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Structural Vector Autoregressions with Nonnormal Residuals

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  • Markku Lanne
  • Helmut Luetkepohl

Abstract

In structural vector autoregressive (SVAR) models identifying restrictions for shocks and impulse responses are usually derived from economic theory or institutional constraints. Sometimes the restrictions are insufficient for identifying all shocks and impulse responses. In this paper it is pointed out that specific distributional assumptions can also help in identifying the structural shocks. In particular, a mixture of normal distributions is considered as a plausible model that can be used in this context. Our model setup makes it possible to test restrictions which are just-identifying in a standard SVAR framework. In particular, we can test for the number of transitory and permanent shocks in a cointegrated SVAR model. The results are illustrated using a data set from King, Plosser, Stock and Watson (1991) and a system of US and European interest rates.

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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1651.

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Date of creation: 2006
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Handle: RePEc:ces:ceswps:_1651

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Keywords: mixture normal distribution; cointegration; vector autoregressive process; vector error correction model; impulse responses;

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References

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  1. Lanne, Markku & Saikkonen, Pentti, 2005. "A Multivariate Generalized Orthogonal Factor GARCH Model," MPRA Paper 23714, University Library of Munich, Germany.
  2. Ralf Brueggemann & Helmut Luetkepohl, 2005. "Uncovered Interest Rate Parity and the Expectations Hypothesis of the Term Structure: Empirical Results for the U.S. and Europe," Economics Working Papers ECO2005/08, European University Institute.
  3. Charles L. Evans & David A. Marshall, 1997. "Monetary policy and the term structure of nominal interest rates: evidence and theory," Working Paper Series, Macroeconomic Issues WP-97-10, Federal Reserve Bank of Chicago.
  4. Lucas, André, 1997. "Cointegration Testing Using Pseudolikelihood Ratio Tests," Econometric Theory, Cambridge University Press, vol. 13(02), pages 149-169, April.
  5. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-40, September.
  6. Benkwitz, Alexander & Lütkepohl, Helmut & Wolters, Jürgen, 1999. "Comparison of Bootstrap Confidence Intervals for Impulse Responses of German Monetary Systems," CEPR Discussion Papers 2208, C.E.P.R. Discussion Papers.
  7. repec:cup:macdyn:v:5:y:2001:i:1:p:81-100 is not listed on IDEAS
  8. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
  9. Nikolaus A. Siegfried, 2002. "An information-theoretic extension to structural VAR modelling," Quantitative Macroeconomics Working Papers 20203, Hamburg University, Department of Economics.
  10. Boswijk, H. Peter & Lucas, Andr‚, 1997. "Semi-nonparametric cointegration testing," Serie Research Memoranda 0041, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
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