2 citations · 4 across the 6 of their papers we have counts for
6 papers
Dimension Reduction for Conditional Density Estimation with Applications to High-Dimensional Causal Inference
Jianhua Mei, Fu Ouyang, Thomas T. Yang
We propose a novel and computationally efficient approach for nonparametric conditional density estimation in high-dimensional settings that achieves dimension reduction without im…
High Dimensional Binary Choice Model with Unknown Heteroskedasticity or Instrumental Variables
Fu Ouyang, Thomas Tao Yang
This paper proposes a new method for estimating high-dimensional binary choice models. We consider a semiparametric model that places no distributional assumptions on the error ter…
Semiparametric Discrete Choice Models for Bundles
Fu Ouyang, Thomas Tao Yang
We propose two approaches to estimate semiparametric discrete choice models for bundles. Our first approach is a kernel-weighted rank estimator based on a matching-based identifica…
Semiparametric Discrete Choice Models for Bundles
Fu Ouyang, Thomas T. Yang
We propose two approaches to estimate semiparametric discrete choice models for bundles. Our first approach is a kernel-weighted rank estimator based on a matching-based identifica…
Revisiting Panel Data Discrete Choice Models with Lagged Dependent Variables
Christopher R. Dobronyi, Fu Ouyang, Thomas Tao Yang
This paper revisits the identification and estimation of a class of semiparametric (distribution-free) panel data binary choice models with lagged dependent variables, exogenous co…
Semiparametric Estimation of Dynamic Binary Choice Panel Data Models
Fu Ouyang, Thomas Tao Yang
We propose a new approach to the semiparametric analysis of panel data binary choice models with fixed effects and dynamics (lagged dependent variables). The model we consider has…