Regression modelEconometrics / time series

Bayesian Dynamic Panel Data Model

The Bayesian dynamic panel data model extends standard dynamic panel models — which include a lagged dependent variable to capture state dependence — by estimating all parameters within a Bayesian framework. Prior distributions are combined with the likelihood to yield a full posterior distribution over model parameters, enabling probabilistic inference and coherent uncertainty quantification even in short panels.

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Sources

  1. Hsiao, C., Pesaran, M. H., & Tahmiscioglu, A. K. (2002). Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics, 109(1), 107–150. DOI: 10.1016/S0304-4076(01)00143-9
  2. Arellano, M., & Bonhomme, S. (2007). Robust priors in nonlinear panel data models. Econometrica, 77(2), 489–536. DOI: 10.3982/ECTA6895

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Referenced by

ScholarGateBayesian Dynamic Panel Data Model (Bayesian Dynamic Panel Data Model). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/bayesian-dynamic-panel-data-model