1.6k citations · 2.1k across the 53 of their papers we have counts for
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Peer Encouragement Designs in Causal Inference with Partial Interference and Identification of Local Average Network Effects
Hyunseung Kang, Guido Imbens
In non-network settings, encouragement designs have been widely used to analyze causal effects of a treatment, policy, or intervention on an outcome of interest when randomizing th…
The State of Applied Econometrics - Causality and Policy Evaluation
Susan Athey, Guido Imbens
In this paper we discuss recent developments in econometrics that we view as important for empirical researchers working on policy evaluation questions. We focus on three main area…
The Econometrics of Randomized Experiments
Susan Athey, Guido Imbens
In this review, we present econometric and statistical methods for analyzing randomized experiments. For basic experiments we stress randomization-based inference as opposed to sam…
Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions
Susan Athey, Guido W. Imbens, Stefan Wager
There are many settings where researchers are interested in estimating average treatment effects and are willing to rely on the unconfoundedness assumption, which requires that the…
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index
Susan Athey, Raj Chetty, Guido Imbens +1
Estimating the long-term effects of treatments is of interest in many fields. A common challenge in estimating such treatment effects is that long-term outcomes are unobserved in t…