be partially or irregularly identified. To illustrate our approach we study panel data models where the distribution of …

The paper develops a general Bayesian framework for robust linear static panel data models using ε-contamination. A two … performance of our estimator relative to classic panel estimators using data on earnings and crime. …

This paper extends the work of Baltagi et al. (2018) to the popular dynamic panel data model. We investigate the … robustness of Bayesian panel data models to possible misspecication of the prior distribution. The proposed robust Bayesian … specifications which includes the dynamic panel model with random effects, with cross-correlated effects à la Chamberlain, for the …

This study develops cluster robust inference methods for panel quantile regression (QR) models with individual fixed …

-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution … general “toolbox” for a wide range of specifications which includes the dynamic space- time panel model with random effects …, with cross-correlated effects à la Chamberlain, for the Hausman-Taylor world and for dynamic panel data models with …

The properties of classical panel data estimators including fixed effect, first-differences, random effects, and … generalized method of moments-instrumental variables estimators in both static as well as dynamic panel data models are …

We propose a new estimator for average causal effects of a binary treatment with panel data in settings with general …

This paper proposes new ℓ1-penalized quantile regression estimators for panel data, which explicitly allows for …