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Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases

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  • Hampf, Benjamin
  • Krüger, Jens J.

Abstract

This study explores the reduction potential of greenhouse gases for major pollution emitting countries of the world using nonparametric productivity measurement methods and directional distance functions. In contrast to the existing literature we apply optimization methods to endogenously determine optimal directions for the e ciency analysis. These directions represent the compromise of output enhancement and emissions reduction. The results show that for reasonable directions the adoption of best-practices would lead to sizable emission reductions in a range of about 20 percent compared to current levels.

Suggested Citation

  • Hampf, Benjamin & Krüger, Jens J., 2013. "Optimal Directions for Directional Distance Functions: An Exploration of Potential Reductions of Greenhouse Gases," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79699, Verein für Socialpolitik / German Economic Association.
  • Handle: RePEc:zbw:vfsc13:79699
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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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