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.
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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1651.
Date of creation: 2006
Date of revision:
mixture normal distribution; cointegration; vector autoregressive process; vector error correction model; impulse responses;
Other versions of this item:
- Lanne, Markku & LÃ¼tkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
- Markku Lanne & Helmut Luetkepohl, 2005. "Structural Vector Autoregressions with Nonnormal Residuals," Economics Working Papers ECO2005/25, European University Institute.
- 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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