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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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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 24509.

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Date of creation: 01 May 2010
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Handle: RePEc:pra:mprapa:24509

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Keywords: Bayesian Analysis; DSGE Models; Vector Autoregressions; MonteCarlo experiments;

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