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Short run and long run causality in time series: inference

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  • Dufour, Jean-Marie
  • Pelletier, Denis
  • Renault, Eric

Abstract

We propose methods for testing hypotheses of non-causality at various horizons, as defined in Dufour and Renault (1998, Econometrica). We study in detail the case of VAR models and we propose linear methods based on running vector autoregressions at different horizons. While the hypotheses considered are nonlinear, the proposed methods only require linear regression techniques as well as standard Gaussian asymptotic distributional theory. Bootstrap procedures are also considered. For the case of integrated processes, we propose extended regression methods that avoid nonstandard asymptotics. The methods are applied to a VAR model of the U.S. economy.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 132 (2006)
Issue (Month): 2 (June)
Pages: 337-362

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Handle: RePEc:eee:econom:v:132:y:2006:i:2:p:337-362

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Web page: http://www.elsevier.com/locate/jeconom

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References

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  1. Dufour, Jean-Marie & Ghysels, Eric & Hall, Alastair, 1994. "Generalized Predictive Tests and Structural Change Analysis in Econometrics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(1), pages 199-229, February.
  2. Donald W.K. Andrews, 1988. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Cowles Foundation Discussion Papers 877R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1989.
  3. DUFOUR, Jean-Marie & PELLETIER, Denis & RENAULT, Éric, 2003. "Short run and long run causality in time series: Inference," Cahiers de recherche 2003-16, Universite de Montreal, Departement de sciences economiques.
  4. Renault, Eric & Sekkat, Khalid & Szafarz, Ariane, 1998. "Testing for spurious causality in exchange rates," Journal of Empirical Finance, Elsevier, vol. 5(1), pages 47-66, January.
  5. Dufour, J.M. & Khalaf, L., 2000. "Simulation-Based Finite and Large Sample Tests in Multivariate Regressions," Cahiers de recherche 2000-10, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  6. Park, Joon Y. & Phillips, Peter C.B., 1989. "Statistical Inference in Regressions with Integrated Processes: Part 2," Econometric Theory, Cambridge University Press, vol. 5(01), pages 95-131, April.
  7. Bernanke, Ben S. & Mihov, Ilian, 1995. "Measuring Monetary Policy," Economics Series 10, Institute for Advanced Studies.
  8. Hiro Y. Toda & Peter C.B. Phillips, 1991. "Vector Autoregression and Causality: A Theoretical Overview and Simulation Study," Cowles Foundation Discussion Papers 1001, Cowles Foundation for Research in Economics, Yale University.
  9. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
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