Knowledge that Transforms

ABSTRACT Commonly used Jones-type discretionary accrual models applied in quarterly settings do not adequately control for nondiscretionary accruals that naturally occur due to firm growth. We show that the relation between quarterly accruals and backward-looking sales growth (measured over a rolling four-quarter window) and forward-looking firm growth (market-to-book ratio) is non-linear. Failure to control for the effects of firm growth and performance on innate accruals leads to excessive Type I error rates in tests of earnings management. We propose simple refinements to Jones-type models that deal with non-linear growth and performance effects and show that the expanded models are well-specified and exhibit high power in quarterly settings where one is testing for earnings management. The expanded models are able to identify the presence of earnings management in a sample of restatement firms. Our findings have important implications for the use of discretionary accrual models in earnings management research. JEL Classifications: C15; M40; M41.

ABSTRACT Credit ratings on many financial instruments failed to accurately portray default risk before the global financial crisis. I find no decline in the performance of corporate credit ratings during or after the crisis, indicating that the failures of ratings on financial instruments were due to conditions unique to the rating agencies' financial instruments divisions. Rather, the preponderance of tests indicate that corporate credit rating performance improves after the crisis, consistent with the rating agencies positively responding to public criticism and regulatory pressures. At the same time, I find evidence of sophisticated market participants decreasing their reliance on corporate credit ratings after the crisis. Consistent with theoretical models of reputation cyclicality, a likely explanation is that the rating agencies suffer spillover reputation damage from their failed ratings on financial instruments. My study informs regulators, practitioners, and academics about the performance of corporate credit ratings during and after the crisis, and provides novel empirical evidence consistent with reputation concerns affecting credit rating usage decisions.

ABSTRACT This paper examines whether and to what extent repatriation tax costs constrain U.S. multinational companies' (MNCs) distributions to shareholders. During the 1987–2004 sample period, I find that repatriation tax costs decrease U.S. MNCs' dividend payments, and the economic magnitude of the effect is substantial. I do not find evidence that repatriation tax costs decrease U.S. MNCs' share repurchases, on average. I find cross-sectional variation in the effect of repatriation tax costs on share repurchases based on U.S. MNCs' opportunities to fund repurchases through external borrowing and to minimize the incremental U.S. cash tax cost of repatriations. I do not observe an association between repatriation tax costs and U.S. MNCs' dividend payments or share repurchases during a more recent time period (2009–2014). This study contributes to our understanding of the impact of the current U.S. worldwide tax system on U.S. MNCs' real decisions and of the determinants of firms' payout policies.

ABSTRACT This study examines the relation between auditors and their clients' investment efficiency. We hypothesize and find that auditor characteristics that proxy for an auditor's knowledge and resources are associated with higher client investment efficiency, after controlling for the auditor's effect on financial reporting quality. This result is consistent with auditors providing informational advantages to their clients in a generalized investment setting. We find that this auditor effect is more pronounced for clients who have a higher demand for information as measured by client size, industry competition, and client complexity. The effect is also more pronounced for clients of longer-tenured auditors. Overall, the results suggest that auditors may be one component to the management information environment and, as such, appear to influence capital investment behavior. JEL Classifications: M4; M42. Data Availability: All data are publicly available.

ABSTRACT In this study, we examine how information foraging by auditors affects audit evidence collection in two distinct contexts, and show how a small change to audit methodology mitigates the potentially harmful effects of foraging. Information Foraging Theory explains how, while navigating an information environment, individuals learn to acquire information through personally experiencing the costs incurred and the values obtained from information. Consistent with the theory, we find that auditors react to the immediately felt costs of information collection (e.g., time and effort) at the expense of a more global consideration of information value (i.e., auditors collect lower-quality audit evidence). However, foraging behavior is moderated by removing the personal cost to the individual auditor (identifying audit evidence for another member of the audit team to collect), further demonstrating that these personally felt costs influence auditor choices in a way that reduces the quality of information collected. We contribute to the literature by demonstrating how information foraging can influence evidence quality and, thus, audit quality, and how a slight alteration of audit methodology can mitigate this behavior.

ABSTRACT Earnings growth dispersion contains information about trends in labor reallocation, unemployment change, and, ultimately, aggregate output. We find that initial macroeconomic estimates released by government statistical agencies do not fully incorporate this information. As a consequence, earnings growth dispersion predicts future restatements in nominal and real GDP growth (and unemployment change) both in the in-sample and out-of-sample tests. Further, when we adjust GDP estimates using the out-of-sample restatement predictions, we find statistically and economically significant effects for the monetary policy prescriptions (Taylor rule) and banking regulation (Basel III).

ABSTRACT We classify all institutional investors that file Form 13-F over the period 1995–2013 as either “tax-sensitive” or “tax-insensitive” based on their trading behavior and portfolio characteristics. We examine tests of the effects of investor tax-sensitivity on portfolio rebalancing, price pressure, and fund performance, and compare our measure of tax-sensitive institutional investor ownership to three measures used in prior studies. We show that our measure of tax-sensitive investors dominates other measures in the portfolio rebalancing and price pressure tests. In the fund performance test, our measure of tax-sensitivity is the only one that finds that tax-sensitive investors have significantly lower returns on their portfolio stocks, which is a new result in the literature. JEL Classifications: G11; G20; H24.

ABSTRACT We examine how the co-location of firms in the same industry affects analysts' cost of gathering and processing information. We find that when the firms in an analyst's portfolio are located farther away from other firms in the same industry, the analyst's portfolio size is smaller and average forecast accuracy is lower. We further find that the additional costs that analysts incur to follow distant firms are amplified when earnings are more difficult to forecast. Last, we provide some evidence that managers are more knowledgeable about other firms in the same geographic area. Specifically, managers are more likely to reference firms in their industry that are geographically closer during conference calls. This paper provides additional evidence that the co-location of firms in the same industry not only affects operating and strategic decisions (as documented in the existing literature), but also analysts' costs of gathering and analyzing information about the firm. JEL Classifications: D83; M40; M41; R10; R12.

ABSTRACT An extensive literature examines the causes and effects of financial misconduct based on samples drawn from four popular databases that identify restatements, securities class action lawsuits, and Accounting and Auditing Enforcement Releases (AAERs). We show that the results from empirical tests can depend on which database is accessed. To examine the causes of such discrepancies, we compare the information in each database to a detailed sample of 1,243 case histories in which regulators brought enforcement actions for financial misrepresentation. These comparisons allow us to identify, measure, and estimate the economic importance of four features of each database that affect inferences from empirical tests. We show the extent to which each database is subject to these concerns and offer suggestions for researchers using these databases. JEL Classifications: G38; K22; K42; M41.

ABSTRACT Developing models to detect financial statement fraud involves challenges related to (1) the rarity of fraud observations, (2) the relative abundance of explanatory variables identified in the prior literature, and (3) the broad underlying definition of fraud. Following the emerging data analytics literature, we introduce and systematically evaluate three data analytics preprocessing methods to address these challenges. Results from evaluating actual cases of financial statement fraud suggest that two of these methods improve fraud prediction performance by approximately 10 percent relative to the best current techniques. Improved fraud prediction can result in meaningful benefits, such as improving the ability of the SEC to detect fraudulent filings and improving audit firms' client portfolio decisions.