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Noncausal vector autoregression

  • Lanne, Markku

    ()

    (Department of Economics, and HECER, University of Helsinki)

  • Saikkonen, Pentti

    ()

    (Department of Mathematics and Statistics, and HECER, University of Helsinki)

In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time series. The assumption of non-Gaussianity is needed for reasons of identifiability. Assuming that the error distribution belongs to a fairly general class of elliptical distributions, we develop an asymptotic theory of maximum likelihood estimation and statistical inference. We argue that allowing for noncausality is of importance in empirical economic research, which currently uses only conventional causal VAR models. Indeed, if noncausality is incorrectly ignored, the use of a causal VAR model may yield suboptimal forecasts and misleading economic interpretations. This is emphasized in the paper by noting that noncausality is closely related to the notion of nonfundamentalness, under which structural economic shocks cannot be recovered from an estimated causal VAR model. As detecting nonfundamentalness is therefore of great importance, we propose a procedure for discriminating between causality and noncausality that can be seen as a test of nonfundamentalness. The methods are illustrated with applications to fiscal foresight and the term structure of interest rates.

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File URL: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/keskustelualoitteet/Documents/0918netti.pdf
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Paper provided by Bank of Finland in its series Research Discussion Papers with number 18/2009.

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Length: 63 pages
Date of creation: 12 Aug 2009
Date of revision:
Handle: RePEc:hhs:bofrdp:2009_018
Contact details of provider: Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland
Web page: http://www.suomenpankki.fi/en/

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  1. Shiller, Robert & Campbell, John, 1991. "Yield Spreads and Interest Rate Movements: A Bird's Eye View," Scholarly Articles 3221490, Harvard University Department of Economics.
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  11. Thomas A. Lubik & Frank Schorfheide, 2004. "Testing for Indeterminacy: An Application to U.S. Monetary Policy," American Economic Review, American Economic Association, vol. 94(1), pages 190-217, March.
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  18. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2011. "Non‐Fundamentalness in Structural Econometric Models: A Review," International Statistical Review, International Statistical Institute, vol. 79(1), pages 16-47, 04.
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  21. Breid, F. Jay & Davis, Richard A. & Lh, Keh-Shin & Rosenblatt, Murray, 1991. "Maximum likelihood estimation for noncausal autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 36(2), pages 175-198, February.
  22. Francq, Christian & Roy, Roch & Zakoian, Jean-Michel, 2005. "Diagnostic Checking in ARMA Models With Uncorrelated Errors," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 532-544, June.
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  24. Christopher L. House & Matthew D. Shapiro, 2008. "Temporary Investment Tax Incentives: Theory with Evidence from Bonus Depreciation," American Economic Review, American Economic Association, vol. 98(3), pages 737-68, June.
  25. Lof, Matthijs, 2011. "Noncausality and Asset Pricing," MPRA Paper 30519, University Library of Munich, Germany.
  26. Lanne, Markku & Saikkonen, Pentti, 2010. "Noncausal autoregressions for economic time series," MPRA Paper 32943, University Library of Munich, Germany.
  27. Douglas G. Steigerwald & Charles Stuart, 1997. "Econometric Estimation Of Foresight: Tax Policy And Investment In The United States," The Review of Economics and Statistics, MIT Press, vol. 79(1), pages 32-40, February.
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