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DSGE Model Validation in a Bayesian Framework: an Assessment

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  • Paccagnini, Alessia

Abstract

This paper presents the concept of Model Validation applied to a Dynamic Stochastic General equilibrium Model (DSGE). The main problem discussed is the approximation of the statistical representation for a DSGE model when not all endogenous variables are observable. MonteCarlo experiments in artificial world are implemented to assess this problem by using the DSGE-VAR. Two Data Generating Processes are compared: a forward-looking and a backward-looking model. These experiments are followed by an empirical analysis with real world data for the US economy.

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  • Paccagnini, Alessia, 2010. "DSGE Model Validation in a Bayesian Framework: an Assessment," MPRA Paper 24509, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:24509
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    2. Roberta Cardani & Alessia Paccagnini & Stelios D. Bekiros, 2017. "The Effectiveness of Forward Guidance in an Estimated DSGE Model for the Euro Area: the Role of Expectations," Working Papers 201701, School of Economics, University College Dublin.

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    More about this item

    Keywords

    Bayesian Analysis; DSGE Models; Vector Autoregressions; MonteCarlo experiments;
    All these keywords.

    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
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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