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Analyzing the Impact of Carbon Mitigation on the Eurozone’s Trade Dynamics with the US and China

Author

Listed:
  • Pathairat Pastpipatkul

    (Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Terdthiti Chitkasame

    (Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

This study focusses on the transmission of carbon pricing mechanisms in shaping trade dynamics between the Eurozone and key partners: the USA and China. Using Bayesian variable selection methods and a Time-Varying Structural Vector Autoregressions (TV-SVAR) model, the research identifies the key variables impacting EU carbon emissions over time. The results reveal that manufactured products from the US have a diminishing positive impact on EU carbon emissions, suggesting potential exemption from future regulations. In contrast, manufactured goods from the US and petroleum products from China are expected to increase emissions, indicating a need for stricter trade policies. These findings provide strategic insights for policymakers aiming to balance trade and environmental objectives.

Suggested Citation

  • Pathairat Pastpipatkul & Terdthiti Chitkasame, 2025. "Analyzing the Impact of Carbon Mitigation on the Eurozone’s Trade Dynamics with the US and China," Econometrics, MDPI, vol. 13(3), pages 1-18, July.
    • Handle: RePEc:gam:jecnmx:v:13:y:2025:i:3:p:28-:d:1712448
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    References listed on IDEAS

    as
    1. Monjon, Stéphanie & Quirion, Philippe, 2011. "Addressing leakage in the EU ETS: Border adjustment or output-based allocation?," Ecological Economics, Elsevier, vol. 70(11), pages 1957-1971, September.
    2. Khan, Zeeshan & Ali, Muhsin & Jinyu, Liu & Shahbaz, Muhammad & Siqun, Yang, 2020. "Consumption-based carbon emissions and trade nexus: Evidence from nine oil exporting countries," Energy Economics, Elsevier, vol. 89(C).
    3. repec:dau:papers:123456789/7346 is not listed on IDEAS
    4. Rahel Aichele & Gabriel Felbermayr, 2015. "Kyoto and Carbon Leakage: An Empirical Analysis of the Carbon Content of Bilateral Trade," The Review of Economics and Statistics, MIT Press, vol. 97(1), pages 104-115, March.
    5. Kapelner, Adam & Bleich, Justin, 2016. "bartMachine: Machine Learning with Bayesian Additive Regression Trees," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i04).
    Full references (including those not matched with items on IDEAS)

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