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What Are the Macroeconomic Effects of High-Frequency Uncertainty Shocks

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  • Laurent Ferrara
  • Pierre Guérin

Abstract

This paper evaluates the effects of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables that are representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric models, which allows us to deal with data of different sampling frequencies. We find that credit and labor market variables react the most to uncertainty shocks in that they exhibit a prolonged negative response to such shocks. When examining detailed investment sub-categories, our estimates suggest that the most irreversible investment projects are the most affected by uncertainty shocks. We also find that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single- and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context.

Suggested Citation

  • Laurent Ferrara & Pierre Guérin, 2016. "What Are the Macroeconomic Effects of High-Frequency Uncertainty Shocks," Staff Working Papers 16-25, Bank of Canada.
  • Handle: RePEc:bca:bocawp:16-25
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Bacchiocchi, Emanuele & Bastianin, Andrea & Missale, Alessandro & Rossi, Eduardo, 2016. "Structural analysis with mixed frequencies: monetary policy, uncertainty and gross capital flows," Working Papers 2016-04, Joint Research Centre, European Commission (Ispra site).
    3. repec:bfr:rueban:2017:44 is not listed on IDEAS
    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. 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".
    6. Magnus Reif, 2018. "Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates," ifo Working Paper Series 265, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    7. 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.
    8. Kyosuke Chikamatsu, Naohisa Hirakata, Yosuke Kido, Kazuki Otaka, 2018. "Nowcasting Japanese GDPs," Bank of Japan Working Paper Series 18-E-18, Bank of Japan.
    9. repec:spr:jbuscr:v:14:y:2018:i:1:d:10.1007_s41549-018-0024-2 is not listed on IDEAS
    10. repec:eee:ecmode:v:78:y:2019:i:c:p:73-97 is not listed on IDEAS

    More about this item

    Keywords

    Business fluctuations and cycles; Econometric and statistical methods;

    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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