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Pollution havens: International empirical evidence using a shadow price measure of climate policy stringency

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  • Hille, Erik

Abstract

Given the ambiguous empirical results of previous research, this paper tests whether support for a climate policy induced pollution haven effect and the pollution haven hypothesis can be found. Unlike the majority of previous studies, the analysis is based on international panel data and includes several methodological novelties: By arguing that trade flows of dirty goods to less polluting sectors may also be influenced by changes in policy stringency, trade information on primary, secondary, and tertiary sectors are included. In order to clearly differentiate between dirty sectors and sectors with high pollution abatement costs, separate measures for pollution intensity and policy stringency are implemented. For the latter an internationally comparable, sector-specific measure of climate policy stringency is derived using a shadow price approach. Endogeneity between a country s trade openness and its trade flows is addressed by estimating a gravity-based instrumental variable. The results provide evidence for a stronger pollution haven effect regarding carbon dioxide intensive and emission relevant energy intensive sectors. However, the impact of climate policy on polluting sectors seems to be rather limited as a distinct pollution haven effect for gross energy intensive sectors cannot be found. Similarly, no support for the stronger pollution haven hypothesis is revealed.

Suggested Citation

  • Hille, Erik, 2014. "Pollution havens: International empirical evidence using a shadow price measure of climate policy stringency," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100551, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc14:100551
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    Cited by:

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    3. Hille, Erik & Shahbaz, Muhammad & Moosa, Imad, 2019. "The impact of FDI on regional air pollution in the Republic of Korea: A way ahead to achieve the green growth strategy?," Energy Economics, Elsevier, vol. 81(C), pages 308-326.
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    8. Wu, Yinyin & Yu, Jie & Song, Malin & Chen, Jiandong & Hou, Wenxuan, 2021. "Shadow prices of industrial air pollutant emissions in China," Economic Modelling, Elsevier, vol. 94(C), pages 726-736.
    9. Jiandong Chen & Ming Gao & Shulei Cheng & Yiyin Xu & Malin Song & Yu Liu & Wenxuan Hou & Shuhong Wang, 2022. "Evaluation and drivers of global low-carbon economies based on satellite data," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    10. Xuhui Ding & Yong Chen & Min Li & Narisu Liu, 2022. "Booster or Killer? Research on Undertaking Transferred Industries and Residents’ Well-Being Improvements," IJERPH, MDPI, vol. 19(22), pages 1-19, November.
    11. Pegels, Anna & Altenburg, Tilman, 2020. "Latecomer development in a “greening” world: Introduction to the Special Issue," World Development, Elsevier, vol. 135(C).
    12. Hu, Xing & Yu, Shiwei & Fang, Xu & Ovaere, Marten, 2023. "Which combinations of renewable energy policies work better? Insights from policy text synergies in China," Energy Economics, Elsevier, vol. 127(PA).
    13. Trinks, Arjan & Hille, Erik, 2023. "Carbon Costs and Industrial Firm Performance: Evidence from International Microdata," VfS Annual Conference 2023 (Regensburg): Growth and the "sociale Frage" 277705, Verein für Socialpolitik / German Economic Association.

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    JEL classification:

    • F18 - International Economics - - Trade - - - Trade and Environment
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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