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Trend Agnostic One-Step Estimation of DSGE Models

Listed author(s):
  • Ferroni Filippo

    ()

    (Banque de France)

DSGE models are currently estimated with a two-step approach: the data is first transformed and then DSGE structural parameters are estimated. Two-step procedures have problems, ranging from component misspecification to incorrect assumptions about the correlation between cyclical and non-cyclical components. In this paper, I present a one-step method, where DSGE structural parameters are jointly estimated with filtering parameters. First, I illustrate the properties of the one-step procedures using simulated data. Then, I show that different data transformations imply different structural estimates and that two-step approaches lack a statistical-based criterion to select amongst them. The one-step approach allows to choose the most likely specification of the non-cyclical component for individual series and/or to construct robust estimates by Bayesian averaging. The role of the investment specific shock as source of GDP volatility is reconsidered.

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Article provided by De Gruyter in its journal The B.E. Journal of Macroeconomics.

Volume (Year): 11 (2011)
Issue (Month): 1 (July)
Pages: 1-36

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Handle: RePEc:bpj:bejmac:v:11:y:2011:i:1:n:25
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