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Environmental Productivity Assessment: an Illustration with the Ecuadorian Oil Industry

Author

Listed:
  • Arnaud Abad

    (BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Michell Arias

    (UPVD - Université de Perpignan Via Domitia)

  • Paola Ravelojaona

    (ICN Business School, CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)

Abstract

In this paper, environmental productivity change is analysed through the production theoretic approach to index numbers. Specifically, pollution-adjusted Malmquist and Hicks-Moorsteen productivity indices are considered. These productivity indices are defined as combination of multiplicative distance functions. Non convex pollution-generating technology is assumed to estimate the pollution-adjusted Malmquist and Hicks-Moorsteen productivity measures. Moreover, the main sources of the environmental productivity change are displayed. An empirical illustration is provided by considering a sample of 20 Ecuadorian oil companies over the period 2014-2018. The results are estimated through a non parametric analytic framework.

Suggested Citation

  • Arnaud Abad & Michell Arias & Paola Ravelojaona, 2023. "Environmental Productivity Assessment: an Illustration with the Ecuadorian Oil Industry," Post-Print hal-03574542, HAL.
  • Handle: RePEc:hal:journl:hal-03574542
    DOI: 10.1002/mde.3970
    Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-03574542v2
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    References listed on IDEAS

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    More about this item

    Keywords

    Data Envelopment Analysis (DEA); Ecuadorian Oil industry; Environmental Efficiency; Productivity Indices; Non Convexity; Pollution-generating Technology;
    All these keywords.

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