Knowledge that Transforms

I examine how the use of sales performance measures in CEO incentive contracts affects the operations of a firm and its suppliers. A growing number of firms are evaluating and compensating their CEOs based on sales performance. However, because sales performance measures are narrow measures that do not incentivize cost control, they can influence operational decisions that affect not only the firm but also its suppliers. I show that the use of sales performance measures in CEO bonus contracts is associated with inventory fluctuations that increase the bullwhip effect, a phenomenon in which a firm exhibits greater volatility in production than in demand, thereby increasing the order volatility faced by its suppliers. Instrumental variable tests using the firm’s network connections through compensation consultants mitigate concerns that the results are driven by omitted factors. Collectively, my findings illuminate spillover effects of CEO incentive contracts on economically linked firms. Data Availability: Data are available from the sources cited in the text.

I propose a mechanism through which institutional investors’ correlated demand shocks provide a source of market risk in asset pricing. Institutional investors have mandates to beat a similar market index. During periods of strong stock market performance, their incentive to outperform intensifies as more of them fall short of the market index. This incentive induces procyclical risk-taking behavior, generating correlated demand that elevates the market betas and risk premia of exposed stocks. Quasi-experiments using exogenous changes in index membership support a causal interpretation of the mechanism. Elevated betas are associated with a higher perceived cost of capital and reduced firm investment.

This paper analytically and empirically investigates managerial investment responses to negative shocks in firm value. In the model, managers are privately informed about the shocks’ persistence, and those facing transitory shocks strategically underinvest to boost earnings and signal financial strength to investors. The model also predicts counter-signaling: firms with strong fundamentals do not need to cut investment to convey strength. We exploit the 2003 mutual fund trading scandal as a plausibly exogenous source of price pressure. Consistent with signaling, we find that firms with greater tainted-fund ownership are more likely to meet or narrowly beat analyst forecasts by cutting R&D, and that this behavior is associated with more favorable earnings announcement returns and better long-run performance. Consistent with counter-signaling, these firms are less likely to cut R&D when they beat analyst forecasts by a wide margin. Cross-sectional tests also support the model’s comparative statics. Data Availability: All data used in the study are publicly available from the sources cited in the text.

We examine how strengthened anti-money laundering (AML) enforcement affects the U.S. banking sector. Heightened enforcement disproportionately raises compliance costs for small banks, especially in counties more exposed to money laundering. In these areas, small banks contract while large banks expand, increasing standardized, government-supported, and secured lending. While aggregate county-level credit does not decline differentially, local outcomes improve. Small establishments grow, non-tradable employment and wages rise, and real estate prices increase. The evidence is consistent with a reallocation mechanism in which AML enforcement shifts activity toward large banks, potentially improving intermediation quality through changes in the composition of local financial intermediation.

The advent of large language models (LLMs) creates new opportunities to conduct qualitative interviews at scale, with thousands of respondents, thereby bridging qualitative and quantitative methods. We develop a simple, versatile approach for researchers to run AI-led qualitative interviews, including voice interviews. We assess its robustness by drawing comparisons to human experts and with several respondents-based quality metrics. The versatility of the approach is illustrated through four broad classes of applications: eliciting key factors in decision making, political views, subjective mental states, and mental models of the effects of public policies. High performance ratings are obtained in all of these domains. Our applications highlight the potential of AI-led interviews as a tool for measurement, hypothesis generation, and discovering mechanisms.

We examine whether PCAOB inspection deficiencies related to management review controls (MRCs) affect financial reporting decisions. Using the goodwill impairment setting, we find that firms are more likely to record goodwill impairments when their auditors have received more PCAOB inspection deficiencies related to goodwill MRCs. The association is stronger when inspection deficiencies are more likely to lead to changes to the design or implementation of an internal control (repeat deficiencies and deficiencies related to MRC precision). We observe some evidence that MRC inspection deficiencies increase the likelihood of goodwill impairment even when unrelated to goodwill, indicating that improving the audit of MRCs can broadly affect financial reporting. Our findings provide evidence that PCAOB inspections affect not only auditor behavior but also the financial reporting behavior of audit clients. Specifically, inspection feedback appears to influence reporting outcomes through changes in the audit and evaluation of MRCs, identifying a channel through which regulatory oversight affects issuers. The results have implications for audit firms seeking to remediate inspection deficiencies, for management and audit committees responsible for overseeing significant estimates and impairment analyses, and for regulators evaluating the broader effectiveness of the PCAOB inspection process.