IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/16430.html

The Transmission of Keynesian Supply Shocks

Author

Listed:
  • Ferrero, Andrea
  • Cesa-Bianchi, Ambrogio

Abstract

Sectoral supply shocks can trigger shortages in aggregate demand when strong sectoral complementarities are at play. US data on sectoral output and prices offer support to this notion of "Keynesian supply shocks" and their underlying transmission mechanism. Demand shocks derived from standard identification schemes using aggregate data can originate from sectoral supply shocks that spillover to other sectors via a Keynesian supply mechanism. This finding is a regular feature of the data and is independent of the effects of the 2020 pandemic. In a New Keynesian model with input-output network calibrated to 3-digit US data, sectoral productivity shocks generate the same pattern for output growth and inflation as observed in the data. The degree of sectoral interconnection, both upstream and downstream, and price stickiness are key determinants of the strength of the mechanism. Sectoral shocks may account for a larger fraction of business cycle fluctuations than previously thought.

Suggested Citation

  • Ferrero, Andrea & Cesa-Bianchi, Ambrogio, 2021. "The Transmission of Keynesian Supply Shocks," CEPR Discussion Papers 16430, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:16430
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP16430
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. is not listed on IDEAS
    2. Chan, Jenny & Diz, Sebastian & Kanngiesser, Derrick, 2024. "Energy prices and household heterogeneity: Monetary policy in a Gas-TANK," Journal of Monetary Economics, Elsevier, vol. 147(S).
    3. Andrea Cipollini & Fabio Parla, 2023. "Climate risk and investment in equities in Europe: a Panel SVAR approach," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0093, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    4. Machado, Caio, 2024. "Uneven recessions and optimal firm subsidies," Journal of Public Economics, Elsevier, vol. 239(C).
    5. Anastasiia Antonova & Mykhailo Matvieiev & Céline Poilly, 2024. "Supply Shocks in the Fog: The Role of Endogenous Uncertainty," AMSE Working Papers 2427, Aix-Marseille School of Economics, France.
    6. Marko Mlikota, 2022. "Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications," Papers 2211.13610, arXiv.org, revised Jan 2026.
    7. Catherine L. Mann & Lennart Brandt, 2022. "On Returning Inflation to Target," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 57(2), pages 87-92, March.
    8. De Graeve, Ferre & Schneider, Jan David, 2023. "Identifying sectoral shocks and their role in business cycles," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 124-141.
    9. Durand, Luigi & Fornero, Jorge Alberto, 2024. "Estimating the output gap in times of COVID-19," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 5(4).
    10. Stefan Schiman-Vukan, 2023. "Austria's (Over)Inflation and Its Main Sources," WIFO Research Briefs 9, WIFO.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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

    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:cpr:ceprdp:16430. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    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.