IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v311y2022ics0306261922001519.html
   My bibliography  Save this article

How policy preferences affect the carbon shadow price in the OECD

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922001519
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118686?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    2. Feng, Guohua & McLaren, Keith R. & Yang, Ou & Zhang, Xiaohui & Zhao, Xueyan, 2021. "The impact of environmental policy stringency on industrial productivity growth: A semi-parametric study of OECD countries," Energy Economics, Elsevier, vol. 100(C).
    3. Choi, Yongrok & Zhang, Ning & Zhou, P., 2012. "Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure," Applied Energy, Elsevier, vol. 98(C), pages 198-208.
    4. Wang, Ke & Yang, Kexin & Wei, Yi-Ming & Zhang, Chi, 2018. "Shadow prices of direct and overall carbon emissions in China’s construction industry: A parametric directional distance function-based sensitive estimation," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 180-193.
    5. Han, Rong & Yu, Bi-Ying & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2017. "Carbon emissions quotas in the Chinese road transport sector: A carbon trading perspective," Energy Policy, Elsevier, vol. 106(C), pages 298-309.
    6. Lin, Boqiang & Chen, Yu, 2019. "Will economic infrastructure development affect the energy intensity of China's manufacturing industry?," Energy Policy, Elsevier, vol. 132(C), pages 122-131.
    7. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    8. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang, 2017. "Worldwide carbon shadow prices during 1990–2011," Energy Policy, Elsevier, vol. 109(C), pages 288-296.
    9. MacIver, Callum & Bukhsh, Waqquas & Bell, Keith R.W., 2021. "The impact of interconnectors on the GB electricity sector and European carbon emissions," Energy Policy, Elsevier, vol. 151(C).
    10. Li, Meng & Gao, Yuning & Meng, Bo & Yang, Zhusong, 2021. "Managing the mitigation: Analysis of the effectiveness of target-based policies on China's provincial carbon emission and transfer," Energy Policy, Elsevier, vol. 151(C).
    11. Wang, Yun & Sun, Xiaohua & Guo, Xu, 2019. "Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors," Energy Policy, Elsevier, vol. 132(C), pages 611-619.
    12. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    13. Mingwei Li & Da Zhang & Chiao-Ting Li & Kathleen M. Mulvaney & Noelle E. Selin & Valerie J. Karplus, 2018. "Air quality co-benefits of carbon pricing in China," Nature Climate Change, Nature, vol. 8(5), pages 398-403, May.
    14. Raymond W. Goldsmith, 1951. "A Perpetual Inventory of National Wealth," NBER Chapters, in: Studies in Income and Wealth, Volume 14, pages 5-73, National Bureau of Economic Research, Inc.
    15. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    16. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    17. Ke Wang & Kexin Yang & Yi-Ming Wei & Chi Zhang, 2018. "Shadow prices of direct and overall carbon emissions in China¡¯s construction industry: a parametric directional distance function-based sensitive estimation," CEEP-BIT Working Papers 120, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    18. 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.
    19. Murty, M.N. & Kumar, Surender, 2002. "Measuring the cost of environmentally sustainable industrial development in India: a distance function approach," Environment and Development Economics, Cambridge University Press, vol. 7(3), pages 467-486, July.
    20. Ke Wang & Linan Che & Chunbo Ma & Yi-Ming Wei, 2017. "The Shadow Price of CO2 Emissions in China's Iron and Steel Industry," CEEP-BIT Working Papers 105, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    21. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    22. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions," Energy Economics, Elsevier, vol. 34(3), pages 700-713.
    23. Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2018. "Environmental efficiency and abatement efficiency measurements of China's thermal power industry: A data envelopment analysis based materials balance approach," European Journal of Operational Research, Elsevier, vol. 269(1), pages 35-50.
    24. David Maradan & Anatoli Vassiliev, 2005. "Marginal Costs of Carbon Dioxide Abatement: Empirical Evidence from Cross-Country Analysis," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 141(III), pages 377-410, September.
    25. Lee, Myunghun & Zhang, Ning, 2012. "Technical efficiency, shadow price of carbon dioxide emissions, and substitutability for energy in the Chinese manufacturing industries," Energy Economics, Elsevier, vol. 34(5), pages 1492-1497.
    26. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    27. Molinos-Senante, María & Guzmán, Catalina, 2018. "Reducing CO2 emissions from drinking water treatment plants: A shadow price approach," Applied Energy, Elsevier, vol. 210(C), pages 623-631.
    28. Fare, Rolf, et al, 1993. "Derivation of Shadow Prices for Undesirable Outputs: A Distance Function Approach," The Review of Economics and Statistics, MIT Press, vol. 75(2), pages 374-380, May.
    29. Murty, Sushama & Robert Russell, R. & Levkoff, Steven B., 2012. "On modeling pollution-generating technologies," Journal of Environmental Economics and Management, Elsevier, vol. 64(1), pages 117-135.
