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Policy and Business Cycle Shocks: A Structural Factor Model Representation of the US Economy

Author

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  • Mario Forni

    (Dipartimento di Economia Marco Biagi and ReCent, Università di Modena e Reggio Emilia, 41100 Modena, Italy
    Center for Economic Policy Research, London EC1V 0DX, UK)

  • Luca Gambetti

    (Departament d’Economia i d’Historia Economica, Universitat Autònoma de Barcelona, 08290 Cerdanyola del Vallès, Spain
    Barcelona GSE, 08005 Barcelona, Spain
    Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche, Università di Torino, 10124 Torino, Italy
    Collegio Carlo Alberto, 10122 Torino, Italy)

Abstract

We use a dynamic factor model to provide a semi-structural representation for 101 quarterly US macroeconomic series. We find that (i) the US economy is well described by a number of structural shocks between two and five. Focusing on the four-shock specification, we identify, using sign restrictions, two policy shocks, monetary and fiscal, and two non-policy shocks, demand and supply. We obtain the following results. (ii) Both supply and demand shocks are important sources of fluctuations; supply prevails for GDP, while demand prevails for employment and inflation. (ii) Monetary and fiscal policy shocks have sizable effects on output and prices, with no evidence of crowding-out of private aggregate demand components; both monetary and fiscal authorities implement important systematic countercyclical policies reacting to demand shocks. (iii) Negative demand shocks have a large long-run positive effect on productivity, consistently with the Schumpeterian “cleansing” view of recessions.

Suggested Citation

  • Mario Forni & Luca Gambetti, 2021. "Policy and Business Cycle Shocks: A Structural Factor Model Representation of the US Economy," JRFM, MDPI, vol. 14(8), pages 1-21, August.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:8:p:371-:d:613706
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    References listed on IDEAS

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    Cited by:

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    3. Juho Koistinen & Bernd Funovits, 2022. "Estimation of Impulse-Response Functions with Dynamic Factor Models: A New Parametrization," Papers 2202.00310, arXiv.org, revised Feb 2022.

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