Knowledge that Transforms

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.

We examine whether syndicated loans securitized through collateralized loan obligations (CLOs) have more standardized financial covenants. We proxy for the standardization of covenants using the textual similarity of their contractual definitions. We find that securitized loans are associated with higher covenant standardization than nonsecuritized institutional loans. In addition, we show that CLOs with more diverse or frequently rebalanced portfolios are more likely to purchase loans with standardized covenants, potentially because standardization alleviates information processing costs related to loan monitoring and screening. We also document that covenant standardization is associated with greater loan and CLO note rating agreement between credit rating agencies, further supporting the relation between lower information costs and covenant standardization. Overall, our study provides evidence that loan securitization is related to the design of standardized financial covenants.

We review developments in conducting inference for model parameters in the presence of intertemporal and cross‐sectional dependence with an emphasis on panel data applications. We review the use of heteroskedasticity and autocorrelation consistent (HAC) standard error estimators, which include the standard clustered and multiway clustered estimators, and discuss alternative sample‐splitting inference procedures, such as the Fama–Macbeth procedure, within this context. We outline pros and cons of the different procedures. We then illustrate the properties of the discussed procedures within a simulation experiment designed to mimic the type of firm‐level panel data that might be encountered in accounting and finance applications. Our conclusion, based on theoretical properties and simulation performance, is that sample‐splitting procedures with suitably chosen splits are the most likely to deliver robust inferential statements with approximately correct coverage properties in the types of large, heterogeneous panels many researchers are likely to face.

We show that the cost of trading on negative news, relative to positive news, increases before earnings announcements. Our evidence suggests that this asymmetry is due to financial intermediaries reducing their exposure to announcement risks by providing liquidity asymmetrically. This asymmetry creates a predictable upward bias in prices that increases preannouncement, and subsequently reverses, confounding short‐window announcement returns as measures of earnings news and risk premia. These findings provide an alternative explanation for asymmetric return reactions to firms' earnings news, and help explain puzzling prior evidence that announcement risk premia precede the actual announcements. Our study informs methods for research centering on earnings announcements and offers a possible explanation for patterns in returns around anticipated periods of heightened inventory risks, including alternative firm‐level, industry‐level, and macroeconomic information events.

Companies’ earnings conference calls are perceived to be venues for sell‐side equity analysts to ask management questions. In this study, we examine another important conference call participant—the buy‐side analyst—that has been underexplored in the literature due to data limitations. Using a large sample of transcripts, we identify 3,834 buy‐side analysts from 701 institutional investment firms who participated (i.e., asked a question) in 13,332 conference calls to examine the determinants and implications of their participation. Buy‐side analysts are more likely to participate when sell‐side analyst coverage is low and dispersion in sell‐side earnings forecasts is high, consistent with buy‐side analysts participating when a company's information environment is poor. Institutional investors trade more of a company's stock in the quarters in which their buy‐side analysts participate in the call. Finally, we find evidence that buy‐side analyst participation is associated with company‐level absolute changes in future stock price, trading volume, institutional ownership, and short interest.

This paper uses data on detected misstatements—earnings restatements—and a dynamic model to estimate the extent of undetected misstatements that violate GAAP. The model features a CEO who can manipulate his firm's stock price by misstating earnings. I find the CEO's expected cost of misleading investors is low. The probability of detection over a five‐year horizon is 13.91%, and the average misstatement, if detected, results in an 8.53% loss in the CEO's retirement wealth. The low expected cost implies a high fraction of CEOs who misstate earnings at least once at 60%, with 2%–22% of CEOs starting to misstate earnings in each year 2003–2010, inflation in stock prices across CEOs who misstate earnings at 2.02%, and inflation in stock prices across all CEOs at 0.77%. Wealthier CEOs manipulate less, and the average misstatement is larger in smaller firms.

We show that board tenure exhibits an inverted U‐shaped relation with firm value and accounting performance. The quality of corporate decisions, such as M&A, financial reporting quality, and CEO compensation, also has a quadratic relation with board tenure. Our results are consistent with the interpretation that directors’ on‐the‐job learning improves firm value up to a threshold, at which point entrenchment dominates and firm performance suffers. To address endogeneity concerns, we use a sample of firms in which an outside director suffered a sudden death, and find that sudden deaths that move board tenure away from (toward) the empirically observed optimum level in the cross‐section are associated with negative (positive) announcement returns. The quality of corporate decisions also follows an inverted U‐shaped pattern in a sample of firms affected by the death of a director.

We examine the real effects of FAS 166 and FAS 167 on banks’ loan‐level mortgage approval and sale decisions. Effective in 2010, these standards tightened the accounting for securitizations and consolidation of securitization entities, respectively, causing banks to recognize an estimated $811 billion of securitized assets on balance sheet. We find that banks that recognize more securitized assets exhibit larger decreases in mortgage approval rates and larger increases in mortgage sale rates. These effects significantly exceed those of banks’ off–balance sheet securitized assets, consistent with our results being driven by the consolidation of securitization entities rather than by securitization per se. We conduct tests that help rule out the financial crisis as an alternative explanation for our results. Further analyses suggest that mechanisms underlying the results include consolidating banks’ reduced regulatory capital adequacy, increased market discipline, and consequent desire not to recognize high‐risk mortgages on balance sheet.

We propose a method for using instrumental variables (IV) to draw inference about causal effects for individuals other than those affected by the instrument at hand. Policy relevance and external validity turn on the ability to do this reliably. Our method exploits the insight that both the IV estimand and many treatment parameters can be expressed as weighted averages of the same underlying marginal treatment effects. Since the weights are identified, knowledge of the IV estimand generally places some restrictions on the unknown marginal treatment effects, and hence on the values of the treatment parameters of interest. We show how to extract information about the treatment parameter of interest from the IV estimand and, more generally, from a class of IV‐like estimands that includes the two stage least squares and ordinary least squares estimands, among others. Our method has several applications. First, it can be used to construct nonparametric bounds on the average causal effect of a hypothetical policy change. Second, our method allows the researcher to flexibly incorporate shape restrictions and parametric assumptions, thereby enabling extrapolation of the average effects for compliers to the average effects for different or larger populations. Third, our method can be used to test model specification and hypotheses about behavior, such as no selection bias and/or no selection on gain.

Johansen’s (1988, 1991) likelihood ratio test for cointegration rank of a Gaussian VAR depends only on the squared sample canonical correlations between current changes and past levels of a simple transformation of the data. We study the asymptotic behavior of the empirical distribution of those squared canonical correlations when the number of observations and the dimensionality of the VAR diverge to infinity simultaneously and proportionally. We find that the distribution almost surely weakly converges to the so-called Wachter distribution. This finding provides a theoretical explanation for the observed tendency of Johansen’s test to find “spurious cointegration”. It also sheds light on the workings and limitations of the Bartlett correction approach to the over-rejection problem. We propose a simple graphical device, similar to the scree plot, for a preliminary assessment of cointegration in high-dimensional VARs.