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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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    References listed on IDEAS

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    Blog mentions

    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. 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.
    2. repec:bfr:rueban:2017:44 is not listed on IDEAS
    3. 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.
    4. 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..
    5. 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.
    6. repec:spr:jbuscr:v:14:y:2018:i:1:d:10.1007_s41549-018-0024-2 is not listed on IDEAS

    More about this item

    Keywords

    MIDAS model; Mixed-frequency VAR; Uncertainty.;

    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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