Publications

We study a non-parametric multi-armed bandit problem with stochastic covariates, where a key complexity driver is the smoothness of payoff functions with respect to covariates. Previous studies have focused on deriving minimax-optimal algorithms…

Seminal studies show that naive lab participants accurately predict who wins real-world elections based solely on candidate photos. It is unclear what this implies for the health of democracy without knowing whether candidates who look more…

We elicit subjective probability distributions from business executives about their own-firm outcomes at a one-year look-ahead horizon. In terms of question design, our key innovation is to let survey respondents freely select support points and…

Two-sided matching platforms provide users with menus of match recommendations. To maximize the number of realized matches between the two sides (referred to herein as customers and suppliers), the platform must balance the inherent tension…

Stanford Latino Entrepreneurship Initiative surveyed 15,000 employer businesses in 2021 as part of its annual national survey to assess the current state of U.S. Latino entrepreneurship. We have compiled some of the most pressing insights about…

This paper proposes a method for estimating consumer preferences among discrete choices, where the consumer chooses at most one product in a category, but selects from multiple categories in parallel. The consumer’s utility is additive in the…

The 2020 U.S. election saw a record turnout, saw a huge increase in absentee voting, and brought unified national Democratic control — yet these facts alone do not imply that vote-by-mail increased turnout or benefited Democrats. Using new…

This chapter presents an overview of advances in the structural analysis of contracting in vertical markets over the past fifteen years. We provide a discussion of theoretical models of contracting and bargaining that form the…

We study whether and how creditors exercise their control rights to shape their borrowers’ executive compensation plans. Highly levered borrowers often face incentives to underinvest due to agency conflicts driven by differences in time horizon…

Many statistical estimands can expressed as continuous linear functionals of a conditional expectation function. This includes the average treatment effect under unconfoundedness and generalizations for continuous-valued and personalized…

Staggered boards (SBs) are one of the most potent common entrenchment devices, and their value effects are considerably debated. We study SBs’ effects on firm value, managerial behavior, and investor composition using a quasi‐experimental setting…

While improving prediction accuracy has been the focus of machine learning in recent years, this alone does not suffice for reliable decision-making. Deploying learning systems in consequential settings also requires calibrating and communicating…

We investigate how sociology students garner recognition from niche field audiences through specialization. Our dataset comprises over 80,000 sociology-related dissertations completed at U.S. universities, as well as data on graduates’ pursuant…

Motivated by recent initiatives to increase transparency in procurement, we study the effects of disclosing information about previous purchases in a setting where an organization delegates its purchasing decisions to its employees. When…

Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes. Typically, different scientists test different intervention ideas in different samples using different outcomes over…

Despite growing antibiotic resistance, the clinical drug development pipeline for antibiotics has been sparse largely because of an unsustainable business model. We illustrate three models to accelerate antibiotic development, using Medicare new…

Randomized experiments have become important tools in empirical research. In a completely randomized treatment-control experiment, the simple difference in means of the outcome is un-biased for the average treatment effect, and covariate…

We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference-in-differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this…