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Bayesian Inference For State Space Model With Panel Data

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  • Ranjita Pandey
  • Anoop Chaturvedi

Abstract

The present work explores panel data set-up in a Bayesian state space model. The conditional posterior densities of parameters are utilized to determine the marginal posterior densities using the Gibbs sampler. An efficient one step ahead predictive density mechanism is developed to further the state of art in prediction-based decision making.

Suggested Citation

  • Ranjita Pandey & Anoop Chaturvedi, 2016. "Bayesian Inference For State Space Model With Panel Data," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 17(2), pages 211-219, June.
    • Handle: RePEc:csb:stintr:v:17:y:2016:i:2:p:211-219
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    References listed on IDEAS

    as
    1. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    3. Chamberlain, Gary, 1982. "Multivariate regression models for panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 5-46, January.
    4. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    5. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
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