Most interpretations of prevalent counterinsurgency theory imply that increasing government services reduces rebel violence. Empirically, however, development programs and economic activity sometimes increase violence. Using new panel data on development spending in Iraq, we show that violence-reducing effects of development assistance are greater when: (i) projects are small; (ii) troop strength is high; and (iii) professional development expertise is available. These findings are consistent with an information-centric (“hearts and minds”) model, which implies that violence-reduction is greatest when projects are secure, valued by community members, and services derived are conditional on government control of the territory.

In this study, we examine whether firms respond to internal control weaknesses (ICWs) by requiring accounting-specific skills when hiring rank-and-file employees. Using unique data containing an extensive collection of job postings, we document significant increases in firms’ job postings that list accounting skills after the disclosure of an ICW. This effect is more pronounced for firms with better financial resources and when ICWs are more severe or personnel-related. In addition, our results extend to employees that are not specifically designated as accountants, suggesting a broader role for rank-and-file employees in influencing internal control quality. Finally, we find that increases in job postings with accounting skill requirements are associated with improvements in internal controls and a higher likelihood of ICW remediation. Overall, our findings shed new light on how firms respond to ineffective internal controls by increasing their emphasis on accounting skills in their workforce. Data Availability: Data are publicly available from the sources identified in the text.

We investigate whether firms manage stock prices in anticipation of share issuance. Warrant exercise results in share issuance and warrant expiration dates are fixed years in advance, which precludes market timing. We predict firms manage stock prices to prevent (induce) warrant exercise when exercise is dilutive (anti-dilutive) to existing shareholders. To test our prediction, we examine stock returns around warrant expiration dates. We find that the difference between out-of-the-money (OTM) and in-the-money (ITM) firms' return patterns (i.e., post-expiration minus pre-expiration returns) is positive, and OTM (ITM) firms' return pattern is positive (negative). Return patterns of three sets of pseudo warrant firms differ from patterns of warrant firms. Return patterns are stronger when more feasible price changes are required to affect warrant expiration status, and firm-issued news items is a mechanism for price management. Thus, our findings provide evidence that firms engage in stock price management in anticipation of share issuance.

Audit practitioners, academics, and attorneys have expressed concern that disclosing critical audit matters (CAMs) will increase jurors' auditor liability judgments when auditors fail to detect misstatements. In contrast, this study provides theory and experimental evidence that CAM disclosures, under certain conditions, reduce auditor liability judgments as jurors perceive that undetected fraudulent misstatements were more foreseeable to the plaintiff (i.e., the financial statement user suing the auditor). However, we find that CAM disclosures only reduce auditor liability for undetected misstatements that, absent CAM disclosure, are relatively difficult to foresee. Finally, CAM disclosures that are unrelated to subsequent misstatements neither increase nor reduce auditor liability judgments relative to the current regime (i.e., where CAMs are not disclosed), but reduce liability judgments relative to reporting that there were no CAMs. As such, we find that, relative to stating there were no CAMs, disclosure of any CAM (i.e., related or unrelated) provides litigation protection in cases of undetected fraud. Consequently, the CAM requirement could incentivize auditors to disclose innocuous boilerplate CAMs, thereby diluting the impact of more warranted CAM disclosures. Data Availabliity: Available from authors upon request.

Measures of private equity (PE) performance based on cash flows do not account for a discount‐rate risk premium that is a component of the capital asset pricing model (CAPM) alpha. We create secondary market PE indices and find that PE discount rates vary considerably. Net asset values are too smooth because they fail to reflect variation in discount rates. Although the CAPM alpha for our index is zero, the generalized public market equivalent based on cash flows is large and positive. We obtain similar results for a set of synthetic funds that invest in small cap stocks. Ignoring variation in PE discount rates can lead to a misallocation of capital.

We analyze the investment behavior of affiliated funds of mutual funds (AFoMFs), which are mutual funds that can only invest in other funds in the family, and are offered by most large families. Though never mentioned in any prospectus, we discover that AFoMFs provide an insurance pool against temporary liquidity shocks to other funds in the family. We show that, though the family benefits because funds can avoid fire sales, the cost of this insurance is borne by the investors in the AFoMFs. The paper thus uncovers some of the hidden complexities of fiduciary responsibility in mutual fund families.

We consider a competitive and perfect financial market in which agents have heterogeneous cash flow valuations. Instead of assuming that agents are endowed with rational expectations, we model their behavior as the product of adaptive learning. Our results demonstrate that adaptive learning affects security design profoundly, with securities mispriced even in the long run and optimal designs trading off underpricing against intrinsic value maximization. The evolutionary dominant security design calls for issuing securities that engender large losses with a small but positive probability, but that otherwise produce stable payoffs, almost the exact opposite of the pure state claims that are optimal in the rational expectations framework.

Binscatter is a popular method for visualizing bivariate relationships and conducting informal specification testing. We study the properties of this method formally and develop enhanced visualization and econometric binscatter tools. These include estimating conditional means with optimal binning and quantifying uncertainty. We also highlight a methodological problem related to covariate adjustment that can yield incorrect conclusions. We revisit two applications using our methodology and find substantially different results relative to those obtained using prior informal binscatter methods. General purpose software in Python, R, and Stata is provided. Our technical work is of independent interest for the nonparametric partition-based estimation literature.