    30. Du, Limin & Hanley, Aoife & Zhang, Ning, 2016. "Environmental technical efficiency, technology gap and shadow price of coal-fuelled power plants in China: A parametric meta-frontier analysis," Resource and Energy Economics, Elsevier, vol. 43(C), pages 14-32.
    31. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    32. Shen, Zhiyang & Bai, Kaixuan & Hong, Tianyang & Balezentis, Tomas, 2021. "Evaluation of carbon shadow price within a non-parametric meta-frontier framework: The case of OECD, ASEAN and BRICS," Applied Energy, Elsevier, vol. 299(C).
    33. Zhou, P. & Zhou, X. & Fan, L.W., 2014. "On estimating shadow prices of undesirable outputs with efficiency models: A literature review," Applied Energy, Elsevier, vol. 130(C), pages 799-806.
    34. Atakelty Hailu, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Reply," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1075-1077.
    35. Shen, Zhiyang & Baležentis, Tomas & Chen, Xueli & Valdmanis, Vivian, 2018. "Green growth and structural change in Chinese agricultural sector during 1997–2014," China Economic Review, Elsevier, vol. 51(C), pages 83-96.
    36. Lee, Chia-Yen & Zhou, Peng, 2015. "Directional shadow price estimation of CO2, SO2 and NOx in the United States coal power industry 1990–2010," Energy Economics, Elsevier, vol. 51(C), pages 493-502.
    37. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    38. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    39. Rhodes, Ekaterina & Scott, William A. & Jaccard, Mark, 2021. "Designing flexible regulations to mitigate climate change: A cross-country comparative policy analysis," Energy Policy, Elsevier, vol. 156(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Shen, Zhiyang & Bai, Kaixuan & Hong, Tianyang & Balezentis, Tomas, 2021. "Evaluation of carbon shadow price within a non-parametric meta-frontier framework: The case of OECD, ASEAN and BRICS," Applied Energy, Elsevier, vol. 299(C).
    3. Wang, Zhaohua & Song, Yanwu & Shen, Zhiyang, 2022. "Global sustainability of carbon shadow pricing: The distance between observed and optimal abatement costs," Energy Economics, Elsevier, vol. 110(C).
    4. Zhang, Ning & Huang, Xuhui & Qi, Chao, 2022. "The effect of environmental regulation on the marginal abatement cost of industrial firms: Evidence from the 11th Five-Year Plan in China," Energy Economics, Elsevier, vol. 112(C).
    5. Wu, Jianxin & Ma, Chunbo & Tang, Kai, 2019. "The static and dynamic heterogeneity and determinants of marginal abatement cost of CO2 emissions in Chinese cities," Energy, Elsevier, vol. 178(C), pages 685-694.
    6. Boussemart, Jean-Philippe & Leleu, Hervé & Shen, Zhiyang, 2017. "Worldwide carbon shadow prices during 1990–2011," Energy Policy, Elsevier, vol. 109(C), pages 288-296.
    7. Ma, Chunbo & Hailu, Atakelty & You, Chaoying, 2019. "A critical review of distance function based economic research on China’s marginal abatement cost of carbon dioxide emissions," Energy Economics, Elsevier, vol. 84(C).
    8. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    9. Zhang, Ning & Huang, Xuhui & Liu, Yunxiao, 2021. "The cost of low-carbon transition for China's coal-fired power plants: A quantile frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    10. Du, Limin & Lu, Yunguo & Ma, Chunbo, 2022. "Carbon efficiency and abatement cost of China's coal-fired power plants," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    11. Tang, Kai & Yang, Lin & Zhang, Jianwu, 2016. "Estimating the regional total factor efficiency and pollutants’ marginal abatement costs in China: A parametric approach," Applied Energy, Elsevier, vol. 184(C), pages 230-240.
    12. Pham, Manh D. & Zelenyuk, Valentin, 2019. "Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets," European Journal of Operational Research, Elsevier, vol. 274(1), pages 186-198.
    13. Abad, Arnaud & Briec, Walter, 2019. "On the axiomatic of pollution-generating technologies: Non-parametric production analysis," European Journal of Operational Research, Elsevier, vol. 277(1), pages 377-390.
    14. Lee, Sang-choon & Oh, Dong-hyun & Lee, Jeong-dong, 2014. "A new approach to measuring shadow price: Reconciling engineering and economic perspectives," Energy Economics, Elsevier, vol. 46(C), pages 66-77.
    15. Zhao, Yu & Zhong, Honglin & Kong, Fanbin & Zhang, Ning, 2023. "Can China achieve carbon neutrality without power shortage? A substitutability perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    16. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
    17. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    18. Cherchye, Laurens & Rock, Bram De & Walheer, Barnabé, 2015. "Multi-output efficiency with good and bad outputs," European Journal of Operational Research, Elsevier, vol. 240(3), pages 872-881.
    19. Haiyan Deng & Ge Bai & Kristiaan Kerstens & Zhiyang Shen, 2023. "Comparing green productivity under convex and nonconvex technologies: Which is a robust approach consistent with energy structure?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(8), pages 4377-4394, December.
    20. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:311:y:2022:i:c:s0306261922001519. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.