This paper constructs individual-specific density forecasts for a panel of firms or households using a dynamic linear … model with common and heterogeneous coefficients and cross-sectional heteroskedasticity. The panel considered in this paper …

This paper considers a linear panel data model with time varying heterogeneity. Bayesian inference techniques organized …

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. …

using a sample of 3,979 neonates which represents over 84,846 observations (infant/days).We use a semiparametric panel data …

This paper constructs individual-specific density forecasts for a panel of firms or households using a dynamic linear … model with common and heterogeneous coefficients and cross-sectional heteroskedasticity. The panel considered in this paper …

Hausman-Taylor world and for dynamic panel data models with homogeneous/heterogeneous slopes and cross-sectional dependence …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 …

using a sample of 3,979 neonates which represents over 84,846 observations (infant/days). We use a semiparametric panel data …

In this paper, we develop a general method for heterogeneous variable selection in Bayesian nonlinear panel data models … approach for general nonlinear panel data models, encompassing multinomial logit and probit models, poisson and negative …

forecasts for short dynamic panel data. We implement a nonparametric Bayesian approach to simultaneously identify coefficients … accurate estimates and score predictive gains over standard panel data estimators. With a data-driven group structure, the BGRE … standard panel data estimators …

We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for a large cross‐section of short …