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How policy preferences affect the carbon shadow price in the OECD

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  • Cui, Lixin
  • Dong, Ruxue
  • Mu, Yunguo
  • Shen, Zhiyang
  • Xu, Jiatong
Abstract
This paper investigates carbon shadow pricing among OECD countries under different policy preferences for the period of 1991–2019. Based on three types of directional distance functions and a dual formulation of the Kuosmanen approach, we derive carbon shadow prices to simulate three policy scenarios emphasizing economic growth, carbon reduction, or both. The proposed analytic framework reveals that the carbon shadow price (CSP) might be zero if the popular method of setting the directional distance function is applied. This implies that pollution control is achievable without any effort for some countries, which contradicts economic rationality. The main contribution of this paper is to introduce a robust approach to measuring CSP for reasonable economic interpretations (avoiding zero values of CSP). We find the estimated CSP is very sensitive to the specification of distance functions: the range of average CSP in scenarios is between 1066.9 and 5840.3 US dollar per ton. The results show that the environmental performance of OECD countries is improving, with average CSP increasing significantly during the sample period. Furthermore, the countries with the highest carbon abatement cost are different: Sweden (3480.7 $/ton) in Scenario 1, Czech Republic, Greece, and Portugal (10976.0 $/ton) in Scenario 2, Portugal (8888.6 $/ton) in Scenario 3. This may derive biased policy implications for countries.

Suggested Citation

  • Cui, Lixin & Dong, Ruxue & Mu, Yunguo & Shen, Zhiyang & Xu, Jiatong, 2022. "How policy preferences affect the carbon shadow price in the OECD," Applied Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:appene:v:311:y:2022:i:c:s0306261922001519
    DOI: 10.1016/j.apenergy.2022.118686
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    More about this item

    Keywords

    Policy preference; Shadow pricing; Nonparametric model; Environmental performance;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • N50 - Economic History - - Agriculture, Natural Resources, Environment and Extractive Industries - - - General, International, or Comparative
    • O10 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - General

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