This study examines whether requiring the disclosure of audited financial statements disciplines managers’ mergers and acquisitions (M&As) decisions. When an M&A transaction meets certain disclosure thresholds, the Securities and Exchange Commission (SEC) requires the public acquirer to disclose the target's audited financial statements after the merger is completed. Using hand‐collected data, I find that the disclosure of private targets’ financial statements is associated with better acquisition decisions. Furthermore, I find that this disciplining effect of disclosure is more pronounced when monitoring by outside capital providers is more difficult and costly, and when other disciplining mechanisms are weaker. Finally, these findings are robust to several alternative explanations, such as monitoring from blockholders and voluntary disclosures. In sum, the evidence suggests that the ex post mandatory disclosure of private targets’ accounting information disciplines managers’ acquisition decisions and improves acquisition efficiency.

We analyze the standard error bias associated with the use of generated regressors—independent variables generated from first‐step regressions—in accounting research settings. Under general conditions, generated regressors do not affect the consistency of coefficient estimates. However, commonly used generated regressors can cause standard errors to be understated. Problematic generated regressors include predicted values, coefficient estimates, and measures derived from these estimates. Widely used generated regressors in accounting include measures of earnings persistence, normal accruals, litigation risk, and conditional conservatism. Using simple regression models and simulation, we demonstrate how generated regressors can produce understated standard errors in accounting research settings. We also demonstrate how the magnitude of the standard error bias is inversely related to the precision of the generated regressor. Finally, we discuss bootstrapping as a correction for the bias and demonstrate the pairs cluster bootstrap as a tool to improve inferences in common accounting settings involving generated regressors.

We analyze a procedure common in empirical accounting and finance research where researchers use ordinary least squares to decompose a dependent variable into its predicted and residual components and use the residuals as the dependent variable in a second regression. This two‐step procedure is used to examine determinants of constructs such as discretionary accruals, real activities management, discretionary book‐tax differences, and abnormal investment. We show that the typical implementation of this procedure generates biased coefficients and standard errors that can lead to incorrect inferences, with both Type I and Type II errors. We further show that the magnitude of the bias in coefficients and standard errors is a function of the correlations between model regressors. We illustrate the potential magnitude of the bias in accounting research in four commonly used settings. Our results indicate significant bias in many of these settings. We offer three solutions to avoid the bias.

Using U.S. banking data between 1993 and 2014, this paper investigates the relationship between CEO optimism and bank liquidity creation. It finds that banks with optimistic CEOs create more liquidity over the entire sample period. In addition, the positive effect of CEO optimism on liquidity creation became stronger during the subprime crisis of 2007‒2009, and this stronger effect was mainly driven by banks with high capital ratios and large banks. These results imply that CEO optimism is likely to encourage banks to create liquidity, especially during banking crises. The results presented in this paper hold when subjected to various robustness checks.

Using U.S. bank data from 1996 to 2013, this paper studies how liquidity risk affects bank performance in financial crises. It finds that during the subprime crisis of 2007–09, liquidity risk reduced a bank’s survival probability, ROA, and net interest margin, and increased its loan-loss-provision expenses. This adverse effect was more severe for banks with lower capital ratios and higher credit risk. In contrast, there is no strong evidence that liquidity risk hurts bank performance in market crises. The results in this paper imply that liquidity risk is not merely a symptom of banks’ insolvency problems; it has an independent effect on bank performance in banking crises.

This study examines whether acquirers make better acquisition decisions when target firms’ financial statements exhibit greater comparability with industry peer firms. We predict and find that acquirers make more profitable acquisition decisions when target firms’ financial statements are more comparable—as evidenced by higher merger announcement returns, higher acquisition synergies, and better future operating performance. We also find that post‐acquisition goodwill impairments and post‐acquisition divestitures are less likely when target firms’ financial statements are more comparable. Finally, we find that acquirers benefit most from comparability when acquirers’ ex ante information asymmetry is higher, acquirers operate in volatile operating environments, and management knows relatively less about the target. In total, our evidence suggests targets’ financial statement comparability helps acquirers make better acquisition‐investment decisions and fosters more efficient capital allocation.