555 citations · 2.2k across the 12 of their papers we have counts for
13 papers
Bootstrap based asymptotic refinements for high-dimensional nonlinear models
Joel L. Horowitz, Ahnaf Rafi
We consider penalized extremum estimation of a high-dimensional, possibly nonlinear model that is sparse in the sense that most of its parameters are zero but some are not. We use…
Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks
Guohao Shen, Yuling Jiao, Yuanyuan Lin +2
We propose a penalized nonparametric approach to estimating the quantile regression process (QRP) in a nonseparable model using rectifier quadratic unit (ReQU) activated deep neura…
Deep Quantile Regression: Mitigating the Curse of Dimensionality Through Composition
Guohao Shen, Yuling Jiao, Yuanyuan Lin +2
This paper considers the problem of nonparametric quantile regression under the assumption that the target conditional quantile function is a composition of a sequence of low-dimen…
Inference in a class of optimization problems: Confidence regions and finite sample bounds on errors in coverage probabilities
Joel L. Horowitz, Sokbae Lee
This paper describes three methods for carrying out non-asymptotic inference on partially identified parameters that are solutions to a class of optimization problems. Applications…
Estimation of a Heterogeneous Demand Function with Berkson Errors
Richard Blundell, Joel Horowitz, Matthias Parey
Berkson errors are commonplace in empirical microeconomics. In consumer demand this form of measurement error occurs when the price an individual pays is measured by the (weighted)…
Non-Asymptotic Inference in Instrumental Variables Estimation
Joel L. Horowitz
This paper presents a simple method for carrying out inference in a wide variety of possibly nonlinear IV models under weak assumptions. The method is non-asymptotic in the sense t…