This article reviews recent advances in fixed effects estimation of panel data models for long
panels, where the number of time periods is relatively large. We focus on semiparametric …

This paper studies fixed effects estimation of quantile regression models for panel data.
Under an asymptotic framework where both the numbers of individuals and time periods …

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

Regression discontinuity is a popular tool for analyzing economic policies or treatment
interventions. This research extends the classic static RD model to a dynamic framework …

This paper studies the identification of causal effects of a continuous treatment using a new
difference-in-difference strategy. Our approach allows for endogeneity of the treatment, and …

This paper shows that the Conditional Quantile Treatment Effect on the Treated is identified
under (i) a Conditional Distributional Difference in Differences assumption and (ii) a new …

This paper proposes a quantile regression estimator for a heterogeneous panel model with
lagged dependent variables and interactive effects. The paper adopts the Common …

We provide new results for nonparametric identification, estimation, and inference of causal
effects usingproxy controls': observables that are noisy but informative proxies for …

This paper introduces estimation methods for grouped latent heterogeneity in panel data
quantile regression. We assume that the observed individuals come from a heterogeneous …

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