The Effects of Firm Growth and Model Specification Choices on Tests of Earnings Management

Conditional conservatism and disaggregated bad news indicators in accrual models

“…In other words, the proportion of false inferences (nonrejection of a false null hypothesis) is reduced by almost one-third, from 12.0 % (=100 -88) in the Allen et al model to just 8.5 % (=100 -91.5) in our extended asymmetric model. We find a comparable improvement in test power when we simulate a discretionary accrual of 0.25 or 0.5 % of total assets for 2000 observations (Collins et al 2014b).…”

“…The results in Tables 3, 4, 5 and 6 are robust to alternative definitions of cash flows and accruals, including measures derived from the SFAS 95 (FASB 1987) statement of cash flows, following Collins and Hribar (2002); measures that combine SFAS 95 data with earlier data from the funds flow statement, following Xie (2001); and broader accrual measures based on net income. The estimates are robust to controlling for market-to-book quintiles as a proxy for expected long-term growth (Collins et al 2014b), realized changes in sales and employees in year t ? 1 as a short-term expected growth proxy, asset market-to-book ratio above one as a (3) Asymmetric model with fourth-quarter sales data (6) Extended model with interactions of annual and quarterly data Effect of fourth-quarter sales change during annual sales decreases (DS) adj.…”

“…Following prior studies (Dechow et al 1995(Dechow et al , 2012Kothari et al 2005;Collins et al 2014b), we simulate earnings management tests for different accrual models. For brevity, we focus on four models: the Allen et al model (1), the Ball and 23 Bushman et al (2011a) predict and find that conservatism leads to an asymmetry in firms' capital expenditures because it gives managers an incentive to quickly cut capital expenditures when investment opportunities decrease but does not have a comparable incentive effect when investment opportunities increase.…”

“…In the performance subsamples in Panel B, the suspect observations are randomly selected from the top or bottom decile of the relevant performance variable, following the simulation protocol from Dechow et al (2012). In the performance subsamples in Panel C, half of the 2000 suspect observations are randomly selected from the top or bottom decile of the relevant performance variable, and the other half are randomly selected from the remainder of the sample following Collins et al (2014b). We estimate each model industry by industry for all observations in the full sample, using the original data for accruals, and test whether the average abnormal accrual for the suspect observations is significantly different from zero at the 10 % significance level in a two-tailed t-test.…”

“…Thus a researcher should incorporate asymmetries for all indicators to avoid type I error due to mis-specified linear functional form. 27 We next examine type I errors in the simulation protocol suggested by Collins et al (2014b), who argue that the treatment sample should be larger and more heterogeneous. They simulate a suspect subsample of 2000 observations, half of which are selected from a given extreme performance partition and the other half from the remainder of the sample.…”