IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v74y2018icp310-320.html
   My bibliography  Save this article

Multi-country comparisons of CO2 emission intensity: The production-theoretical decomposition analysis approach

Author

Listed:
  • Wang, H.
  • Zhou, P.

Abstract

Comparing CO2 emission intensities of multiple regions reveals the sources of regional disparities and helps regions, especially the low-performing ones, to identify strategies for improving carbon performance. Conducting the comparison from a production perspective can help policymakers pinpoint opportunities to improve the general production system to reduce national emission intensity. This study proposes a spatial production-theoretical decomposition analysis (PDA) approach for such a purpose. Built upon the production theory framework, the proposed spatial PDA model quantifies the impacts of carbon technical performance, potential carbon factor and economy structure on regional disparities in emission intensity. Inter-factor substitution effects are further captured by using a two-stage decomposition procedure. Relevant methodological issues are discussed. The spatial PDA model is then applied to compare the emission intensities of 14 global economies in 2007. It is shown that the proposed model reveals the driving forces of regional disparities from viewpoints of production technology and technical efficiency, and is useful to shape pertinent policy measures aiming at promoting national emission intensity.

Suggested Citation

  • Wang, H. & Zhou, P., 2018. "Multi-country comparisons of CO2 emission intensity: The production-theoretical decomposition analysis approach," Energy Economics, Elsevier, vol. 74(C), pages 310-320.
  • Handle: RePEc:eee:eneeco:v:74:y:2018:i:c:p:310-320
    DOI: 10.1016/j.eneco.2018.05.038
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988318302172
    Download Restriction: Full text for ScienceDirect subscribers only

