Browse or search publications from faculty affiliated with the lab.
Design-based Analysis in Difference-in-Differences Settings with Staggered Adoption
In this paper we study estimation of and inference for average treatment effects in a setting with panel data. We focus on the setting where units…
The Association between Alpha-1 Adrenergic Receptor Antagonists and In-Hospital Mortality from COVID-19
Effective therapies for coronavirus disease 2019 (COVID-19) are urgently needed, and pre-clinical data suggest alpha-1 adrenergic receptor…
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…
Practitioner’s Guide: Designing Adaptive Experiments
Adaptive experiments present a unique opportunity to more rapidly learn which of many treatments work best, evaluate multiple hypotheses, and…
Uncovering Interpretable Potential Confounders in Electronic Medical Records
In medicine, randomized clinical trials are the gold standard for informing treatment decisions. Observational comparative effectiveness research…
Association of α1-Blocker Receipt With 30-Day Mortality and Risk of Intensive Care Unit Admission Among Adults Hospitalized With Influenza or Pneumonia in Denmark
Alpha 1–adrenergic receptor blocking agents (α1-blockers) have been reported to have protective benefits against hyperinflammation and cytokine…
Policy Learning with Observational Data
In many areas, practitioners seek to use observational data to learn a treatment assignment policy that satisfies application-specific…
Local Linear Forests
Random forests are a powerful method for non-parametric regression, but are limited in their ability to fit smooth signals. Taking the perspective…
Generic Drug Repurposing for Public Health and National Security: COVID-19 and Beyond
The novel disease caused by the SARS-CoV-2 virus (COVID-19) has been a shock to both our health and wealth, with more than 276,000 dead in the U.S…
A How-To Guide for Conducting Retrospective Analyses: Example COVID-19 Study
In the urgent setting of the COVID-19 pandemic, treatment hypotheses abound, each of which requires careful evaluation. A randomized controlled…
Alpha-1 Adrenergic Receptor Antagonists for Preventing Acute Respiratory Distress Syndrome and Death from Cytokine Storm Syndrome
In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation (‘…
Combining Experimental and Observational Data to Estimate Treatment Effects on Long Term Outcomes
There has been an increase in interest in experimental evaluations to estimate causal effects, partly because their internal validity tends to be…
policytree: Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
The problem of learning treatment assignment policies from randomized or observational data arises in many fields. For example, in personalized…
The Allocation of Decision Authority to Human and Artificial Intelligence
The allocation of decision authority by a principal to either a human agent or an artificial intelligence is examined. The principal trades off an…
Stable Prediction with Model Misspecification and Agnostic Distribution Shift
For many machine learning algorithms, two main assumptions are required to guarantee performance. One is that the test data are drawn from the…
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements
We develop SHOPPER, a sequential probabilistic model of shopping data. SHOPPER uses interpretable components to model the forces that drive how a…
Economists (and Economics) in Tech Companies
As technology platforms have created new markets and new ways of acquiring information, economists have come to play an increasingly central role…
Service Quality in the Gig Economy: Empirical Evidence about Driving Quality at Uber
The rise of marketplaces for goods and services has led to changes in the mechanisms used to ensure high quality. We analyze this phenomenon in…
Sufficient Representations for Categorical Variables
Many learning algorithms require categorical data to be transformed into real vectors before it can be used as input. Often, categorical…
Balanced Linear Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of the outcome model as well as the exploration method used, particularly in…
Synthetic Difference in Differences
We present a new perspective on the Synthetic Control (SC) method as a weighted least squares regression estimator with time fixed effects…
Generalized Random Forests
We propose generalized random forests, a method for nonparametric statistical estimation based on random forests (Breiman [Mach. Learn. …
Estimation Considerations in Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of the outcome model as well as the exploration method used,…
Offline Multi-Action Policy Learning: Generalization and Optimization
In many settings, a decision-maker wishes to learn a rule, or policy, that maps from observable characteristics of an individual to an action.…