To test hypotheses about earnings management, many studies investigate managers' manipulation of real activities (real earnings management, REM). Tests using measures of abnormal REM hinge critically on the measurement of normal real activities. Yet, there is no systematic evidence on the statistical properties of commonly used REM measures. We provide such evidence by documenting the Type I error rates and power of the test of the REM measures commonly used in the literature. We find these measures are often misspecified with Type I error rates that deviate from the nominal significance level of the test, especially in samples of firms with extreme performance or firm characteristics. We also compare the specification and power of traditional REM measures with performance‐matched REM measures to see if the latter provide better specified and more powerful tests. While performance‐matched REM measures are not immune from misspecification in all settings, in general they are better specified under the null hypothesis (i.e., in terms of Type I errors) than are traditional REM measures. Comparisons of the power to detect abnormal REM reveal that neither approach, traditional or performance‐matched, is consistently more powerful than the other in terms of detecting abnormal REM ranging from 1 to 10 percent of (lagged) total assets. The absence of a dominant approach to measure abnormal REM leads us to recommend that future researchers report results using both traditional and performance‐matched measures, so that readers are able to clearly assess the reliability of the inferences drawn about the magnitude and significance of the abnormal REM documented in a given study.

We examine whether customer-base concentration has a differential impact on profitability for firms contracting with major government customers versus firms contracting with major corporate customers. We document that firm profitability increases with the concentration of major government customers, but decreases with the concentration of major corporate customers. We attribute the contrasting results to the differential impact of major government and corporate customers on demand uncertainty. Specifically, firms contracting with major government customers face lower demand uncertainty that enables them to realize more efficiency gains from customer-specific investments, whereas firms contracting with major corporate customers are exposed to higher demand uncertainty that reduces the efficiency of customer-specific investments. Overall, our study suggests that major government customers are unique and important in the composition of customer base, and they impact firm outcomes in a significantly different way than major corporate customers.

Using the complete history of regular quarterly and annual filings by U.S. corporations, we show that changes to the language and construction of financial reports have strong implications for firms’ future returns and operations. A portfolio that shorts “changers” and buys “nonchangers” earns up to 188 basis points per month in alpha (over 22% per year) in the future. Moreover, changes to 10‐Ks predict future earnings, profitability, future news announcements, and even future firm‐level bankruptcies. Unlike typical underreaction patterns, we find no announcement effect, suggesting that investors are inattentive to these simple changes across the universe of public firms.

While current audit standards explicitly state engagement partner tenure requirements, firms have flexibility in managing the rotation process. We conduct semi-structured interviews with 20 U.S. audit firm partners who share their experiences on topics including how they identify appropriate candidate partners and what efforts they undertake to manage relationships with clients post-rotation. We investigate firms' motivation to manage the auditor-client relationship through the lens of Social Exchange Theory (SET), and we consider how likely outcomes of this rotation process map onto regulators' intent that a newly rotated partner provides a fresh perspective to the audit. Our study informs regulators and investors about the process by which engagement partners are selected for rotation, documenting that partner assignment is typically not random. Further, our finding that partner rotation is an extended process (rather than a single discrete event) has implications for audit researchers investigating the effects of partner rotation.