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Structural Vector Autoregressions with Nonnormal Residuals

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Author Info
Markku Lanne ()
Helmut Lütkepohl ()

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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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Publisher Info
Paper provided by CESifo GmbH in its series CESifo Working Paper Series with number CESifo Working Paper No. 1651.

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

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

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January. [Downloadable!] (restricted)
  2. Boswijk, H. Peter & Lucas, Andr‚, 1997. "Semi-nonparametric cointegration testing," Serie Research Memoranda 0041, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics. [Downloadable!]
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  3. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1991. "Stochastic trends and economic fluctuations," Working Paper Series, Macroeconomic Issues 91-4, Federal Reserve Bank of Chicago.
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  4. Evans, Charles L. & Marshall, David A., 1998. "Monetary policy and the term structure of nominal interest rates: Evidence and theory," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 53-111, December. [Downloadable!] (restricted)
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  5. 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. [Downloadable!] (restricted)
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  6. repec:cup:macdyn:v:5:y:2001:i:1:p:81-100 is not listed on IDEAS
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Cited by:
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  1. Markku Lanne & Helmut Luetkepohl, 2008. "A Statistical Comparison of Alternative Identification Schemes for Monetary Policy Shocks," Economics Working Papers ECO2008/23, European University Institute. [Downloadable!]
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