The desire to capture heterogeneity in the response of the dependent variable to covariates
often forces empiricists to employ panel data quantile regression models. Very often …

This thesis studies quantile regression methods for dynamic panel data models. Quantile
regression for panel data is extremely important in econometrics since it allows the …

This note discusses two errors in the approach proposed in Canay for constructing a
computationally simple two-step estimator in a quantile regression model with quantile …

We introduce a class of quantile regression estimators for short panels. Our framework
covers static and dynamic autoregressive models, models with general predetermined …

Unconditional quantile treatment effects are difficult to estimate in the presence of fixed
effects. Panel data are frequently used because fixed effects or differences are necessary to …

We propose a generalization of the linear quantile regression model to accommodate
possibilities afforded by panel data. Specifically, we extend the correlated random …

This paper proposes a penalized quantile regression estimator for panel data that explicitly
considers individual heterogeneity associated with the covariates. We provide conditions …

We propose a generalization of the linear quantile regression model to accommodate
possibilities afforded by panel data. Specifically, we extend the correlated random …

This chapter studies estimation and inference methods for multi-dimensional quantile
regression panel data models. First, we discuss the fixed effects (FE) model. This model …

We introduce a quantile regression approach to panel data models with endogenous
variables and individual effects correlated with the independent variables. We find newly …