IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_10798.html
   My bibliography  Save this paper

Shipping Cost Uncertainty, Endogenous Regime Switching and the Global Drivers of Inflation

Author

Listed:
  • Christina Anderl
  • Guglielmo Maria Caporale

Abstract

The recent Covid-19 pandemic has disrupted global supply chains and led to large increases in shipping costs. This paper first provides shipping cost mean and uncertainty measures by using the endogenous regime switching model with dynamic feedback and interactions developed by Chang et al. (2023). The uncertainty indicator measures overall risk in the shipping market and is shown to represent a useful addition to the existing set of economic and financial uncertainty indices. Both the shipping cost mean and uncertainty measures are then included in structural VAR models for the US, the UK and the euro area to examine the pass-through to headline CPI, core CPI, PPI and import price inflation vis-à-vis other global and domestic shocks. The results suggest that shipping cost uncertainty shocks have sizeable effects on all inflation measures and are characterised by a stronger pass-through than that of other domestic or global shocks. Unlike the latter, they also affect significantly core CPI inflation. These findings imply that shipping cost mean and uncertainty should also be considered by policymakers when assessing the global drivers of inflation.

Suggested Citation

  • Christina Anderl & Guglielmo Maria Caporale, 2023. "Shipping Cost Uncertainty, Endogenous Regime Switching and the Global Drivers of Inflation," CESifo Working Paper Series 10798, CESifo.
    • Handle: RePEc:ces:ceswps:_10798
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10798.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Julian di Giovanni & Ṣebnem Kalemli-Özcan & Alvaro Silva & Muhammed A. Yildirim, 2022. "Global Supply Chain Pressures, International Trade, and Inflation," NBER Working Papers 30240, National Bureau of Economic Research, Inc.
    3. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    4. Nektarios A. Michail & Konstantinos D. Melas & Lena Cleanthous, 2022. "The relationship between shipping freight rates and inflation in the Euro Area," International Economics, CEPII research center, issue 172, pages 40-49.
    5. Carrière-Swallow, Yan & Deb, Pragyan & Furceri, Davide & Jiménez, Daniel & Ostry, Jonathan D., 2023. "Shipping costs and inflation," Journal of International Money and Finance, Elsevier, vol. 130(C).
    6. Nicholas Apergis & James E. Payne, 2013. "New Evidence on the Information and Predictive Content of the Baltic Dry Index," IJFS, MDPI, vol. 1(3), pages 1-19, July.
    7. Uhlig, Harald, 1994. "What Macroeconomists Should Know about Unit Roots: A Bayesian Perspective," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 645-671, August.
    8. Gianluca Benigno & Julian di Giovanni & Jan J. J. Groen & Adam I. Noble, 2022. "The GSCPI: A New Barometer of Global Supply Chain Pressures," Staff Reports 1017, Federal Reserve Bank of New York.
    9. Morten O. Ravn & Harald Uhlig, 2002. "On adjusting the Hodrick-Prescott filter for the frequency of observations," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 371-375.
    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. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," Economics Series Working Papers 1033, University of Oxford, Department of Economics.
    2. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2019. "Identification of Financial Factors in Economic Fluctuations," The Economic Journal, Royal Economic Society, vol. 129(617), pages 311-337.
    3. Klug, Thorsten & Mayer, Eric & Schuler, Tobias, 2022. "The corporate saving glut and the current account in Germany," Journal of International Money and Finance, Elsevier, vol. 121(C).
    4. Ben Zeev, Nadav, 2018. "What can we learn about news shocks from the late 1990s and early 2000s boom-bust period?," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 94-105.
    5. Christian Glocker & Pascal Towbin, 2012. "The Macroeconomic Effects of Reserve Requirements," WIFO Working Papers 420, WIFO.
    6. Tim Berg, 2012. "Did monetary or technology shocks move euro area stock prices?," Empirical Economics, Springer, vol. 43(2), pages 693-722, October.
    7. Breitenlechner, Maximilian & Scharler, Johann, 2016. "The Bank Lending Channel and the Market for Banks' Wholesale Funding," VfS Annual Conference 2016 (Augsburg): Demographic Change 145679, Verein für Socialpolitik / German Economic Association.
    8. Nadav Ben Zeev, 2019. "Is There A Single Shock That Drives The Majority Of Business Cycle Fluctuations?," Working Papers 1906, Ben-Gurion University of the Negev, Department of Economics.
    9. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.
    10. Carrillo-Maldonado, Paul & Díaz-Cassou, Javier, 2023. "An anatomy of external shocks in the Andean region," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    11. Pooyan Amir‐Ahmadi & Thorsten Drautzburg, 2021. "Identification and inference with ranking restrictions," Quantitative Economics, Econometric Society, vol. 12(1), pages 1-39, January.
    12. Breitenlechner, Max & Mathy, Gabriel P. & Scharler, Johann, 2021. "Decomposing the U.S. Great Depression: How important were loan supply shocks?," Explorations in Economic History, Elsevier, vol. 79(C).
    13. Martin Geiger & Johann Scharler, 2018. "How do consumers interpret the macroeconomic effects of oil price fluctuations? Evidence from U.S. survey data," Working Papers 2018-13, Faculty of Economics and Statistics, Universität Innsbruck.
    14. Canova, Fabio & Ferroni, Filippo, 2020. "A hitchhiker guide to empirical macro models," CEPR Discussion Papers 15446, C.E.P.R. Discussion Papers.
    15. Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner, 2020. "Uniform Priors for Impulse Responses," Working Papers 22-30, Federal Reserve Bank of Philadelphia.
    16. Glocker, Christian & Towbin, Pascal, 2015. "Reserve requirements as a macroprudential instrument – Empirical evidence from Brazil," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 158-176.
    17. Bańbura, Marta & Bobeica, Elena & Martínez Hernández, Catalina, 2023. "What drives core inflation? The role of supply shocks," Working Paper Series 2875, European Central Bank.
    18. Paul Levine & Joseph Pearlman & Alessio Volpicella & Bo Yang, 2022. "The Use and Mis-Use of SVARs for Validating DSGE Models," School of Economics Discussion Papers 0522, School of Economics, University of Surrey.
    19. Ha, Jongrim & Kose, M. Ayhan & Ohnsorge, Franziska & Yilmazkuday, Hakan, 2023. "Understanding the global drivers of inflation: How important are oil prices?11We would like to thank Xuguang Simon Sheng, Guest Editor, and two anonymous reviewers for their detailed feedback. We also," Energy Economics, Elsevier, vol. 127(PA).
    20. Breitenlechner, Max & Scharler, Johann & Sindermann, Friedrich, 2016. "Banks’ external financing costs and the bank lending channel: Results from a SVAR analysis," Journal of Financial Stability, Elsevier, vol. 26(C), pages 228-246.

    More about this item

    Keywords

    shipping cost uncertainty; inflation pass-through; endogenous regime switching;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ces:ceswps:_10798. 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: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.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.