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Structural Error Correction Model: A Bayesian Perspective

Author

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  • Chew Lian Chua
  • Peter Summers

Abstract

This paper proposes a Structural Error Correction Model (SECM) that allows concurrent estimation of the structural parameters and analysis of cointegration. We amalgamate the Bayesian methods of Kleibergen and Paap (2002) for analysis of cointegration in the ECM, and the Bayesian methods of Waggoner and Zha (2003) for estimating the structural parameters in BSVAR into our proposed model. Empirically, we apply the SCEM to four data generating processes, each with a different number of cointegrating vector. The results show that in each of the DGPs, the Bayes factors are able to select the appropriate cointegrating vectors and the estimated marginal posterior parameters’ pdfs cover the actual values. Key words: structural error correction model

Suggested Citation

  • Chew Lian Chua & Peter Summers, 2004. "Structural Error Correction Model: A Bayesian Perspective," Econometric Society 2004 Far Eastern Meetings 702, Econometric Society.
  • Handle: RePEc:ecm:feam04:702
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    References listed on IDEAS

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    1. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    2. Strachan, Rodney W, 2003. "Valid Bayesian Estimation of the Cointegrating Error Correction Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 185-195, January.
    3. BAUWENS, Luc & GIOT, Pierre, 1997. "A Gibbs sampling approach to cointegration," CORE Discussion Papers 1997016, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Daniel F. Waggoner & Tao Zha, 2000. "A Gibbs simulator for restricted VAR models," FRB Atlanta Working Paper 2000-3, Federal Reserve Bank of Atlanta.
    5. 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.
    6. Kleibergen, Frank & Paap, Richard, 2002. "Priors, posteriors and bayes factors for a Bayesian analysis of cointegration," Journal of Econometrics, Elsevier, vol. 111(2), pages 223-249, December.
    7. Sugita, K., 2001. "Bayesian Cointegration Analysis," The Warwick Economics Research Paper Series (TWERPS) 591, University of Warwick, Department of Economics.
    8. Fisher, Lance A. & Huh, Hyeon-Seung & Summers, Peter M., 2000. "Structural Identification of Permanent Shocks in VEC Models: A Generalization," Journal of Macroeconomics, Elsevier, vol. 22(1), pages 53-68, January.
    9. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    10. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    11. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
    12. Amisano, Gianni, 2003. "Bayesian inference in cointegrated systems," Research in Economics, Elsevier, vol. 57(4), pages 287-314, December.
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    More about this item

    Keywords

    structural error correction model; cointegration; Bayesian; structural parameters; singular value decomposition.;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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