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Macroeconomic Shocks and the Business Cycle: Evidence from a Structural Factor Model

Author

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  • Mario Forni

  • Luca Gambetti

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 six. Focusing on the four-shock specification, we identify, using sign restrictions, two non-policy shocks, demand and supply, and two policy shocks, monetary and fiscal. 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) Policy matters: Both monetary and fiscal policy shocks have sizeable effects on output and prices, with little evidence of crowding out; 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, 2010. "Macroeconomic Shocks and the Business Cycle: Evidence from a Structural Factor Model," Center for Economic Research (RECent) 040, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    • Handle: RePEc:mod:recent:040
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    Cited by:

    1. Kerssenfischer, Mark, 2017. "The effects of US monetary policy shocks: Applying external instrument identification to a dynamic factor model," Discussion Papers 08/2017, Deutsche Bundesbank.
    2. Matteo Barigozzi & Antonio M. Conti & Matteo Luciani, 2014. "Do Euro Area Countries Respond Asymmetrically to the Common Monetary Policy?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 693-714, October.
    3. Li, Hongjun & Li, Qi & Shi, Yutang, 2017. "Determining the number of factors when the number of factors can increase with sample size," Journal of Econometrics, Elsevier, vol. 197(1), pages 76-86.
    4. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    5. Olli Palm'en, 2020. "Inflation Dynamics of Financial Shocks," Papers 2006.03301, arXiv.org.
    6. Leiva-Leon Danilo, 2014. "Real vs. nominal cycles: a multistate Markov-switching bi-factor approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(5), pages 557-580, December.
    7. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," Working Papers ECARES ECARES 2011-019, ULB -- Universite Libre de Bruxelles.
    8. Barnett, William A. & Chauvet, Marcelle & Leiva-Leon, Danilo, 2014. "Real-Time Nowcasting Nominal GDP Under Structural Break," MPRA Paper 53699, University Library of Munich, Germany.
    9. Ángel Cuevas & Enrique Quilis, 2012. "A factor analysis for the Spanish economy," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 3(3), pages 311-338, September.
    10. Farhad Taghizadeh‐Hesary & Naoyuki Yoshino & Sayoko Shimizu, 2020. "The impact of monetary and tax policy on income inequality in Japan," The World Economy, Wiley Blackwell, vol. 43(10), pages 2600-2621, October.
    11. Colin Ellis & Haroon Mumtaz & Pawel Zabczyk, 2014. "What Lies Beneath? A Time‐varying FAVAR Model for the UK Transmission Mechanism," Economic Journal, Royal Economic Society, vol. 0(576), pages 668-699, May.
    12. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.
    13. Jin, Xisong & Nadal De Simone, Francisco, 2020. "Monetary policy and systemic risk-taking in the Euro area investment fund industry: A structural factor-augmented vector autoregression analysis," Journal of Financial Stability, Elsevier, vol. 49(C).
    14. Casalis, André & Krustev, Georgi, 2022. "Cyclical drivers of euro area consumption: What can we learn from durable goods?," Journal of International Money and Finance, Elsevier, vol. 120(C).
    15. Ductor, Lorenzo & Leiva-Leon, Danilo, 2016. "Dynamics of global business cycle interdependence," Journal of International Economics, Elsevier, vol. 102(C), pages 110-127.

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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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