16 citations · 37 across the 8 of their papers we have counts for
10 papers
Estimating Causal Effects of Discrete and Continuous Treatments with Binary Instruments
Victor Chernozhukov, Iván Fernández-Val, Sukjin Han +1
We propose an instrumental variable framework for identifying and estimating causal effects of discrete and continuous treatments with binary instruments. The basis of our approach…
Pairwise Valid Instruments
Zhenting Sun, Kaspar Wüthrich
Finding valid instruments is difficult. We propose Validity Set Instrumental Variable (VSIV) estimation, a method for estimating local average treatment effects (LATEs) in heteroge…
A model of multiple hypothesis testing
Davide Viviano, Kaspar Wuthrich, Paul Niehaus
Multiple hypothesis testing practices vary widely, without consensus on which are appropriate when. This paper provides an economic foundation for these practices designed to captu…
Bias correction for quantile regression estimators
Grigory Franguridi, Bulat Gafarov, Kaspar Wuthrich
We study the bias of classical quantile regression and instrumental variable quantile regression estimators. While being asymptotically first-order unbiased, these estimators can h…
Distributional conformal prediction
Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu
We propose a robust method for constructing conditionally valid prediction intervals based on models for conditional distributions such as quantile and distribution regression. Our…
Detecting p-hacking
Graham Elliott, Nikolay Kudrin, Kaspar Wuthrich
We theoretically analyze the problem of testing for -hacking based on distributions of -values across multiple studies. We provide general results for when such distributions…
Omitted variable bias of Lasso-based inference methods: A finite sample analysis
Kaspar Wuthrich, Ying Zhu
We study the finite sample behavior of Lasso-based inference methods such as post double Lasso and debiased Lasso. We show that these methods can exhibit substantial omitted variab…
Decentralization Estimators for Instrumental Variable Quantile Regression Models
Hiroaki Kaido, Kaspar Wuthrich
The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2005) is a popular tool for estimating causal quantile effects with endogenous covariates. Howe…
An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic Controls
Victor Chernozhukov, Kaspar Wüthrich, Yinchu Zhu
We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. We recast the causal inference problem as a counterfactual prediction…
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…