This paper is concerned with computational issues related to penalized quantile regression
(PQR) with ultrahigh dimensional predictors. Various algorithms have been developed for …

Quantile regression has become one of the standard tools of econometrics. We examine its
compatibility with the special goals of stochastic frontier analysis. We document several …

In this paper, we develop spectral and post-spectral estimators for grouped panel data
models. Both estimators are consistent in the asymptotics where the number of observations …

This paper provides a new multi-dimensional clustering approach for unobserved
heterogeneity in panel data models. Each unit is associated with multiple clusters. For …

This paper provides a framework for joint estimation and identification of latent group
structures in panel data models using a pairwise fusion penalized approach. The latent …

Dynamic interactions among several stochastic processes are common in many scientific
fields. It is crucial to model these interactions to understand the dynamic relationship of the …

In non-experimental longitudinal studies, researchers often estimate causal effects
assuming time-constant unobserved heterogeneity or linear-in-parameters conditional …

This paper studies economic resilience as the ability of an economic system to respond to
adverse shocks. We propose several measures of resilience based on a quantile function …

This paper introduces a new fixed effects estimator for linear panel data models with
clustered time patterns of unobserved heterogeneity. The method avoids non-convex and …

While the Vector Autoregression (VAR) model has received extensive attention for modelling
complex time series, quantile VAR analysis remains relatively underexplored for high …