Trend Agnostic One-Step Estimation of DSGE Models

Filippo Ferroni 1 , 1
  • 1 Banque de France, filippo.ferroni@banque-france.fr

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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The B.E. Journal of Macroeconomics publishes significant research and scholarship in theoretical and applied macroeconomics. The range of topics includes business cycle research, economic growth, and monetary economics, as well as topics drawn from the substantial areas of overlap between macroeconomics and international economics, labor economics, finance, development economics, political economy, public economics, econometric theory.

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