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Do energy efficiency and export quality affect the ecological footprint in emerging countries? A two-step approach using the SBM–DEA model and panel quantile regression

Author

Listed:
  • Emad Kazemzadeh

    (Ferdowsi University of Mashhad)

  • José Alberto Fuinhas

    (University of Coimbra)

  • Matheus Koengkan

    (University of Aveiro)

  • Fariba Osmani

    (Ferdowsi University of Mashhad)

  • Nuno Silva

    (University of Coimbra)

Abstract

The research was performed in 16 emerging countries from 1990 to 2014, using a two-step approach. First, a slacks-based (SBM)–data envelopment analysis (DEA) model annually estimates countries' resources and energy efficiency. In the second step, a panel quantile regression was used to assess the impacts of resources and energy efficiency, export quality, and the other variables on the ecological footprint. The SBM–DEA model revealed that Turkey and Hungary were the countries that got the better rank, and China and India got the worst rank on resources and energy efficiency mean. Quantile regression revealed that resources, energy efficiency, and trade openness reduce the ecological footprint. On the other hand, GDP, consumption of fossil fuels, and population contribute to deteriorating the environmental footprint. Export quality and urban population worsen the ecological footprint but only in some quantiles. Export quality in 10th and 25th quantiles and the case of the urban population all quantiles except the 10th one aggravates the ecological footprint. Thus, from a policy perspective, we have variables that require different kinds of intervention to mitigate/reduce the ecological footprint, i.e., requires many policy measures and the active collaboration of citizens.

Suggested Citation

  • Emad Kazemzadeh & José Alberto Fuinhas & Matheus Koengkan & Fariba Osmani & Nuno Silva, 2022. "Do energy efficiency and export quality affect the ecological footprint in emerging countries? A two-step approach using the SBM–DEA model and panel quantile regression," Environment Systems and Decisions, Springer, vol. 42(4), pages 608-625, December.
    • Handle: RePEc:spr:envsyd:v:42:y:2022:i:4:d:10.1007_s10669-022-09846-2
    DOI: 10.1007/s10669-022-09846-2
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    5. Alireza Amirteimoori & Biresh K. Sahoo & Saber Mehdizadeh, 2023. "Data envelopment analysis for scale elasticity measurement in the stochastic case: with an application to Indian banking," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-36, December.
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