399 citations · 407 across the 9 of their papers we have counts for
14 papers
Fast Algorithms for the Quantile Regression Process
Victor Chernozhukov, Iván Fernández-Val, Blaise Melly
The widespread use of quantile regression methods depends crucially on the existence of fast algorithms. Despite numerous algorithmic improvements, the computation time is still no…
SortedEffects: Sorted Causal Effects in R
Shuowen Chen, Victor Chernozhukov, Iván Fernández-Val +1
Chernozhukov et al. (2018) proposed the sorted effect method for nonlinear regression models. This method consists of reporting percentiles of the partial effects in addition to th…
Mastering Panel 'Metrics: Causal Impact of Democracy on Growth
Shuowen Chen, Victor Chernozhukov, Iván Fernández-Val
The relationship between democracy and economic growth is of long-standing interest. We revisit the panel data analysis of this relationship by Acemoglu, Naidu, Restrepo and Robins…
Selection and the Distribution of Female Hourly Wages in the U.S
Iván Fernández-Val, Franco Peracchi, Aico van Vuuren +1
We analyze the role of selection bias in generating the changes in the observed distribution of female hourly wages in the United States using CPS data for the years 1975 to 2020.…
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
Victor Chernozhukov, Iván Fernández-Val, Siyi Luo
We develop a distribution regression model under endogenous sample selection. This model is a semi-parametric generalization of the Heckman selection model. It accommodates much ri…
Shape-Enforcing Operators for Point and Interval Estimators
Xi Chen, Victor Chernozhukov, Iván Fernández-Val +2
A common problem in econometrics, statistics, and machine learning is to estimate and make inference on functions that satisfy shape restrictions. For example, distribution functio…
Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models
Victor Chernozhukov, Iván Fernández-Val, Whitney Newey +2
Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships. However,…
Fixed Effect Estimation of Large T Panel Data Models
Iván Fernández-Val, Martin Weidner
This article reviews recent advances in fixed effect estimation of panel data models for long panels, where the number of time periods is relatively large. We focus on semiparametr…
Nonseparable Multinomial Choice Models in Cross-Section and Panel Data
Victor Chernozhukov, Iván Fernández-Val, Whitney Newey
Multinomial choice models are fundamental for empirical modeling of economic choices among discrete alternatives. We analyze identification of binary and multinomial choice models…
Extremal Quantile Regression: An Overview
Victor Chernozhukov, Iván Fernández-Val, Tetsuya Kaji
Extremal quantile regression, i.e. quantile regression applied to the tails of the conditional distribution, counts with an increasing number of economic and financial applications…
quantreg.nonpar: An R Package for Performing Nonparametric Series Quantile Regression
Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov +1
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point…
Counterfactual: An R Package for Counterfactual Analysis
Mingli Chen, Victor Chernozhukov, Iván Fernández-Val +1
The Counterfactual package implements the estimation and inference methods of Chernozhukov, Fernández-Val and Melly (2013) for counterfactual analysis. The counterfactual distribut…
Generic Inference on Quantile and Quantile Effect Functions for Discrete Outcomes
Victor Chernozhukov, Iván Fernández-Val, Blaise Melly +1
Quantile and quantile effect functions are important tools for descriptive and causal analyses due to their natural and intuitive interpretation. Existing inference methods for the…
Program Evaluation and Causal Inference with High-Dimensional Data
Alexandre Belloni, Victor Chernozhukov, Ivan Fernández-Val +1
In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (L…