This study examines the capital-market effects of tipper-tippee insider trading laws. To do so, I exploit the unexpected decision issued by the Court of Appeals for the Second Circuit in U.S. v. Newman 773 F.3d 438, which reduced legal jeopardy for Second Circuit-based market participants prior to being overturned. Consistent with Newman constraining insider trading enforcement, I find strong evidence of plausible insider trading in the Second Circuit following the ruling. I also document a substantial reduction in general trading activity in Second Circuit stocks, as well as an increase in daily quoted spreads and the price impact of trading. These findings are consistent with unchecked insider trading increasing transaction costs and crowding-out investors. In total, my results show that tipper-tippee insider trading restrictions play an important role in bolstering market integrity, and that market participants can to some degree counteract insider trading when public regulation is constrained.

Andrew T. Levin of Dartmouth College and NBER reviews “Monetary Policy and Its Unintended Consequences” by Raghuram Rajan. The EconLit abstract of this book begins: “Details how monetary adventurism can have unintended effects and promotes policy that is moderate and focused on combating high inflation and financial instability.”

This paper offers the first study of how changes in corporate R&D investment affect labor mobility. We show that increases in R&D spur employee departures to join start-ups’ founding teams. This appears to reflect employees taking the ideas, skills, or technologies created through the R&D process but not especially valuable to the R&D-investing firm to start-ups. The employee-founded start-ups tend to be outside the R&D-investing employer’s industry, suggesting that the underlying ideas would impose diversification costs on the R&D-investing firm. The start-ups are more likely to be VC backed, high tech, and high wage, pointing to substantial spillover benefits.

This paper obtains comparable estimates of the effect of unemployment insurance (UI) benefits on labor supply throughout the unemployment spell and over the business cycle using a regression kink design and 20 years of administrative data from California. For a given unemployment duration, the behavioral effect of UI benefit levels on labor supply does not vary with the business cycle from 2002 to 2019. However, due to increased coverage from extensions in benefit durations, the duration elasticity of UI benefits rises during recessions. The behavioral effect during the start of the COVID-19 pandemic is substantially lower at all unemployment durations.

We examine identification of differentiated products demand when one has “micro data” linking the characteristics and choices of individual consumers. Our model nests standard specifications featuring rich observed and unobserved consumer heterogeneity as well as product/market‐level unobservables that introduce the problem of econometric endogeneity. Previous work establishes identification of such models using market‐level data and instruments for all prices and quantities. Micro data provides a panel structure that facilitates richer demand specifications and reduces requirements on both the number and types of instrumental variables. We address identification of demand in the standard case in which nonprice product characteristics are assumed exogenous, but also cover identification of demand elasticities and other key features when these product characteristics are endogenous and not instrumented. We discuss implications of these results for applied work.

Online university courses have become common, though some question whether the modality can adequately substitute for an in-person experience. We explore online course enrollment and student outcomes at a large public 4-year system. Online enrollment nearly doubled from 2012 to 2019. Female students and older students were especially likely to take online classes. Students earned more As and Fs in online courses, but semester grade point averages were higher in terms when students took at least one class online. Importantly, taking higher shares of courses online was associated with increased degree completion, with the largest benefits for younger students and male students.

The money metric utility function is an essential tool for calculating welfare-relevant growth and inflation. We show how to recover it from repeated cross-sectional data without making parametric assumptions about preferences. We do this by solving the following recursive problem. Given compensated demand, we construct money metric utility by integration. Given money metric utility, we construct compensated demand by matching households over time whose money metric utility value is the same. We illustrate our method using household consumption survey data from the United Kingdom from 1974 to 2017 and find that real consumption calculated using official aggregate inflation statistics overstates money metric utility in 1974 pounds for the poorest households by around 0.5% a year and understates it by around a third of a percentage point per year for the richest households. We extend our method to allow for missing or mismeasured prices, assuming preferences are separable between goods with well-measured prices and the rest. We discuss how our results change if the prices of some service sectors are mismeasured.

Little is known about how the SEC selects its targets for investigation. We study this subject using a new database of formal SEC investigations. We predict and find that case selection is associated with a firm's (i) likelihood of regulatory noncompliance, (ii) exposure to private sector scrutiny, and (iii) conspicuous public trigger events. The relationship between investigations and regulatory noncompliance and private sector scrutiny preferences is sensitive to SEC constraints, whereas the relationship with triggers is not. We also examine the association between investigation motives and enforcement actions, an important SEC outcome reported to Congress. While regulatory noncompliance-motivated and public trigger-motivated investigations are more likely to result in public charges, specifically when the SEC is constrained, private sector scrutiny-motivated investigations are less likely to result in public charges. Finally, investigation rates of potential targets are associated with the career trajectories of SEC personnel, while investigation outcomes are not.

We extend Jin and Myers’s (2006) model to derive the relation between stock price crash risk and operating leverage (i.e., the fraction of fixed costs in total costs). The model predicts that (1) firms’ operating leverage decreases as stock price crash risk increases and (2) the negative effect of crash risk on operating leverage is more pronounced when firms are closer to the crash threshold or when managers face higher costs of stock price crashes. We empirically test the model predictions using a large sample of manufacturing firms in the US and find consistent results. Further analysis shows that higher levels of crash risk lead to a less sticky cost behavior. In addition, crash risk–driven operating deleveraging effectively reduces stock return volatility and enhances operating performance in subsequent years. Collectively, our findings reveal that crash-prone firms adopt a more flexible cost structure to delay stock price crashes and mitigate adverse outcomes.

We examine how firms respond to requests for enhanced disclosure that we make on an online investor platform. Exploiting variation in firms' customer and supplier disclosures, we ask a randomized set of non-disclosing firms to provide information on their customers' and suppliers' identities. We find that the firms' probability of disclosure depends on the basis we give for the demand—requests appealing to disclosure's usefulness to investors lead to more frequent disclosure, while those appealing to regulators' preference for disclosure lead to less frequent disclosure. The requests we make on the platform lead to more frequent customer- and supplier-related inquiries from other platform users. We also find that the treatment firms' disclosure of customer and supplier information improves in the next period's regulatory filings. The findings suggest that investor platforms can enhance corporate transparency by increasing retail investors' ability to demand information.