to use discretionary accruals. Moreover, managers of suspect firms also engage in earnings smoothing under the condition of high information uncertainty. In addition, this study contributes to the literature by exploring the role of information uncertainty in managers' decisions to use accrual earnings management compared to real earnings management. The last empirical chapter examines the effect of information uncertainty on the long-run performance of firms meeting/beating earnings expectations. There is mixed evidence about whether market participants are irrationally over-optimistic about the information contained within earnings announcements. The evidence provided in this chapter contributes to our knowledge on the interaction effect of information uncertainty on the mispricing of investors. Indeed, empirical results show that firms meeting/beating earnings benchmarks underperform in the long-run period under high information uncertainty compared to low information uncertainty, after controlling for variables such as firm size, market-to-book ratio, capital expenditures, and sales growth in the fiscal year that earnings are announced. The results are robust after using alternative measures of stock performance. The evidence overall suggests that the condition of information uncertainty is necessary for explaining irrational behaviour of investors. These findings indicate that future underperformance may follow managed earnings under high information uncertainty.
- Subjects :
- accrual earnings management
real earnings management
information uncertainty
Subjects
Details
- Language :
- English
- Database :
- British Library EThOS
- Publication Type :
- Dissertation/ Thesis
- Accession number :
- edsble.868283
- Document Type :
- Electronic Thesis or Dissertation