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What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?

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  • Laurent Ferrara
  • Pierre Guérin

Abstract

Following the Great Recession, econometric models that better account for un certainty have gained increased attention, and an increasing number of works evaluate the effects of uncertainty shocks. In this paper, we evaluate the impact of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric methodology that allows us to avoid aggregating high-frequency data before estimating models. The impulse response analysis uncovers various salient facts. First, in line with the existing literature, high-frequency uncertainty shocks are associated with a broad-based decline in economic activity. Second, we find that credit and labor market variables react the most to uncertainty shocks. Third, we show that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single-frequency and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context. Finally, we find that some macroeconomic variables exhibit an asymmetric response to uncertainty shocks over the different phases of the business cycle.

Suggested Citation

  • Laurent Ferrara & Pierre Guérin, 2015. "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?," EconomiX Working Papers 2015-12, University of Paris Nanterre, EconomiX.
  • Handle: RePEc:drm:wpaper:2015-12
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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Guest Contribution: “Macroeconomic Effects of High-Frequency Uncertainty Shocks”
      by Menzie Chinn in Econbrowser on 2015-06-30 12:30:51

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    Cited by:

    1. Laurent Ferrara & Stéphane Lhuissier & Fabien Tripier, 2018. "Uncertainty Fluctuations: Measures, Effects and Macroeconomic Policy Challenges," Financial and Monetary Policy Studies, in: Laurent Ferrara & Ignacio Hernando & Daniela Marconi (ed.), International Macroeconomics in the Wake of the Global Financial Crisis, pages 159-181, Springer.
    2. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2020. "Economic Policy Uncertainty Spillovers in Booms and Busts," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(1), pages 125-155, February.
    3. Roberto Casarin & Claudia Foroni & Massimiliano Marcellino & Francesco Ravazzolo, 2016. "Uncertainty Through the Lenses of A Mixed-Frequency Bayesian Panel Markov Switching Model," Working Papers 585, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    4. Piergiorgio Alessandri & Andrea Gazzani & Alejandro Vicondoa, 2021. "The real effects of financial uncertainty shocks: A daily identification approach," Working Papers 61, Red Nacional de Investigadores en Economía (RedNIE).
    5. Rodrigo Cerda & Álvaro Silva & José Tomás Valente, 2018. "Impact of economic uncertainty in a small open economy: the case of Chile," Applied Economics, Taylor & Francis Journals, vol. 50(26), pages 2894-2908, June.
    6. Martin Feldkircher & Florian Huber & Michael Pfarrhofer, 2021. "Measuring the effectiveness of US monetary policy during the COVID‐19 recession," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(3), pages 287-297, July.
    7. Racicot, François-Éric & Théoret, Raymond, 2019. "Hedge fund return higher moments over the business cycle," Economic Modelling, Elsevier, vol. 78(C), pages 73-97.
    8. Matthieu Bussière & Laurent Ferrara & Juliana Milovich, 2017. "Explaining the recent slump in investment: the role of expected demand and uncertainty," Rue de la Banque, Banque de France, issue 44, may..
    9. Kyosuke Chikamatsu, Naohisa Hirakata, Yosuke Kido, Kazuki Otaka, 2018. "Nowcasting Japanese GDPs," Bank of Japan Working Paper Series 18-E-18, Bank of Japan.
    10. Gregoriou, Greg N. & Racicot, François-Éric & Théoret, Raymond, 2021. "The response of hedge fund tail risk to macroeconomic shocks: A nonlinear VAR approach," Economic Modelling, Elsevier, vol. 94(C), pages 843-872.
    11. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2014. "Uncertainty and Monetary Policy in Good and Bad Times," "Marco Fanno" Working Papers 0188, Dipartimento di Scienze Economiche "Marco Fanno".
    12. Ferrara, L. & Istrefi, K., 2016. "Impact des chocs d’incertitude sur l’économie mondiale – Synthèse de conférence," Bulletin de la Banque de France, Banque de France, issue 206, pages 61-68.
    13. Stéphane Lhuissier & Fabien Tripier, 2016. "Do Uncertainty Shocks Always Matter for Business Cycles?," Working Papers 2016-19, CEPII research center.
    14. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    15. Ömer YALÇINKAYA & Ali Kemal ÇELİK, 2021. "The Impact of Global Uncertainties on Economic Growth: Evidence from the US Economy (1996: Q1-2018: Q4)," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 35-54, June.
    16. Emanuele BACCHIOCCHI & Andrea BASTIANIN & Alessandro MISSALE & Eduardo ROSSI, 2016. "Structural Analysis With Mixed Frequency: Monetary Policy, Uncertainty And Gross Capital Flows," Departmental Working Papers 2016-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    17. Andrea Cipollini & Ieva Mikaliunaite, 2021. "Financial distress and real economic activity in Lithuania: a Granger causality test based on mixed-frequency VAR," Empirical Economics, Springer, vol. 61(2), pages 855-881, August.
    18. Chikamatsu, Kyosuke & Hirakata, Naohisa & Kido, Yosuke & Otaka, Kazuki, 2021. "Mixed-frequency approaches to nowcasting GDP: An application to Japan," Japan and the World Economy, Elsevier, vol. 57(C).
    19. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2022. "Uncertainty and monetary policy in good and bad times: A replication of the vector autoregressive investigation by Bloom (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 210-217, January.
    20. Maria Elena Bontempi & Michele Frigeri & Roberto Golinelli & Matteo Squadrani, 2021. "EURQ: A New Web Search‐based Uncertainty Index," Economica, London School of Economics and Political Science, vol. 88(352), pages 969-1015, October.
    21. Dario Bonciani & Andrea Tafuro, 2018. "The Effects of Uncertainty Shocks on Daily Prices," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 89-104, April.
    22. Ömer YALÇINKAYA & Muhammet DAŞTAN, 2020. "Effects of Global Economic, Political and Geopolitical Uncertainties on the Turkish Economy: A SVAR Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 97-116, March.
    23. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
    24. Calmès, Christian & Théoret, Raymond, 2020. "Bank fee-based shocks and the U.S. business cycle," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

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    More about this item

    Keywords

    MIDAS model; Mixed-frequency VAR; Uncertainty.;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • 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

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