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Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space

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  • Gary Koop

    ()

  • Roberto León-González

    ()

  • Rodney W. Strachan

    ()

Abstract

A message coming out of the recent Bayesian literature on cointegration is that it is important to elicit a prior on the space spanned by the cointegrating vectors (as opposed to a particular identified choice for these vectors). In this note, we discuss a sensible way of eliciting such a prior. Furthermore, we develop a collapsed Gibbs sampling algorithm to carry out efficient posterior simulation in cointegration models. The computational advantages of our algorithm are most pronounced with our model, since the form of our prior precludes simple posterior simulation using conventional methods (e.g. a Gibbs sampler involves non-standard posterior conditionals). However, the theory we draw upon implies our algorithm will be more efficient even than the posterior simulation methods which are used with identified versions of cointegration models.

Suggested Citation

  • Gary Koop & Roberto León-González & Rodney W. Strachan, 2005. "Efficient Posterior Simulation for Cointegrated Models with Priors On the Cointegration Space," Discussion Papers in Economics 05/13, Department of Economics, University of Leicester, revised Apr 2006.
  • Handle: RePEc:lec:leecon:05/13
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    File URL: http://www.le.ac.uk/economics/research/RePEc/lec/leecon/dp05-13.pdf
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    References listed on IDEAS

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    1. Strachan, R.W. & van Dijk, H.K., 2004. "Valuing structure, model uncertainty and model averaging in vector autoregressive processes," Econometric Institute Research Papers EI 2004-23, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    Cited by:

    1. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney, 2012. "Bayesian model averaging in the instrumental variable regression model," Journal of Econometrics, Elsevier, vol. 171(2), pages 237-250.
    2. Sylvia Kaufmann & Johann Scharler, 2013. "Bank-Lending Standards, Loan Growth and the Business Cycle in the Euro Area," Working Papers 2013-34, Faculty of Economics and Statistics, University of Innsbruck.
    3. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, Elsevier.
    4. Justyna Wróblewska, 2015. "Common Trends and Common Cycles – Bayesian Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 7(2), pages 91-110, June.
    5. Krzysztof Osiewalski & Jacek Osiewalski, 2013. "A Long-Run Relationship between Daily Prices on Two Markets: The Bayesian VAR(2)–MSF-SBEKK Model," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 5(1), pages 65-83, March.
    6. Jochmann Markus & Koop Gary, 2015. "Regime-switching cointegration," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 35-48, February.
    7. Katsuhiro Sugita, 2017. "Time Series Analysis of the US Term Structure of Interest Rates Using a Bayesian Markov Switching Cointegration Model," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(3), pages 49-56, March.
    8. Justyna Wróblewska, 2012. "Bayesian Analysis of Weak Form Polynomial Reduced Rank Structures in VEC Models," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(4), pages 253-267, December.
    9. Dąbrowski, Marek A. & Wróblewska, Justyna, 2015. "Exchange rate as a shock absorber or a shock propagator in Poland and Slovakia - an approach based on Bayesian SVAR models with common serial correlation," MPRA Paper 61441, University Library of Munich, Germany.
    10. Justyna Wróblewska, 2011. "Bayesian Analysis of Weak Form Reduced Rank Structure in VEC Models," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 3(3), pages 169-186, September.
    11. Tsay, Ruey S. & Ando, Tomohiro, 2012. "Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3345-3365.
    12. Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W., 2011. "Bayesian inference in a time varying cointegration model," Journal of Econometrics, Elsevier, vol. 165(2), pages 210-220.
    13. Dąbrowski, Marek A. & Wróblewska, Justyna, 2016. "Exchange rate as a shock absorber in Poland and Slovakia: Evidence from Bayesian SVAR models with common serial correlation," Economic Modelling, Elsevier, vol. 58(C), pages 249-262.
    14. Heather M Anderson & Farshid Vahid, 2010. "VARs, Cointegration and Common Cycle Restrictions," Monash Econometrics and Business Statistics Working Papers 14/10, Monash University, Department of Econometrics and Business Statistics.

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