Decision Making & Negotiations

We study how small and medium enterprise (SME) lenders react to information about their competitors’ contracting decisions. To isolate this learning from lenders’ common reactions to unobserved shocks to fundamentals, we exploit the staggered entry of lenders into an information-sharing platform. Upon entering, lenders adjust their contract terms toward what others offer. This reaction is mediated by the distribution of market shares: lenders with higher shares or that operate in concentrated markets react less.

We study the effects of evaluating asset managers against a benchmark on corporate decisions, e.g., investments, M&A, and IPOs. We introduce asset managers into an otherwise standard model and show that firms inside the benchmark are effectively subsidized by the asset managers. This “benchmark inclusion subsidy” arises because asset managers have incentives to hold some of the equity of firms in the benchmark regardless of their risk characteristics. Due to the benchmark inclusion subsidy, a firm inside the benchmark values an investment project more than the one outside.

We designed and fielded a survey of New York and Pennsylvania firms to study the impacts of New York's 2018 Paid Family Leave policy on employer outcomes. We match each NY firm to a comparable PA firm and use difference-in-difference models to analyze within-match-pair changes in outcomes. We find that PFL leads to an improvement in employers' rating of their ease of handling long employee absences, concentrated in the first policy year and among firms with 50-99 employees. We also find an increase in employee leave-taking in the second policy year, driven by smaller firms.

We construct a new measure of voluntary disclosure based on firms’ websites. Using the Wayback Machine, we create a standardized measure of disclosure capturing the quantity of information on firms’ websites. We validate our measure by documenting that it is positively associated with established measures of firms’ voluntary disclosure and liquidity. Importantly, we document that our measure, while correlated with established disclosure measures, is not subsumed by those measures. It complements existing measures in three important ways.

We study the classical newsvendor problem in which the decision-maker must trade-off underage and overage costs. In contrast to the typical setting, we assume that the decision-maker does not know the underlying distribution driving uncertainty but has only access to historical data. In turn, the key questions are how to map existing data to a decision and what type of performance to expect as a function of the data size.

Using high-frequency transaction-level income, spending, balances, and credit limits data from an online financial service, we show that many consumers fail to stick to their self-set debt paydown plans and argue that this behavior is best explained by a model of present bias. Theoretically, we show that (i) a present-biased agent's sensitivity of consumption spending to paycheck receipt reflects his or her short-run impatience and that (ii) this sensitivity varies with available resources only for agents who are aware (sophisticated) rather than unaware (naive) of their future impatience.

The use of order flow information by financial firms has come to the forefront of the regulatory debate. A central question is: Should a dealer who acquires information by taking client orders be allowed to use or share that information? We explore how information sharing affects dealers, clients and issuer revenues in U.S. Treasury auctions. Because one cannot observe alternative information regimes, we build a model, calibrate it to auction results data, and use it to quantify counter-factuals. The model's key force is that sharing information reduces uncertainty about future value.

We study the problems of offline and online contextual optimization with feedback information, where instead of observing the loss, we observe, after-the-fact, the optimal action an oracle with full knowledge of the objective function would have taken. We aim to minimize regret, which is defined as the difference between our losses and the ones incurred by an all-knowing oracle.

Expectations Investing offers a unique and powerful alternative for identifying value-price gaps. Rappaport and Mauboussin provide everything the reader needs to utilize the discounted cash flow model successfully. And they add an important twist: they suggest that rather than forecasting cash flows, investors should begin by estimating the expectations embedded in a company's stock price. An investor who has a fix on the market's expectations can then assess the likelihood of expectations revisions.