(Translated by https://www.hiragana.jp/)
The relationship between shipping freight rates and inflation in the Euro Area
IDEAS home Printed from https://ideas.repec.org/p/cyb/wpaper/2022-2.html
   My bibliography  Save this paper

The relationship between shipping freight rates and inflation in the Euro Area

Author

Listed:
  • Nektarios A. Michail

    (Central Bank of Cyprus)

  • Konstantinos D. Melas

    (Metropolitan College, Greece and University of Western Macedonia, Kastoria, Greece)

  • Lena Cleanthous

    (Central Bank of Cyprus)

Abstract

Consumer inflation across the globe has rebounded during 2021, also as a result of supply side disruptions, one of which is the increase in freight costs. To elaborate on the relationship between inflation and shipping costs, we employ a Vector Error Correction Model (VECM) and use disaggregated monthly data from January 2009 to August 2021, using both constant tax and the standard price indices. Following a shock in freight rates, the most hard-hit sectors appear to be garments and major household appliances, items that have traditionally been manufactured outside the euro area. In addition, using a threshold regression methodology we show that when freight rates rise more than $1,300-$1,500 per day, the sensitivity of inflation to freight changes increases.

Suggested Citation

  • Nektarios A. Michail & Konstantinos D. Melas & Lena Cleanthous, 2022. "The relationship between shipping freight rates and inflation in the Euro Area," Working Papers 2022-2, Central Bank of Cyprus.
    • Handle: RePEc:cyb:wpaper:2022-2
    as

    Download full text from publisher

    File URL: https://www.centralbank.cy/images/media/pdf/The-relationship-between-shipping-freight-rates-and-inflation-in-the-Euro-Area.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    3. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    4. Yao, Yi-Ching, 1988. "Estimating the number of change-points via Schwarz' criterion," Statistics & Probability Letters, Elsevier, vol. 6(3), pages 181-189, February.
    5. Sheth, Jagdish, 2020. "Impact of Covid-19 on consumer behavior: Will the old habits return or die?," Journal of Business Research, Elsevier, vol. 117(C), pages 280-283.
    6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    7. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(3), pages 315-352, June.
    8. Jushan Bai & Pierre Perron, 2003. "Critical values for multiple structural change tests," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 72-78, June.
    9. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    10. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    11. Ngoc Thien Anh Pham & Nicholas Sim, 2020. "Shipping cost and development of the landlocked developing countries: Panel evidence from the common correlated effects approach," The World Economy, Wiley Blackwell, vol. 43(4), pages 892-920, April.
    12. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Anderl, Christina & Caporale, Guglielmo Maria, 2024. "Shipping cost uncertainty, endogenous regime switching and the global drivers of inflation," International Economics, Elsevier, vol. 178(C).
    2. Sologon, Denisa Maria & O'Donoghue, Cathal & Linden, Jules & Kyzyma, Iryna & Loughrey, Jason, 2022. "Welfare and Distributional Impact of Soaring Prices in Europe," IZA Discussion Papers 15738, Institute of Labor Economics (IZA).
    3. Nektarios A. Michail & Kyriaki G. LouKa, 2023. "The inefficiency of Quantitative Easing in the Euro Area," Working Papers 2023-3, Central Bank of Cyprus.
    4. Mrudul Y. Jani & Manish R. Betheja & Urmila Chaudhari & Biswajit Sarkar, 2023. "Effect of Future Price Increase for Products with Expiry Dates and Price-Sensitive Demand under Different Payment Policies," Mathematics, MDPI, vol. 11(2), pages 1-31, January.
    5. Omid Asadollah & Linda Schwartz Carmy & Md. Rezwanul Hoque & Hakan Yilmazkuday, 2024. "Geopolitical risk, supply chains, and global inflation," The World Economy, Wiley Blackwell, vol. 47(8), pages 3450-3486, August.

