IDEAS home Printed from https://ideas.repec.org/p/pad/wpaper/0288.html
   My bibliography  Save this paper

Sectoral Uncertainty

Author

Listed:
  • Efrem Castelnuovo

    (University of Padova, CESifo, and CAMA)

  • Kerem Tuzcuoglu

    (Bank of Canada)

  • Luis Uzeda

    (Bank of Canada)

Abstract

We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a large dataset of disaggregated industrial production series for the US economy. Our results indicate that common uncertainty and uncertainty linked to nondurable goods both recorded their pre-pandemic global peaks during the 1973-75 recession. In contrast, durable goods uncertainty recorded its pre-pandemic peak during the global financial crisis of 2008-09. Vector autoregression exercises identify unexpected changes in durable goods uncertainty as drivers of downturns that are both economically and statistically significant, while unexpected hikes in nondurable goods uncertainty are expansionary. Our findings suggest that: (i) uncertainty is heterogeneous at a sectoral level; and (ii) durable goods uncertainty may drive some business cycle effects typically attributed to aggregate uncertainty.

Suggested Citation

  • Efrem Castelnuovo & Kerem Tuzcuoglu & Luis Uzeda, 2022. "Sectoral Uncertainty," "Marco Fanno" Working Papers 0288, Dipartimento di Scienze Economiche "Marco Fanno".
  • Handle: RePEc:pad:wpaper:0288
    as

    Download full text from publisher

    File URL: https://economia.unipd.it/sites/economia.unipd.it/files/20220288.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
    2. Michael W. McCracken & Serena Ng, 2016. "FRED-MD: A Monthly Database for Macroeconomic Research," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
    3. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    4. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    5. Omori, Yasuhiro & Chib, Siddhartha & Shephard, Neil & Nakajima, Jouchi, 2007. "Stochastic volatility with leverage: Fast and efficient likelihood inference," Journal of Econometrics, Elsevier, vol. 140(2), pages 425-449, October.
    6. Leduc, Sylvain & Liu, Zheng, 2016. "Uncertainty shocks are aggregate demand shocks," Journal of Monetary Economics, Elsevier, vol. 82(C), pages 20-35.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Karaki, Mohamad B. & Rangaraju, Sandeep Kumar, 2023. "The confidence channel of U.S. financial uncertainty: Evidence from industry-level data," Economic Modelling, Elsevier, vol. 129(C).
    3. Eksi, Ozan & Onur Tas, Bedri Kamil, 2022. "Time-varying effect of uncertainty shocks on unemployment," Economic Modelling, Elsevier, vol. 110(C).
    4. Lu, Yunzhi & Li, Jie & Yang, Haisheng, 2023. "Time-varying impacts of monetary policy uncertainty on China's housing market," Economic Modelling, Elsevier, vol. 118(C).
    5. Rivolta, Giulia & Trecroci, Carmine, 2020. "Measuring the effects of U.S. uncertainty and monetary conditions on EMEs' macroeconomic dynamics," MPRA Paper 99403, University Library of Munich, Germany.
    6. Dew-Becker, Ian & Giglio, Stefano & Kelly, Bryan, 2021. "Hedging macroeconomic and financial uncertainty and volatility," Journal of Financial Economics, Elsevier, vol. 142(1), pages 23-45.
    7. Brianti, Marco, 2021. "Financial Shocks, Uncertainty Shocks, and Monetary Policy Trade-Offs," Working Papers 2021-5, University of Alberta, Department of Economics.
    8. Breitenlechner, Max & Geiger, Martin & Scharler, Johann, 2022. "Bank liquidity and the propagation of uncertainty in the U.S," Finance Research Letters, Elsevier, vol. 46(PB).
    9. Niko Hauzenberger & Florian Huber & Gary Koop & James Mitchell, 2020. "Bayesian Modelling of TVP-VARs Using Regression Trees," Working Papers 2308, University of Strathclyde Business School, Department of Economics, revised Aug 2023.
    10. Tosapol Apaitan & Pongsak Luangaram & Pym Manopimoke, 2022. "Uncertainty in an emerging market economy: evidence from Thailand," Empirical Economics, Springer, vol. 62(3), pages 933-989, March.
    11. Boyan Jovanovic & Sai Ma, 2022. "Uncertainty and Growth Disasters," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 33-64, April.
    12. Haque, Qazi & Magnusson, Leandro M., 2021. "Uncertainty shocks and inflation dynamics in the U.S," Economics Letters, Elsevier, vol. 202(C).
    13. Caggiano, Giovanni & Castelnuovo, Efrem & Delrio, Silvia & Kima, Richard, 2021. "Financial uncertainty and real activity: The good, the bad, and the ugly," European Economic Review, Elsevier, vol. 136(C).
    14. Suah, Jing Lian, 2022. "Impact of uncertainty and exchange rate shocks: Theory and global empirics," Journal of Asian Economics, Elsevier, vol. 82(C).
    15. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
    16. Choi Sangyup & Yoon Chansik, 2022. "Uncertainty, Financial Markets, and Monetary Policy over the Last Century," The B.E. Journal of Macroeconomics, De Gruyter, vol. 22(2), pages 397-434, June.
    17. Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2017. "Estimating the real effects of uncertainty shocks at the Zero Lower Bound," European Economic Review, Elsevier, vol. 100(C), pages 257-272.
    18. Luca Gambetti & Dimitris Korobilis & John D. Tsoukalas & Francesco Zanetti, 2023. "Agreed and Disagreed Uncertainty," Working Paper series 23-01, Rimini Centre for Economic Analysis.
    19. Giovanni Pellegrino & Federico Ravenna & Gabriel Züllig, 2021. "The Impact of Pessimistic Expectations on the Effects of COVID‐19‐Induced Uncertainty in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(4), pages 841-869, August.
    20. Iseringhausen, Martin & Petrella, Ivan & Theodoridis, Konstantinos, 2021. "Aggregate Skewness and the Business Cycle," Cardiff Economics Working Papers E2021/30, Cardiff University, Cardiff Business School, Economics Section.

    More about this item

    Keywords

    Dynamic Factor; Uncertainty; Stochastic Volatility; Sectors;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pad:wpaper:0288. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Raffaele Dei Campielisi (email available below). General contact details of provider: https://edirc.repec.org/data/dspadit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.