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Detecting Earnings Management Dechow , Sloan, Sweeney (1995). Septian Bayu K. (0806479080). Outline. Introduction Statistical Background Measuring DA Experimental Design Data Analysis Empirical Results Conclusions Implications. Introduction (1). - PowerPoint PPT Presentation
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SEPTIAN BAYU K. (0806479080)
Detecting Earnings Management
Dechow, Sloan, Sweeney (1995)
Outline
IntroductionStatistical BackgroundMeasuring DAExperimental DesignData AnalysisEmpirical ResultsConclusionsImplications
Introduction (1)
Analysis of earnings management focuses on discretionally accruals (DA) Separate total accruals to DA & NDA
The aim of research Finding the sophisticated model(s) to measure to
detect earnings management with DA/NDA
Research gap Modified Jones Model
Introduction (2)
Prior research DA: Healy (1995), DeAngelo (1996), Jones (1991) Accounting procedure changes: Healy (1985), Healy &
Palepu (1990), Sweeney (1994) Specific components of DA: McNichols & Wilson
(1988), DeAngelo et al (1994) Components of Discretionary Cash Flow (Dechow &
Sloan (1991)
Statistical Background
McNichols & Wilson (1988)
Problems: Incorrectly attributing earnings management to
PART Unintentionally extracting earnings management
caused by PART Low power test
Measuring DA (1)
The Healy model (Healy, 1985)
The DeAngelo model (DeAngelo, 1986) NDAτ = TAτ-1
The Jones model (Jones, 1991)
Measuring DA (2)
The Modified Jones model
The Industry model (Dechow & Sloan, 1991) NDA τ = γ1 + γ2 median1 (TA τ)
Experimental Design
Randomly 1000 firm-years (1950-1991)Firm-years experiencing extreme financial
performanceFirm-years with accrual manipulation
Expense manipulation Revenue manipulation Margin manipulation
32 firms that are subject to SEC enforcement actions
Data Analysis
Total accruals (TA)
CFO = Earnings – TA Using Z-statistic
Empirical Results
Random sample of firm-years Table 1, table 2
Samples of firm-years experiencing extreme financial performance Figure 1, table 3, figure 2, table 4
Samples of firm-years with artificially induced earnings management Figure 3, figure 4
Sample of firm-years in which of the SEC alleges earnings are overstated Figure 5, table 5, table 6, table 7
Conclusions
All of models appear well specified when applied to random sample of the firm-years
The models all generate test of low power of earnings management
All models reject the null hypothesis of no earnings management
Modified Jones model generate the revenue –based earnings management
Implications
Regardless of the model used to detect earnings management Further research: develop new model with more
powerful test to detect earnings management
Correlation between PART ad firm performance, considered the models
Consider about earnings management context