Informing DSGE Models Through Dynamic Factor Models

ABSTRACT Structural dynamic factor models (SDFM) represent a reliable tool to inform the construction of dynamic stochastic general equilibrium (DSGE) models. The reason is that the log‐linear solution of a DSGE model has a factor structure which ensures consistency between the representations of the two models. We assess the usefulness of SDFM for DSGE analysis by means of simulations. Using a standard DSGE model as the data generating process, we show that the factor model always provides accurate estimates of the impulse response functions. As an application, we reassess the literature studying the response of hours to technology shock. An additional application studies the effects of monetary policy.

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Publication Details

Journal
Journal of Applied Econometrics
Published
2025-03-25
DOI
https://doi.org/10.1002/jae.3122
Citations
1
Primary Topic
Monetary Policy and Economic Impact
Type
article
Field-Weighted Citation Impact
3.09
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article

Informing DSGE Models Through Dynamic Factor Models

Mario Forni, Marco Lippi, Luca Sala, Luca Gambetti
1 citations
Journal of Applied Econometrics
Monetary Policy and Economic Impact
3.09
article

Informing DSGE Models Through Dynamic Factor Models

Mario Forni, Marco Lippi, Luca Sala, Luca Gambetti
article en
1 citations

Abstract

ABSTRACT Structural dynamic factor models (SDFM) represent a reliable tool to inform the construction of dynamic stochastic general equilibrium (DSGE) models. The reason is that the log‐linear solution of a DSGE model has a factor structure which ensures consistency between the representations of the two models. We assess the usefulness of SDFM for DSGE analysis by means of simulations. Using a standard DSGE model as the data generating process, we show that the factor model always provides accurate estimates of the impulse response functions. As an application, we reassess the literature studying the response of hours to technology shock. An additional application studies the effects of monetary policy.

Journal of Applied EconometricsVol. 40(5)
University of Modena and Reggio Emilia (IT), Universitat Autònoma de Barcelona (ES), Einaudi Institute for Economics and Finance (IT), University of Turin (IT), Bocconi University (IT)
Openalex Percentile: Top 12%
Monetary Policy and Economic Impact
3.09
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