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VALIDATING DSGE MODELS WITH SVARS AND HIGH-DIMENSIONAL DYNAMIC FACTOR MODELS

Published online by Cambridge University Press:  13 December 2021

Marco Lippi
Marco Lippi*
Affiliation:
Einaudi Institute for Economics and Finance
*
Address correspondence to Marco Lippi, Einaudi Institute for Economics and Finance, Roma, Italy; e-mail: [email protected].
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Abstract

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A popular validation procedure for Dynamic Stochastic General Equilibrium (DSGE) models consists in comparing the structural shocks and impulse-response functions obtained by estimation-calibration of the DSGE with those obtained in an Structural Vector Autoregressions (SVAR) identified by means of some of the DSGE restrictions. I show that this practice can be seriously misleading when the variables used in the SVAR contain measurement errors. If this is the case, for generic values of the parameters of the DSGE, the shocks estimated in the SVAR are not “made of” the corresponding structural shocks plus measurement error. Rather, each of the SVAR shocks is contaminated by noncorresponding structural shocks. We argue that High-Dimensional Dynamic Factor Models are free from this drawback and are the natural model to use in validation procedures for DSGEs.

Type
ARTICLES
Information
Econometric Theory , Volume 39 , Issue 6: SPECIAL ISSUE IN HONOR OF BENEDIKT M PÖTSCHER , December 2023 , pp. 1273 - 1291
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Footnotes

The author thanks two anonymous referees, the Guest Editor, Manfred Deistler and the Editor, Peter C. B. Phillips, for their very constructive comments, which led to a much improved presentation.

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