723 citations · 5.4k across the 110 of their papers we have counts for
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Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks
Victor Chernozhukov, Ivan Fernandez-Val
Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of a…
Intersection Bounds: Estimation and Inference
Victor Chernozhukov, Sokbae Lee, Adam M. Rosen
We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or…
Posterior Inference in Curved Exponential Families under Increasing Dimensions
Alexandre Belloni, Victor Chernozhukov
This work studies the large sample properties of the posterior-based inference in the curved exponential family under increasing dimension. The curved structure arises from the imp…
L1-Penalized Quantile Regression in High-Dimensional Sparse Models
Alexandre Belloni, Victor Chernozhukov
We consider median regression and, more generally, a possibly infinite collection of quantile regressions in high-dimensional sparse models. In these models the overall number of r…
Average and Quantile Effects in Nonseparable Panel Models
Victor Chernozhukov, Ivan Fernandez-Val, Jinyong Hahn +1
Nonseparable panel models are important in a variety of economic settings, including discrete choice. This paper gives identification and estimation results for nonseparable models…
Inference on Counterfactual Distributions
Victor Chernozhukov, Ivan Fernandez-Val, Blaise Melly
Counterfactual distributions are important ingredients for policy analysis and decomposition analysis in empirical economics. In this article we develop modeling and inference tool…