DSGE Model Validation in a Bayesian Framework: an Assessment Report as inadecuate




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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.



Item Type: MPRA Paper -

Original Title: DSGE Model Validation in a Bayesian Framework: an Assessment-

Language: English-

Keywords: Bayesian Analysis, DSGE Models, Vector Autoregressions, MonteCarlo experiments-

Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space ModelsC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: GeneralC - Mathematical and Quantitative Methods > C0 - General > C01 - EconometricsC - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General-





Author: Paccagnini, Alessia

Source: https://mpra.ub.uni-muenchen.de/24509/







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