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04/28/2023
Hedonic Prices and Quality Adjusted Price Indices Powered by AI
Accurate, real-time measurements of price index changes using electronic...
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01/18/2023
An MCMC Approach to Classical Estimation
This paper studies computationally and theoretically attractive estimato...
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07/26/2022
Future-Dependent Value-Based Off-Policy Evaluation in POMDPs
We study off-policy evaluation (OPE) for partially observable MDPs (POMD...
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05/19/2022
High-dimensional Data Bootstrap
This article reviews recent progress in high-dimensional bootstrap. We f...
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12/26/2021
Omitted Variable Bias in Machine Learned Causal Models
We derive general, yet simple, sharp bounds on the size of the omitted v...
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10/10/2021
A Response to Philippe Lemoine's Critique on our Paper "Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S."
Recently, Phillippe Lemoine posted a critique of our paper "Causal Impac...
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10/06/2021
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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07/06/2021
Inference for Low-Rank Models
This paper studies inference in linear models whose parameter of interes...
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06/17/2021
Causal Bias Quantification for Continuous Treatment
In this work we develop a novel characterization of marginal causal effe...
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05/31/2021
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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05/16/2021
Learning Financial Network with Focally Sparse Structure
This paper studies the estimation of network connectedness with focally ...
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05/10/2021
Deeply-Debiased Off-Policy Interval Estimation
Off-policy evaluation learns a target policy's value with a historical d...
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04/30/2021
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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04/07/2021
DoubleML – An Object-Oriented Implementation of Double Machine Learning in Python
DoubleML is an open-source Python library implementing the double machin...
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03/17/2021
DoubleML – An Object-Oriented Implementation of Double Machine Learning in R
The R package DoubleML implements the double/debiased machine learning f...
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12/30/2020
Adversarial Estimation of Riesz Representers
We provide an adversarial approach to estimating Riesz representers of l...
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12/17/2020
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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11/02/2020
Insights from Optimal Pandemic Shielding in a Multi-Group SEIR Framework
The COVID-19 pandemic constitutes one of the largest threats in recent d...
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05/28/2020
Causal Impact of Masks, Policies, Behavior on Early Covid-19 Pandemic in the U.S
This paper evaluates the dynamic impact of various policies, such as sch...
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12/30/2019
Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data
In this paper we develop a data-driven smoothing technique for high-dime...
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12/27/2019
Minimax Semiparametric Learning With Approximate Sparsity
Many objects of interest can be expressed as a linear, mean square conti...
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12/22/2019
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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09/17/2019
Distributional conformal prediction
We propose a robust method for constructing conditionally valid predicti...
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09/12/2019
Fast Algorithms for the Quantile Regression Process
The widespread use of quantile regression methods depends crucially on t...
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09/02/2019
SortedEffects: Sorted Causal Effects in R
Chernozhukov et al. (2018) proposed the sorted effect method for nonline...
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08/24/2019
Inference on weighted average value function in high-dimensional state space
This paper gives a consistent, asymptotically normal estimator of the ex...
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05/24/2019
Semi-Parametric Efficient Policy Learning with Continuous Actions
We consider off-policy evaluation and optimization with continuous actio...
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01/12/2019
Mastering Panel 'Metrics: Causal Impact of Democracy on Growth
The relationship between democracy and economic growth is of long-standi...
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12/19/2018
Inference For Heterogeneous Effects Using Low-Rank Estimations
We study a panel data model with general heterogeneous effects, where sl...
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12/11/2018
Closing the U.S. gender wage gap requires understanding its heterogeneity
In 2016, the majority of full-time employed women in the U.S. earned sig...
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11/28/2018
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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09/14/2018
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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09/13/2018
Valid Simultaneous Inference in High-Dimensional Settings (with the hdm package for R)
Due to the increasing availability of high-dimensional empirical applica...
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09/04/2018
Shape-Enforcing Operators for Point and Interval Estimators
A common problem in statistics is to estimate and make inference on func...
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06/29/2018
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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06/13/2018
LASSO-Driven Inference in Time and Space
We consider the estimation and inference in a system of high-dimensional...
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06/13/2018
Plug-in Regularized Estimation of High-Dimensional Parameters in Nonlinear Semiparametric Models
We develop a theory for estimation of a high-dimensional sparse paramete...
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06/05/2018
High-Dimensional Econometrics and Regularized GMM
This chapter presents key concepts and theoretical results for analyzing...
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06/05/2018
High-Dimensional Econometrics and Generalized GMM
This chapter presents key concepts and theoretical results for analyzing...
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03/21/2018
Network and Panel Quantile Effects Via Distribution Regression
This paper provides a method to construct simultaneous confidence bands ...
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02/23/2018
Double/De-Biased Machine Learning Using Regularized Riesz Representers
We provide adaptive inference methods for linear functionals of sparse l...
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02/17/2018
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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01/13/2018
Censored Quantile Instrumental Variable Estimation with Stata
Many applications involve a censored dependent variable and an endogenou...
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12/28/2017
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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12/25/2017
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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12/13/2017
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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11/29/2017
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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11/06/2017
Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models
This paper introduces two classes of semiparametric triangular systems w...
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02/21/2017
Best Linear Predictor with Missing Response: Locally Robust Approach
This paper provides asymptotic theory for Inverse Probability Weighing (...
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01/30/2017
