In this article, we consider a high-dimensional quantile regression model where the sparsity
structure may differ between two sub-populations. We develop ℓ1-penalized estimators of …

This paper provides estimation and inference methods for a large number of heterogeneous
treatment effects in a panel data setting with many potential controls. We assume that …

High-dimensional time series datasets are becoming increasingly common in various fields
of economics and finance. Given the ubiquity of time series data, it is crucial to develop …

This paper addresses statistical inference for high-dimensional threshold regression
parameters. I establish oracle inequalities for the scaled LASSO estimator proposed by Lee …

We develop uniform inference for high-dimensional threshold regression parameters and
valid inference for the threshold parameter in this paper. We first establish oracle …

This paper studies the variable selection problem in threshold model with a covariate-
dependent threshold, in which the threshold is modeled by a function of candidate variables …

This paper studies high-dimensional threshold models with a time-varying threshold
approximated using a Fourier function. We develop a weighted LASSO estimator of …

This paper investigates the degree of market integration, exchange rate pass-through, and
the market factors that contribute to deviations from perfect integration. To analyze the price …

We combine the robust criterion with the lasso penalty together for the high-dimensional
threshold model. It estimates regression coeffcients as well as the threshold parameter …

This paper investigates the extent of market integration and exchange rate pass-through, as
well as market factors that may be associated with deviations from perfect market integration …