    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. Jouini, Jamel & Boutahar, Mohamed, 2005. "Evidence on structural changes in U.S. time series," Economic Modelling, Elsevier, vol. 22(3), pages 391-422, May.
    2. Maria Siranova & Menbere Workie Tiruneh, 2016. "The determinants of errors and omissions in a small and open economy: The case of Slovakia," Working Papers wp73, Institute of Economic Research, Slovak Academy of Sciences, revised 08 Apr 2016.
    3. Pavel Kotyza & Katarzyna Czech & Michał Wielechowski & Luboš Smutka & Petr Procházka, 2021. "Sugar Prices vs. Financial Market Uncertainty in the Time of Crisis: Does COVID-19 Induce Structural Changes in the Relationship?," Agriculture, MDPI, vol. 11(2), pages 1-16, January.
    4. Samih Antoine Azar & Angelic Salha, 2017. "The Bias in the Long Run Relation between the Prices of BRENT and West Texas Intermediate Crude Oils," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 44-54.
    5. P Muthuramu & T Uma Maheswari, 2019. "Tests for Structural Breaks in Time Series Analysis: A Review of Recent Development," Shanlax International Journal of Economics, Shanlax Journals, vol. 7(4), pages 66-79, September.
    6. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
    7. Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2014. "Causality and contagion in EMU sovereign debt markets," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 12-27.
    8. Devi, P. Indira & Shanmugam, K.R. & Jayasree, M.G., 2012. "Compensating Wages for Occupational Risks of Farm Workers in India," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 67(2), pages 1-12.
    9. Dupuy, Arnaud & Marey, Philip S., 2008. "Shifts and twists in the relative productivity of skilled labor," Journal of Macroeconomics, Elsevier, vol. 30(2), pages 718-735, June.
    10. Hervé Le Bihan, 2004. "Tests de ruptures : une application au PIB tendanciel français," Économie et Prévision, Programme National Persée, vol. 163(2), pages 133-154.
    11. Mohitosh Kejriwal, 2020. "A Robust Sequential Procedure for Estimating the Number of Structural Changes in Persistence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 669-685, June.
    12. Kurozumi, Eiji & Tuvaandorj, Purevdorj, 2011. "Model selection criteria in multivariate models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 164(2), pages 218-238, October.
    13. Alessandro Casini & Pierre Perron, 2018. "Structural Breaks in Time Series," Boston University - Department of Economics - Working Papers Series WP2019-02, Boston University - Department of Economics.
    14. Bajo-Rubio, Oscar & Diaz-Roldan, Carmen & Esteve, Vicente, 2007. "Change of regime and Phillips curve stability: The case of Spain, 1964-2002," Journal of Policy Modeling, Elsevier, vol. 29(3), pages 453-462.
    15. Giorgio Canarella & Rangan Gupta & Stephen M. Miller & Stephen K. Pollard, 2019. "Unemployment rate hysteresis and the great recession: exploring the metropolitan evidence," Empirical Economics, Springer, vol. 56(1), pages 61-79, January.
    16. repec:hum:wpaper:sfb649dp2014-060 is not listed on IDEAS
    17. Francis Declerck & Jean-Pierre Indjehagopian & Frédéric Lantz, 2020. "Dynamics of biofuel prices on the European market: Impact of the EU environmental policy on the resources markets," Working Papers hal-02487491, HAL.
    18. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    19. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    20. Marta Gómez-Puig & Simón Sosvilla-Rivero, 2015. "“On the bi-directional causal relationship between public debt and economic growth in EMU countries”," IREA Working Papers 201512, University of Barcelona, Research Institute of Applied Economics, revised May 2015.
    21. Telli, Şahin & Chen, Hongzhuan, 2020. "Structural breaks and trend awareness-based interaction in crypto markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).

    More about this item

    Keywords

    inflation; shipping; freight rates; supply shock;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

    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:cyb:wpaper:2022-2. 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: Anna Markidou (email available below). General contact details of provider: https://edirc.repec.org/data/cbcgvcy.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.