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Codependent VAR Models and the Pseudo-Structural Form

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  • Trenkler, Carsten
  • Weber, Enzo

Abstract

This paper investigates whether codependence restrictions can be uniquely imposed on VAR and VEC models via the so-called pseudo-structural form used in the literature. Codependence of order q is given if a linear combination of autocorrelated variables eliminates the serial correlation after q lags. Importantly, maximum likelihood estimation and likelihood ratio testing are only possible if the codependence restrictions can be uniquely imposed. Applying the pseudostructural form, our study reveals that this is not generally the case, but that unique imposition is guaranteed in several important special cases. Moreover, we discuss further issues, in particular upper bounds for the codependence order.

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Paper provided by University of Mannheim, Department of Economics in its series Working Papers with number 12-10.

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Date of creation: 2012
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Handle: RePEc:mnh:wpaper:31690

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Keywords: Codependence ; VAR ; cointegration ; pseudo-structural form ; serial correlation common features;

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  1. Vahid, F. & Issler, J.V., 2001. "The Importance Of Common Cyclical Features in VAR Analysis: A Monte-Carlo Study," Monash Econometrics and Business Statistics Working Papers 2/01, Monash University, Department of Econometrics and Business Statistics.
  2. Cubadda, Gianluca & Hecq, Alain, 2001. "On non-contemporaneous short-run co-movements," Economics Letters, Elsevier, vol. 73(3), pages 389-397, December.
  3. Carsten Trenkler & Enzo Weber, 2013. "Codependent VAR models and the pseudo-structural form," AStA Advances in Statistical Analysis, Springer, vol. 97(3), pages 287-295, July.
  4. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-95, October.
  5. Vahid, Farshid & Engle, Robert F., 1997. "Codependent cycles," Journal of Econometrics, Elsevier, vol. 80(2), pages 199-221, October.
  6. Robert F. Engle & Sharon Kozicki, 1990. "Testing For Common Features," NBER Technical Working Papers 0091, National Bureau of Economic Research, Inc.
  7. Trenkler, Carsten & Weber, Enzo, 2010. "Testing for Codependence of Non-Stationary Variables," University of Regensburg Working Papers in Business, Economics and Management Information Systems 446, University of Regensburg, Department of Economics.
  8. Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-60, Oct.-Dec..
  9. Paruolo Paolo, 2003. "Common dynamics in I(1) VAR systems," Economics and Quantitative Methods qf0316, Department of Economics, University of Insubria.
  10. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
  11. Franchi, Massimo & Paruolo, Paolo, 2011. "A characterization of vector autoregressive processes with common cyclical features," Journal of Econometrics, Elsevier, vol. 163(1), pages 105-117, July.
  12. Robert F. Engle & João Victor Issler, 1993. "Common trends and common cycles in Latin America," Revista Brasileira de Economia, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 47(2), pages 149-176, April.
  13. Christoph Schleicher, 2004. "Codependence in Cointegrated Autoregressive Models," Computing in Economics and Finance 2004 286, Society for Computational Economics.
  14. Gouriéroux, Christian & Peaucelle, Irina, 1992. "Séries codépendantes : application à l’hypothèse de parité du pouvoir d’achat," L'Actualité Economique, Société Canadienne de Science Economique, vol. 68(1), pages 283-304, mars et j.
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Cited by:
  1. Trenkler, Carsten & Weber, Enzo, 2012. "Identifying the Shocks behind Business Cycle Asynchrony in Euroland," Working Papers 12-11, University of Mannheim, Department of Economics.
  2. Carsten Trenkler & Enzo Weber, 2013. "Codependent VAR models and the pseudo-structural form," AStA Advances in Statistical Analysis, Springer, vol. 97(3), pages 287-295, July.

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