Structural Vector Autoregressions With Nonnormal Residuals
AbstractIn 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.Classification-JEL: C32
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 28 (2010)
Issue (Month): 1 ()
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Other versions of this item:
- Markku Lanne & Helmut Luetkepohl, 2005. "Structural Vector Autoregressions with Nonnormal Residuals," Economics Working Papers ECO2005/25, European University Institute.
- Markku Lanne & Helmut Luetkepohl, 2006. "Structural Vector Autoregressions with Nonnormal Residuals," CESifo Working Paper Series 1651, CESifo Group Munich.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
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