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On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling

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Author Info
Michiel D. de Pooter () (Faculty of Economics, Erasmus Universiteit Rotterdam)
René Segers () (Faculty of Economics, Erasmus Universiteit Rotterdam)
Herman K. van Dijk () (Faculty of Economics, Erasmus Universiteit Rotterdam)

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Abstract

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables 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 regression parameters and variance components, in particular when some parameter have substantial posterior probability near the boundary of the parameter region, and show that one should carefully scan the shape of the posterior density function. Analytical, graphical and empirical results are used along the way.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 06-076/4.

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Date of creation: 31 Aug 2006
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Handle: RePEc:dgr:uvatin:20060076

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Gibbs sampler; MCMC; serial correlation; non-stationarity; reduced rank models; state-space models; random effects panel data models;

Other versions of this item:

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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  1. 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.
  2. Van Dijk, H.K. & Koop, G., 1999. "Testing for Integration Using Evolving Trend and Seasonals Models : A Bayesian Approach," Papers 9934/a, Erasmus University of Rotterdam - Econometric Institute.
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  3. Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July. [Downloadable!] (restricted)
    Other versions:
  4. Kleibergen, Frank & van Dijk, Herman K., 1998. "Bayesian Simultaneous Equations Analysis Using Reduced Rank Structures," Econometric Theory, Cambridge University Press, vol. 14(06), pages 701-743, December. [Downloadable!]
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  5. H. K. Van Dijk, 1999. "Some remarks on the simulation revolution in bayesian econometric inference," Econometric Reviews, Taylor and Francis Journals, vol. 18(1), pages 105-112. [Downloadable!] (restricted)
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  6. Pooter, M.D. de & Segers, R. & Dijk, H.K. van, 2006. "Gibbs sampling in econometric practice," Econometric Institute Report EI 2006-13 Revision_Date:, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
  7. Frank Kleibergen & Herman K. van Dijk, 1998. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Tinbergen Institute Discussion Papers 98-025/4, Tinbergen Institute. [Downloadable!]
  8. Kleibergen, F.R. & Van Dijk, H.K., 1993. "On the Shape of the Likelyhood/Posterior in Cointegration Models," Papers 9315-a, Erasmus University of Rotterdam - Econometric Institute.
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  9. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," NBER Working Papers 3120, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  10. 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. [Downloadable!] (restricted)
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  11. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August. [Downloadable!]
  12. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  13. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De. [Downloadable!] (restricted)
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