Error Bands for Impulse Responses
AbstractWe examine the theory and behavior in practice of Bayesian and bootstrap methods for generating error bands on impulse responses in dynamic linear models. The Bayesian intervals have a firmer theoretical foundation in small samples, are easier to compute, and are about as good in small samples by classical criteria as are the best bootstrap intervals. Bootstrap intervals based directly on the simulated small-sample distribution of an estimator, without bias correction, perform very badly. We show that a method that has been used to extend to the overidentified case standard algorithms for Bayesian intervals in reduced form models is incorrect, and we show how to obtain correct Bayesian intervals for this case.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1085.
Length: 42 pages
Date of creation: Nov 1994
Date of revision:
Publication status: Published in Econometrica (1999), 67(5): 1113-1156
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Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Other versions of this item:
- NEP-ALL-2000-06-29 (All new papers)
- NEP-ECM-2000-06-29 (Econometrics)
- NEP-ETS-2000-06-29 (Econometric Time Series)
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