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F. Ravenna, “Vector Autoregressions and Reduced Form Representations of DSGE Models,” Journal of Monetary Economics, Vol. 54, No. 7, 2007, pp. 2048-2064. doi:10.1016/j.jmoneco.2006.09.002

has been cited by the following article:

• TITLE: On the Identification of Technology Shocks: An Alternative to the Standard Long-Run Method

  AUTHORS: Ufuk Devrim Demirel

  KEYWORDS: Technology Shocks; Long-Run Restrictions; Relative Identification

  JOURNAL NAME: Theoretical Economics Letters, Vol.2 No.5, December 27, 2012

  ABSTRACT: This study proposes an alternative procedure to identify technology shocks using vector autoregressions (VARs). The proposed procedure delivers improved small-sample properties relative to the standard long-run identification method provided that the dynamics of the observed variables can only be captured precisely by an infinite-order VAR. Monte Carlo experiments on artificial data produced by a standard version of the real business cycle model demonstrate that the proposed procedure is associated with smaller average bias and mean square error. These results obtain under a range of specifications regarding the share of technology shocks in overall output variability.