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We document 45 specific allegations related to audit deficiencies based on GAAS, as detailed in 141 AAERs and 153 securities class action lawsuits over the violation years 1978–2016. Next, we use these allegations to validate popular proxies of audit quality. Of all the audit quality proxies, we find that restatements consistently predict all of the top six most cited audit deficiencies. The ratio of audit fees to total fees and the presence of a city specialist auditor predict five of the most cited deficiencies. Overall, our results suggest that the predictive power of audit quality proxies depends on (i) the settings that researchers are interested in and (ii) the specific audit deficiencies hypothesized to matter in the investigated setting. For instance, future studies related to auditor independence might consider using restatements and the ratio of audit fees to total fees as proxies of audit quality.

Drawing on the political theory of judicial decision making, our paper proposes a new and parsimonious ex ante litigation risk measure: federal judge ideology. We find that judge ideology complements existing measures of litigation risk based on industry membership and firm characteristics. Firms in liberal circuits (the third quartile in ideology) are 33.5% more likely to be sued in securities class action lawsuits than those in conservative circuits (the first quartile in ideology). This result is stronger after the U.S. Supreme Court's ruling in the Tellabs case. We next show that the effect of judge ideology on litigation risk is greater for firms with more sophisticated shareholders and with higher expected litigation costs. Furthermore, judicial appointments affect litigation risk and the value of firms in the circuit, highlighting the economic consequences of political appointments of judges. Finally, using our new measure, we document that litigation risk deters managers from providing long-term earnings guidance, a result that existing measures of litigation risk cannot show.

We study nonofficer directors' influence on the accounting conservatism of U.S. public firms. Between 1986 and 2002, all 50 U.S. states enacted laws that limited nonofficer directors' litigation risk but often left officer directors' litigation risk unchanged. We find that conditional conservatism decreased after the staggered enactments of the laws, which we attribute to less nonofficer director monitoring of financial reporting in affected firms. Conservatism fell less when shareholder or debtholder power was high, consistent with major stakeholders moderating the influence of nonofficer directors. We verify that our results stem from reductions in the asymmetric timeliness of accruals and, specifically, its current assets components. We also show that affected firms switched away from Big N auditors more often, which reduced these firms' commitment to conservative financial reports.

Are regulatory interventions delayed reactions to market failures or can regulators proactively pre-empt corporate misbehavior? From a public interest view, we would expect \"effective\" regulation to ex ante mitigate agency conflicts between corporate insiders and outsiders, and prevent corporate misbehavior from occurring or quickly rectify transgressions. However, regulators are also self-interested and may be captured, uninformed, or ideological, and become less effective as a result. In this registered report, we develop a historical time series of corporate (accounting) scandals and (accounting) regulations for a panel of 26 countries from 1800 to 2015. An analysis of the lead-lag relations at both the global and individual country level yields the following insights: (1) Corporate scandals are an antecedent to regulation over long stretches of time, suggesting that regulators are typically less flexible and informed than firms. (2) Regulation is positively related to the incidence of future scandals, suggesting that regulators are not fully effective, that explicit rules are required to identify scandalous corporate actions, or that new regulations have unintended consequences. (3) There exist systematic differences in these lead-lag relations across countries and over time, suggesting that the effectiveness of regulation is shaped by fundamental country characteristics like market development and legal tradition.

Whistleblowers are ostensibly a valuable resource to regulators investigating securities violations, but whether there is a link between whistleblower involvement and the outcomes of enforcement actions is unclear. Using a data set of employee whistleblowing allegations obtained from the U.S. government and the universe of enforcement actions for financial misrepresentation, we find that whistleblower involvement is associated with higher monetary penalties for targeted firms and employees and with longer prison sentences for culpable executives. We also find that regulators more quickly begin enforcement proceedings when whistleblowers are involved. Our findings suggest that whistleblowers are a valuable source of information for regulators who investigate and prosecute financial misrepresentation.

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.

This paper discusses the empirical literature on the economic consequences of disclosure and financial reporting regulation, drawing on U.S. and international evidence. Given the policy relevance of research on regulation, we highlight the challenges with (1) quantifying regulatory costs and benefits, (2) measuring disclosure and reporting outcomes, and (3) drawing causal inferences from regulatory studies. Next, we discuss empirical studies that link disclosure and reporting activities to firm-specific and market-wide economic outcomes. Understanding these links is important when evaluating regulation. We then synthesize the empirical evidence on the economic effects of disclosure regulation and reporting standards, including the evidence on International Financial Reporting Standards (IFRS) adoption. Several important conclusions emerge. We generally lack evidence on market-wide effects and externalities from regulation, yet such evidence is central to the economic justification of regulation. Moreover, evidence on causal effects of disclosure and reporting regulation is still relatively rare. We also lack evidence on the real effects of such regulation. These limitations provide many research opportunities. We conclude with several specific suggestions for future research.

We develop a state-of-the-art fraud prediction model using a machine learning approach. We demonstrate the value of combining domain knowledge and machine learning methods in model building. We select our model input based on existing accounting theories, but we differ from prior accounting research by using raw accounting numbers rather than financial ratios. We employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. To assess the performance of fraud prediction models, we introduce a new performance evaluation metric commonly used in ranking problems that is more appropriate for the fraud prediction task. Starting with an identical set of theory-motivated raw accounting numbers, we show that our new fraud prediction model outperforms two benchmark models by a large margin: the Dechow et al. logistic regression model based on financial ratios, and the Cecchini et al. support-vector-machine model with a financial kernel that maps raw accounting numbers into a broader set of ratios.

We examine the capital-market effects of changes in securities regulation in the European Union aimed at reducing market abuse and increasing transparency. To estimate causal effects for the population of E.U. firms, we exploit that for plausibly exogenous reasons, such as national legislative procedures, E.U. countries adopted these directives at different times. We find significant increases in market liquidity, but the effects are stronger in countries with stricter implementation and traditionally more stringent securities regulation. The findings suggest that countries with initially weaker regulation do not catch up with stronger countries, and that countries diverge more upon harmonizing regulation.

This study examines whether penalties issued to Chinese listed companies by securities regulators for violations of corporate law affect the cost of debt, and the moderating role of corporate social responsibility (CSR) fulfillment on this relationship. Our sample consists of firms listed on Shanghai and Shenzhen stock exchanges from 2011 to 2017 and the data are collected from the announcements of China Securities Regulatory Commission. The findings are as follows: (1) punishment announcements by regulatory authorities increase the cost of debt; and (2) the effect of punishment announcements on the cost of debt is partially offset by prior CSR performance. These findings are shown to be robust. The reputation insurance effect of CSR is more pronounced in state-owned enterprises and in an institutional environment with low marketization, a weak legal environment, and low information transparency. The findings support the reputation insurance hypothesis of CSR and employ the cost of debt as a governance mechanism.