Browse or search publications from faculty affiliated with the lab.
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…
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Many scientific and engineering challenges—ranging from personalized medicine to customized marketing recommendations—require an understanding of…
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data
We estimate a model of consumer choices over restaurants using data from several thousand anonymous mobile phone users. Restaurants have latent…
Stable Predictions across Unknown Environments
In many important machine learning applications, the training distribution used to learn a probabilistic classifier differs from the testing…
Exact P-values for Network Interference
We study the calculation of exact p-values for a large class of non-sharp null hypotheses about treatment effects in a setting with data from…
Sampling-Based vs. Design-Based Uncertainty in Regression Analysis
Previously titled: Finite Population Causal Standard Errors
Consider a researcher estimating the parameters of a regression…
Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges
There is a large literature on semiparametric estimation of average treatment effects under unconfounded treatment assignment in settings with a…
Beyond Prediction: Using Big Data for Policy Problems
Machine-learning prediction methods have been extremely productive in applications ranging from medicine to allocating fire and health inspectors…
Context Selection for Embedding Models
Word embeddings are an effective tool to analyze language. They have been recently extended to model other types of data beyond text, such as…
Matrix Completion Methods for Causal Panel Data Models
In this paper we develop new methods for estimating causal effects in settings with panel data, where a subset of units are exposed to a…
Structured Embedding Models for Grouped Data
Word embeddings are a powerful approach for analyzing language, and exponential family embeddings (EFE) extend them to other types of data. Here…