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Bayesian Inference in a Cointegrating Panel Data Model

Author

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  • Gary Koop
  • Roberto Leon-Gonzalez

    ()

  • Rodney Strachan

    ()

Abstract

This paper develops methods of Bayesian inference in a cointegrating panel data model. This model involves each cross-sectional unit having a vector error correction representation. It is flexible in the sense that different cross-sectional units can have different cointegration ranks and cointegration spaces. Furthermore, the parameters which characterize short-run dynamics and deterministic components are allowed to vary over cross-sectional units. In addition to a noninformative prior, we introduce an informative prior which allows for information about the likely location of the cointegration space and about the degree of similarity in coefficients in different cross-sectional units. A collapsed Gibbs sampling algorithm is developed which allows for efficient posterior inference. Our methods are illustrated using real and artificial data.

Suggested Citation

  • Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2006. "Bayesian Inference in a Cointegrating Panel Data Model," Discussion Papers in Economics 06/2, Department of Economics, University of Leicester.
  • Handle: RePEc:lec:leecon:06/2
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    File URL: http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp06-2.pdf
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    References listed on IDEAS

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    Cited by:

    1. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.

    More about this item

    Keywords

    Bayesian; panel data cointegration; error correction model; reduced rank regression; Markov Chain Monte Carlo;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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