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Home > Research > Working Paper No. 527: Can a data-rich environment help identify the sources of model misspecification? - Francesca Monti
 

Working Paper No. 527: Can a data-rich environment help identify the sources of model misspecification? - Francesca Monti

27 March 2015

​Working Paper No. 527
Can a data-rich environment help identify the sources of model misspecification?
Francesca Monti

This paper proposes a method for detecting the sources of misspecification in a dynamic stochastic general equilibrium (DSGE) model based on testing, in a data-rich environment, the exogeneity of the variables of the DSGE with respect to some auxiliary variables. Finding evidence of non-exogeneity implies misspecification, and finding that some specific variables help predict certain shocks can shed light on the dimensions along which the model is misspecified. Forecast error variance decomposition analysis then helps assess the relevance of the missing channels. The paper puts the proposed methodology to work both in a controlled experiment - by running a Monte Carlo simulation with a known data-generating process - and using a state-of-the-art model and US data up to 2011.

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