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Gibbs sampling in econometric practice

  • de Pooter, M.D.
  • Segers, R.
  • van Dijk, H.K.

We present a road map for effective application of Bayesian analysis of a class of well-known dynamic econometric models by means of the Gibbs sampling algorithm. Members belonging to this class are the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model and as Hierarchical Linear Mixed Models, the State-Space model and the Panel Data model. We discuss issues involved when drawing Bayesian inference on equation parameters and variance components and show that one should carefully scan the shape of the criterion function for irregularities before applying the Gibbs sampler. Analytical, graphical and empirical results are used along the way.

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File URL: http://repub.eur.nl/pub/7743/EI%20report%202006-13.pdf
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Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2006-13.

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Date of creation: 21 Mar 2006
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Handle: RePEc:ems:eureir:7743
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Web page: http://www.eur.nl/ese

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  1. Sala-i-Martin, Xavier, 1994. "Cross-sectional regressions and the empirics of economic growth," European Economic Review, Elsevier, vol. 38(3-4), pages 739-747, April.
  2. Quah, Danny, 1997. "Empirics for Growth and Distribution: Stratification, Polarization, and Convergence Clubs," CEPR Discussion Papers 1586, C.E.P.R. Discussion Papers.
  3. Robert J. Barro, 1989. "Economic Growth in a Cross Section of Countries," NBER Working Papers 3120, National Bureau of Economic Research, Inc.
  4. Schotman, Peter & van Dijk, Herman K., 1991. "A Bayesian analysis of the unit root in real exchange rates," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 195-238.
  5. repec:dgr:uvatin:2098025 is not listed on IDEAS
  6. Dale J. Poirier, 1995. "Intermediate Statistics and Econometrics: A Comparative Approach," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262161494, June.
  7. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139, March.
  8. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, June.
  9. Kim, Chang-Jin & Nelson, Charles R, 1989. "The Time-Varying-Parameter Model for Modeling Changing Conditional Variance: The Case of the Lucas Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 433-40, October.
  10. Kleibergen, Frank & van Dijk, Herman K., 1994. "On the Shape of the Likelihood/Posterior in Cointegration Models," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 514-551, August.
  11. Frank Kleibergen & Herman K. van Dijk, 1998. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Tinbergen Institute Discussion Papers 98-025/4, Tinbergen Institute.
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