
A Response to Philippe Lemoine's Critique on our Paper "Causal Impact of Masks, Policies, Behavior on Early Covid19 Pandemic in the U.S."
Recently, Phillippe Lemoine posted a critique of our paper "Causal Impac...
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RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Many causal and policy effects of interest are defined by linear functio...
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Inference for LowRank Models
This paper studies inference in linear models whose parameter of interes...
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Causal Bias Quantification for Continuous Treatment
In this work we develop a novel characterization of marginal causal effe...
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A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees
Debiased machine learning is a meta algorithm based on bias correction a...
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Learning Financial Network with Focally Sparse Structure
This paper studies the estimation of network connectedness with focally ...
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DeeplyDebiased OffPolicy Interval Estimation
Offpolicy evaluation learns a target policy's value with a historical d...
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Automatic Debiased Machine Learning via Neural Nets for Generalized Linear Regression
We give debiased machine learners of parameters of interest that depend ...
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DoubleML – An ObjectOriented Implementation of Double Machine Learning in Python
DoubleML is an opensource Python library implementing the double machin...
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DoubleML – An ObjectOriented Implementation of Double Machine Learning in R
The R package DoubleML implements the double/debiased machine learning f...
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Adversarial Estimation of Riesz Representers
We provide an adversarial approach to estimating Riesz representers of l...
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Nearly optimal central limit theorem and bootstrap approximations in high dimensions
In this paper, we derive new, nearly optimal bounds for the Gaussian app...
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Insights from Optimal Pandemic Shielding in a MultiGroup SEIR Framework
The COVID19 pandemic constitutes one of the largest threats in recent d...
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Causal Impact of Masks, Policies, Behavior on Early Covid19 Pandemic in the U.S
This paper evaluates the dynamic impact of various policies, such as sch...
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Adaptive Discrete Smoothing for HighDimensional and Nonlinear Panel Data
In this paper we develop a datadriven smoothing technique for highdime...
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Minimax Semiparametric Learning With Approximate Sparsity
Many objects of interest can be expressed as a linear, mean square conti...
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Improved Central Limit Theorem and bootstrap approximations in high dimensions
This paper deals with the Gaussian and bootstrap approximations to the d...
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Distributional conformal prediction
We propose a robust method for constructing conditionally valid predicti...
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Fast Algorithms for the Quantile Regression Process
The widespread use of quantile regression methods depends crucially on t...
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SortedEffects: Sorted Causal Effects in R
Chernozhukov et al. (2018) proposed the sorted effect method for nonline...
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Inference on weighted average value function in highdimensional state space
This paper gives a consistent, asymptotically normal estimator of the ex...
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SemiParametric Efficient Policy Learning with Continuous Actions
We consider offpolicy evaluation and optimization with continuous actio...
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Mastering Panel 'Metrics: Causal Impact of Democracy on Growth
The relationship between democracy and economic growth is of longstandi...
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Inference For Heterogeneous Effects Using LowRank Estimations
We study a panel data model with general heterogeneous effects, where sl...
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Closing the U.S. gender wage gap requires understanding its heterogeneity
In 2016, the majority of fulltime employed women in the U.S. earned sig...
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Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
We develop a distribution regression model under endogenous sample selec...
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Learning L2 Continuous Regression Functionals via Regularized Riesz Representers
Many objects of interest can be expressed as an L2 continuous functional...
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Valid Simultaneous Inference in HighDimensional Settings (with the hdm package for R)
Due to the increasing availability of highdimensional empirical applica...
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ShapeEnforcing Operators for Point and Interval Estimators
A common problem in statistics is to estimate and make inference on func...
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Subvector Inference in Partially Identified Models with Many Moment Inequalities
This paper considers inference for a function of a parameter vector in a...
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LASSODriven Inference in Time and Space
We consider the estimation and inference in a system of highdimensional...
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Plugin Regularized Estimation of HighDimensional Parameters in Nonlinear Semiparametric Models
We develop a theory for estimation of a highdimensional sparse paramete...
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HighDimensional Econometrics and Regularized GMM
This chapter presents key concepts and theoretical results for analyzing...
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HighDimensional Econometrics and Generalized GMM
This chapter presents key concepts and theoretical results for analyzing...
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Network and Panel Quantile Effects Via Distribution Regression
This paper provides a method to construct simultaneous confidence bands ...
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Double/DeBiased Machine Learning Using Regularized Riesz Representers
We provide adaptive inference methods for linear functionals of sparse l...
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Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data
We extend conformal inference to general settings that allow for time se...
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Censored Quantile Instrumental Variable Estimation with Stata
Many applications involve a censored dependent variable and an endogenou...
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Orthogonal Machine Learning for Demand Estimation: High Dimensional Causal Inference in Dynamic Panels
There has been growing interest in how economists can import machine lea...
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An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
This paper introduces new inference methods for counterfactual and synth...
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Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments
We propose strategies to estimate and make inference on key features of ...
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Detailed proof of Nazarov's inequality
The purpose of this note is to provide a detailed proof of Nazarov's ine...
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Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models
This paper introduces two classes of semiparametric triangular systems w...
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Best Linear Predictor with Missing Response: Locally Robust Approach
This paper provides asymptotic theory for Inverse Probability Weighing (...
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Double/Debiased/Neyman Machine Learning of Treatment Effects
Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016) prov...
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hdm: HighDimensional Metrics
In this article the package Highdimensional Metrics (hdm) is introduced...
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Double/Debiased Machine Learning for Treatment and Causal Parameters
Most modern supervised statistical/machine learning (ML) methods are exp...
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HighDimensional Metrics in R
The package Highdimensional Metrics (hdm) is an evolving collection of ...
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Program Evaluation and Causal Inference with HighDimensional Data
In this paper, we provide efficient estimators and honest confidence ban...
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Victor Chernozhukov
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Professor, Department of Economics + Center for Statistics and Data Science