4 papers · 1 filter
Linear Estimation of Structural and Causal Effects for Nonseparable Panel Data
Victor Chernozhukov, Ben Deaner, Ying Gao +2
This paper develops linear estimators for structural and causal parameters of nonseparable models using panel data. These models incorporate unobserved, time-varying, individual he…
Inferring Treatment Effects in Large Panels by Uncovering Latent Similarities
Ben Deaner, Chen-Wei Hsiang, Andrei Zeleneev
The presence of unobserved confounders is one of the main challenges in identifying treatment effects. In this paper, we propose a new approach to causal inference using panel data…
Many Proxy Controls
Ben Deaner
A recent literature considers causal inference using noisy proxies for unobserved confounding factors. The proxies are divided into two sets that are independent conditional on the…
Approximation-Robust Inference in Dynamic Discrete Choice
Ben Deaner
Estimation and inference in dynamic discrete choice models often relies on approximation to lower the computational burden of dynamic programming. Unfortunately, the use of approxi…