Browse or search publications from faculty affiliated with the lab.
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations
When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods…
CAREER: A Foundation Model for Labor Sequence Data
Labor economists regularly analyze employment data by fitting predictive models to small, carefully constructed longitudinal survey datasets.…
Digital Interventions and Habit Formation in Educational Technology
We evaluate a contest-based intervention intended to increase the usage of an educational app that helps children in India learn to read English.…
Impact Matters for Giving at Checkout
We conducted two experiments on PayPal’s Give at Checkout feature to learn about the effect of 1) information about charity outcomes on donations…
Optimal Experimental Design for Staggered Rollouts
In this paper, we study the design and analysis of experiments conducted on a set of units over multiple time periods where the starting time of…
Can Personalized Digital Counseling Improve Consumer Search for Modern Contraceptive Methods?
This paper analyzes a randomized controlled trial of a personalized digital counseling intervention addressing informational constraints and…
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
In many settings, interventions may be more effective for some individuals than others, so that targeting interventions may be beneficial. We…
Policy Learning with Adaptively Collected Data
In a wide variety of applications, including healthcare, bidding in first price auctions, digital recommendations, and online education, it can be…
Federated Causal Inference in Heterogeneous Observational Data
We are interested in estimating the effect of a treatment applied to individuals at multiple sites, where data is stored locally for each site.…
Machine-Learning-Based High-Benefit Approach versus Conventional High-Risk Approach in Blood Pressure Management
In medicine, clinicians treat individuals under an implicit assumption that high-risk patients would benefit most from the treatment (‘high-risk…
Semiparametric Estimation of Treatment Effects in Randomized Experiments
We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick tailed…
The Heterogeneous Earnings Impact of Job Loss Across Workers, Establishments, and Markets
Using generalized random forests and rich Swedish administrative data, we show that the earnings effects of job displacement due to establishment…
Flexible and Efficient Contextual Bandits with Heterogeneous Treatment Effect Oracles
Contextual bandit algorithms often estimate reward models to inform decision-making. However, true rewards can contain action-independent…
Smiles in Profiles: Improving Fairness and Efficiency Using Estimates of User Preferences in Online Marketplaces
Online platforms often face challenges being both fair (i.e., non-discriminatory) and efficient (i.e., maximizing revenue). Using computer vision…
Uncovering Interpretable Potential Confounders in Electronic Medical Records
Randomized clinical trials (RCT) are the gold standard for informing treatment decisions. Observational studies are often plagued by selection…
Stable Learning Establishes Some Common Ground between Causal Inference and Machine Learning
Causal inference has recently attracted substantial attention in the machine learning and artificial intelligence community. It is usually…
Counterfactual Inference for Consumer Choice Across Many Product Categories
This paper proposes a method for estimating consumer preferences among discrete choices, where the consumer chooses at most one product in a…
Estimating Experienced Racial Segregation in U.S. Cities Using Large-Scale GPS Data
We estimate a measure of segregation, experienced isolation, that captures individuals’ exposure to diverse others in the places they visit over…
Semiparametric Estimation of Treatment Effects in Randomized Experiments
We develop new semiparametric methods for estimating treatment effects. We focus on a setting where the outcome distributions may be thick tailed…
Shared Decision-Making: Can Improved Counseling Increase Willingness to Pay for Modern Contraceptives?
Long-acting reversible contraceptives are highly effective in preventing unintended pregnancies, but take-up remains low. This paper analyzes a…
Ten Rules for Conducting Retrospective Pharmacoepidemiological Analyses: Example COVID-19 Study
Since the beginning of the COVID-19 pandemic, pharmaceutical treatment hypotheses have abounded, each requiring careful evaluation. A randomized…
Breiman’s Two Cultures: A Perspective from Econometrics
Breiman’s “Two Cultures” paper painted a picture of two disciplines, data modeling, and algorithmic machine learning, both engaged in the analyses…
Alpha-1 Adrenergic Receptor Antagonists to Prevent Hyperinflammation and Death from Lower Respiratory Tract Infection
In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation,…
Optimal Model Selection in Contextual Bandits with Many Classes via Offline Oracles
We study the problem of model selection for contextual bandits, in which the algorithm must balance the bias-variance trade-off for model…