Working Papers

Income differences across US cities are well documented, but little is known about the level of standard of living in each city — defined as the amount of market-based consumption that residents are able to afford. In this paper we provide…

I incorporate computational constraints into decision theory in order to capture how cognitive limitations affect behavior. I impose an axiom of computational tractability that only rules out behaviors that are thought to be fundamentally hard. I…

We study the hierarchy of communities in real-world networks under a generic stochastic block model, in which the connection probabilities are structured in a binary tree. Under such model, a standard recursive bi-partitioning algorithm is…

We estimate a measure of segregation, experienced isolation, that captures individuals’ exposure to diverse others in the places they visit over the course of their days. Using Global Positioning System (GPS) data collected from smartphones, we…

I propose a new approach to mechanism design: rather than assume a common prior belief, assume access to a common dataset. I restrict attention to incomplete information games where a designer commits to a policy and a single agent responds. I…

We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick tailed, where treatment effects are small, where sample sizes are large and where assignment is completely…

Interest rate caps are widespread in consumer credit markets, yet there is limited evidence on their effects on market outcomes and welfare. The effects of this policy are ambiguous and depend on a trade-off between consumer protection…

Long-acting reversible contraceptives are highly effective in preventing unintended pregnancies, but take-up remains low. This paper analyzes a randomized controlled trial of interventions addressing two barriers to long-acting reversible…

Empirical models play a distinctive role in the study of matching markets. They provide a quantitative framework for measuring heterogeneity in preferences for schools (Hastings et al., 2009), comparing school assignment mechanisms (…

Analyzing observational data from multiple sources can be useful for increasing statistical power to detect a treatment effect; however, practical constraints such as privacy considerations may restrict individual-level information sharing across…

Banks’ reluctance to repair their balance sheets, combined with deposit insurance and regulatory forbearance in recognizing greater risks and losses, can lead to solvency problems that look like liquidity (bank-run) crises. Regulatory forbearance…

New technologies have enabled firms to elicit granular behavioral data from consumers in exchange for lower prices and better experiences. This data can mitigate asymmetric information and moral hazard, but it may also increase firms’ market…

Overlap in baseline covariates between treated and control groups, also known as positivity or common support, is a common assumption in observational causal inference. Assessing this assumption is often ad hoc, however, and can give misleading…

We propose a new estimator for the average causal effects of a binary treatment with panel data in settings with general treatment patterns. Our approach augments the twoway-fixed-effects specification with the unit-specific weights that arise…

We study a prominent energy regulation affecting large Chinese manufacturers that are part of broader conglomerates. Using detailed firm-level data and difference-in-differences research designs, we show that regulated firms cut output and…

We study the problem of model selection for contextual bandits, in which the algorithm must balance the bias-variance trade-off for model estimation while also balancing the exploration-exploitation trade-off. In this paper, we propose the first…

We propose a new diffusion-asymptotic analysis for sequentially randomized experiments, including those that arise in solving multi-armed bandit problems. In an experiment with n time steps, we let the mean reward gaps between actions…

It has become increasingly common for data to be collected adaptively, for example using contextual bandits. Historical data of this type can be used to evaluate other treatment assignment policies to guide future innovation or experiments.…

COVID-19 drove a mass social experiment in working from home. We survey more than 30,000 Americans over multiple waves to investigate whether WFH will stick, and why. Our data say that 20 percent of full workdays will be supplied from home after…

Individuals face non-linear budget constraints in myriad situations. We test a fundamental assumption of economic analysis in such settings: that individuals display stable preferences when facing linear and non-linear incentives. We use a…