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06/21/2023
Estimating the Value of Evidence-Based Decision Making
Business/policy decisions are often based on evidence from randomized ex...
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05/01/2023
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
Motivated by a recent literature on the double-descent phenomenon in mac...
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02/15/2022
Long-term Causal Inference Under Persistent Confounding via Data Combination
We study the identification and estimation of long-term treatment effect...
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12/09/2021
Covariate Balancing Sensitivity Analysis for Extrapolating Randomized Trials across Locations
The ability to generalize experimental results from randomized control t...
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12/01/2021
Synthetic Design: An Optimization Approach to Experimental Design with Synthetic Controls
We investigate the optimal design of experimental studies that have pre-...
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08/09/2021
Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models
We develop a new approach for identifying and estimating average causal ...
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07/26/2021
Efficient Treatment Effect Estimation in Observational Studies under Heterogeneous Partial Interference
In many observational studies in social science and medical applications...
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01/23/2021
A Design-Based Perspective on Synthetic Control Methods
Since their introduction in Abadie and Gardeazabal (2003), Synthetic Con...
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06/17/2020
Combining Experimental and Observational Data to Estimate Treatment Effects on Long Term Outcomes
There has been an increase in interest in experimental evaluations to es...
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02/04/2020
Decoupling Learning Rates Using Empirical Bayes Priors
In this work, we propose an Empirical Bayes approach to decouple the lea...
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11/09/2019
Optimal Experimental Design for Staggered Rollouts
Experimentation has become an increasingly prevalent tool for guiding po...
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09/05/2019
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations
Researchers often use artificial data to assess the performance of new e...
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03/24/2019
Machine Learning Methods Economists Should Know About
We discuss the relevance of the recent Machine Learning (ML) literature ...
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12/15/2018
Balanced Linear Contextual Bandits
Contextual bandit algorithms are sensitive to the estimation method of t...
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08/15/2018
Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption
In this paper we study estimation of and inference for average treatment...
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07/08/2018
A Causal Bootstrap
The bootstrap, introduced by Efron (1982), has become a very popular met...
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07/05/2018
The Role of the Propensity Score in Fixed Effect Models
We develop a new approach for estimating average treatment effects in th...
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11/19/2017
Estimation Considerations in Contextual Bandits
Contextual bandit algorithms seek to learn a personalized treatment assi...
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10/27/2017
Matrix Completion Methods for Causal Panel Data Models
In this paper we develop new methods for estimating causal effects in se...
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03/30/2016
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
Estimating the long-term effects of treatments is of interest in many fi...
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04/05/2015