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.

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.

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.

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.

We exploit the information content of option prices to construct a novel measure of bank tail risk. We document a persistent increase in tail risk for the U.S. banking industry following the global financial crisis, except for banks designated as systemically important by the Dodd–Frank Act. We show that this post-crisis difference in tail risk for large and small banks is consistent with the too-big-to-fail (TBTF) status of large banks being reinforced by the Dodd–Frank designation: Naming the banks whose failure could threaten the financial stability of the U.S. gave investors a list of banks the government deemed as TBTF.

We develop a theory of trust in lending that distinguishes between reputation and trust. Banks emerge as more trusted lenders than non-banks. We show that trust severs the link between performance and the cost and availability of financing for lenders, but trust can be lost and is difficult to regain. Banks survive an erosion of trust better than non-banks. Banks' trust advantage arises from the lower cost of funding due to insured deposits and an endogenous belief revision channel that complements the effect of the funding cost advantage. The results have novel policy relevance for deposit insurance scope.

The US Securities and Exchange Commission’s mandated CEO pay ratio is a simple, but salient, metric that could resonate with employees given it focuses on their compensation. Reporting a relatively or surprisingly high ratio reduces employee perceptions of their pay, views of the CEO, and hampers productivity growth. Employee pay satisfaction drops after disclosing a high ratio even if their wages were previously disclosed and when the pay ratio disclosure adds little new information. Disclosures by firms with a high ratio contain more discretionary language to explain the ratio or portray employee relations positively and are more likely to be covered by the media. However, neither information source substantially alters the employee response to a salient ratio. Our work illustrates that requiring firms to disclose a salient metric can have unintended consequences on employees and suggests caution in requiring firms to report simplified Environmental, Social, and Governance (ESG) metrics that are inherently multifaceted.

We find that male participants in Harvard Business School’s New Venture Competition who were randomly exposed to more venture capital (VC) investors on their panel were substantially more likely to start a VC-backed startup post-graduation, indicating that access to investors impacts fundraising independent of the quality of ideas. However, female participants experience no benefit from exposure to male or female venture capitalists (VCs), which appears related to a reduced propensity to reach out to VCs to whom they were exposed. Our results therefore also demonstrate gender-based differences in the degree to which increased exposure to investors can address networking frictions in venture capital.