English, Article, Journal or magazine article edition: Vector Autoregressions and Reduced Form Representations of DSGE Models Federico Ravenna

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Bookmark: http://trove.nla.gov.au/version/56661
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Vector autoregressions and reduced form representations of DSGE models
Author
  • Federico Ravenna
Physical Description
  • preprint
Notes
  • Vector Autoreregression; Dynamic Stochastic General Equilibrium Model; Kalman Filter; Business Cycle Shocks
  • RePEc:red:sed005:841
  • Dynamic Stochastic General Equilibrium models are often tested against empirical VARs or estimated by minimizing the distance between the model's and the VAR impulse response functions. These methodologies require that the data-generating process consistent with the DSGE theoretical model has a VAR representation. This paper discusses the assumptions needed for a finite-order VAR(p) representation of any subset of a DSGE model variables to exist. When a VAR(p) is only an approximation to the true VAR, the paper shows that the truncated VAR(p) may return largely incorrect estimates of the impulse response function. The results do not hinge on an incorrect identification strategy or on small sample bias. But the bias introduced by truncation can lead to bias in the identification of the structural shocks. Identification strategies that are equivalent in the true VAR representation perform differently in the approximating VAR.
  • RePEc:bde:wpaper:0619
Language
  • English
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