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Trend Agnostic One-Step Estimation of DSGE Models

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  • Ferroni Filippo

    (Banque de France)

Abstract

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.

Suggested Citation

  • Ferroni Filippo, 2011. "Trend Agnostic One-Step Estimation of DSGE Models," The B.E. Journal of Macroeconomics, De Gruyter, vol. 11(1), pages 1-36, July.
  • Handle: RePEc:bpj:bejmac:v:11:y:2011:i:1:n:25
    DOI: 10.2202/1935-1690.2248
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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