60 citations · 84 across the 9 of their papers we have counts for
12 papers
Principal Component Analysis for a Mix of Stationary and Nonstationary Variables
James D. Hamilton, Xinwei Ma, Jin Xi
This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables. The method does not require knowing which var…
Context-Dependent Heterogeneous Preferences: A Comment on Barseghyan and Molinari (2023)
Matias D. Cattaneo, Xinwei Ma, Yusufcan Masatlioglu
Barseghyan and Molinari (2023) give sufficient conditions for semi-nonparametric point identification of parameters of interest in a mixture model of decision-making under risk, al…
Breaking the Winner's Curse in Mendelian Randomization: Rerandomized Inverse Variance Weighted Estimator
Xinwei Ma, Jingshen Wang, Chong Wu
Developments in genome-wide association studies and the increasing availability of summary genetic association data have made the application of two-sample Mendelian Randomization…
lpcde: Estimation and Inference for Local Polynomial Conditional Density Estimators
Matias D. Cattaneo, Rajita Chandak, Michael Jansson +1
This paper discusses the R package lpcde, which stands for local polynomial conditional density estimation. It implements the kernel-based local polynomial smoothing methods introd…
Boundary Adaptive Local Polynomial Conditional Density Estimators
Matias D. Cattaneo, Rajita Chandak, Michael Jansson +1
We begin by introducing a class of conditional density estimators based on local polynomial techniques. The estimators are boundary adaptive and easy to implement. We then study th…
Attention Overload
Matias D. Cattaneo, Paul Cheung, Xinwei Ma +1
We introduce an Attention Overload Model (AOM) in which alternatives compete for attention, so each alternative's consideration probability weakly decreases as the choice problem e…
Local Regression Distribution Estimators
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
This paper investigates the large sample properties of local regression distribution estimators, which include a class of boundary adaptive density estimators as a prime example. F…
lpdensity: Local Polynomial Density Estimation and Inference
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
Density estimation and inference methods are widely used in empirical work. When the underlying distribution has compact support, conventional kernel-based density estimators are n…
Simple Local Polynomial Density Estimators
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
This paper introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automati…
Robust Inference Using Inverse Probability Weighting
Xinwei Ma, Jingshen Wang
Inverse Probability Weighting (IPW) is widely used in empirical work in economics and other disciplines. As Gaussian approximations perform poorly in the presence of "small denomin…
Two-Step Estimation and Inference with Possibly Many Included Covariates
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
We study the implications of including many covariates in a first-step estimate entering a two-step estimation procedure. We find that a first order bias emerges when the number of…
A Random Attention Model
Matias D. Cattaneo, Xinwei Ma, Yusufcan Masatlioglu +1
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Ran…