    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. Wang, Chunhua, 2013. "Changing energy intensity of economies in the world and its decomposition," Energy Economics, Elsevier, vol. 40(C), pages 637-644.
    2. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Multiplicative structural decomposition analysis of energy and emission intensities: Some methodological issues," Energy, Elsevier, vol. 123(C), pages 47-63.
    3. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    4. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    5. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    6. Zhang, Xing-Ping & Zhang, Jing & Tan, Qin-Liang, 2013. "Decomposing the change of CO2 emissions: A joint production theoretical approach," Energy Policy, Elsevier, vol. 58(C), pages 329-336.
    7. Wang, Qunwei & Zhang, Cheng & Cai, Wanhuan, 2017. "Factor substitution and energy productivity fluctuation in China: A parametric decomposition analysis," Energy Policy, Elsevier, vol. 109(C), pages 181-190.
    8. Erik Dietzenbacher & Alex R. Hoen & Bart Los, 2000. "Labor Productivity in Western Europe 1975–1985: An Intercountry, Interindustry Analysis," Journal of Regional Science, Wiley Blackwell, vol. 40(3), pages 425-452, August.
    9. Ma, Chunbo & Stern, David I., 2016. "Long-run estimates of interfuel and interfactor elasticities," Resource and Energy Economics, Elsevier, vol. 46(C), pages 114-130.
    10. Zhou, P. & Ang, B.W., 2008. "Decomposition of aggregate CO2 emissions: A production-theoretical approach," Energy Economics, Elsevier, vol. 30(3), pages 1054-1067, May.
    11. Bostian, Moriah & Färe, Rolf & Grosskopf, Shawna & Lundgren, Tommy, 2016. "Environmental investment and firm performance: A network approach," Energy Economics, Elsevier, vol. 57(C), pages 243-255.
    12. Long, Ruyin & Shao, Tianxiang & Chen, Hong, 2016. "Spatial econometric analysis of China’s province-level industrial carbon productivity and its influencing factors," Applied Energy, Elsevier, vol. 166(C), pages 210-219.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. Wu, F. & Fan, L.W. & Zhou, P. & Zhou, D.Q., 2012. "Industrial energy efficiency with CO2 emissions in China: A nonparametric analysis," Energy Policy, Elsevier, vol. 49(C), pages 164-172.
    15. Liu, Xiao & Zhou, Dequn & Zhou, Peng & Wang, Qunwei, 2017. "What drives CO2 emissions from China’s civil aviation? An exploration using a new generalized PDA method," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 30-45.
    16. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    17. Ang, B.W. & Wang, H., 2015. "Index decomposition analysis with multidimensional and multilevel energy data," Energy Economics, Elsevier, vol. 51(C), pages 67-76.
    18. Pasurka, Carl Jr., 2006. "Decomposing electric power plant emissions within a joint production framework," Energy Economics, Elsevier, vol. 28(1), pages 26-43, January.
    19. Li, Man, 2010. "Decomposing the change of CO2 emissions in China: A distance function approach," Ecological Economics, Elsevier, vol. 70(1), pages 77-85, November.
    20. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl Jr., 2010. "Toxic releases: An environmental performance index for coal-fired power plants," Energy Economics, Elsevier, vol. 32(1), pages 158-165, January.
    21. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    22. Lee, Kihoon & Oh, Wankeun, 2006. "Analysis of CO2 emissions in APEC countries: A time-series and a cross-sectional decomposition using the log mean Divisia method," Energy Policy, Elsevier, vol. 34(17), pages 2779-2787, November.
    23. Kim, Kyunam & Kim, Yeonbae, 2012. "International comparison of industrial CO2 emission trends and the energy efficiency paradox utilizing production-based decomposition," Energy Economics, Elsevier, vol. 34(5), pages 1724-1741.
    24. Seifert, Stefan & Cullmann, Astrid & von Hirschhausen, Christian, 2016. "Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector," Energy Economics, Elsevier, vol. 56(C), pages 9-19.
    25. Li, Jianglong & Lin, Boqiang, 2016. "Inter-factor/inter-fuel substitution, carbon intensity, and energy-related CO2 reduction: Empirical evidence from China," Energy Economics, Elsevier, vol. 56(C), pages 483-494.
    26. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.
    27. Marcel P. Timmer & Erik Dietzenbacher & Bart Los & Robert Stehrer & Gaaitzen J. Vries, 2015. "An Illustrated User Guide to the World Input–Output Database: the Case of Global Automotive Production," Review of International Economics, Wiley Blackwell, vol. 23(3), pages 575-605, August.
    28. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2014. "Potential gains from trading bad outputs: The case of U.S. electric power plants," Resource and Energy Economics, Elsevier, vol. 36(1), pages 99-112.
    29. Wang, H., 2015. "A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator," Energy, Elsevier, vol. 80(C), pages 114-122.
    30. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    31. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    32. Mette Asmild & Joseph Paradi & Vanita Aggarwall & Claire Schaffnit, 2004. "Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry," Journal of Productivity Analysis, Springer, vol. 21(1), pages 67-89, January.
    33. Chris Bataille & Nic Rivers & Paulus Mau & Chris Joseph & Jian-Jun Tu, 2007. "How Malleable are the Greenhouse Gas Emission Intensities of the G7 Nations?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 145-170.
    34. Wang, H. & Zhou, P. & Zhou, D.Q., 2013. "Scenario-based energy efficiency and productivity in China: A non-radial directional distance function analysis," Energy Economics, Elsevier, vol. 40(C), pages 795-803.
    35. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    36. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    37. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    38. Fare, Rolf & Grosskopf, Shawna & Pasurka, Carl Jr., 2007. "Pollution abatement activities and traditional productivity," Ecological Economics, Elsevier, vol. 62(3-4), pages 673-682, May.
    39. Rolf Färe & Shawna Grosskopf, 2000. "Theory and Application of Directional Distance Functions," Journal of Productivity Analysis, Springer, vol. 13(2), pages 93-103, March.
    40. Balta-Ozkan, Nazmiye & Yildirim, Julide & Connor, Peter M., 2015. "Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach," Energy Economics, Elsevier, vol. 51(C), pages 417-429.
    41. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    42. H. Wang & B.W. Ang & P. Zhou, 2018. "Decomposing aggregate CO2 emission changes with heterogeneity: An extended production-theoretical approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin, Boqiang & Xu, Mengmeng, 2019. "Quantitative assessment of factors affecting energy intensity from sector, region and time perspectives using decomposition method: A case of China’s metallurgical industry," Energy, Elsevier, vol. 189(C).
    2. Zhao, Zhibo & Shi, Xunpeng & Zhao, Lingdi & Zhang, Jinggu, 2020. "Extending production-theoretical decomposition analysis to environmentally sensitive growth: Case study of Belt and Road Initiative countries," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Liu, Bingquan & Shi, Junxue & Wang, Hui & Su, Xuelin & Zhou, Peng, 2019. "Driving factors of carbon emissions in China: A joint decomposition approach based on meta-frontier," Applied Energy, Elsevier, vol. 256(C).
    4. Wang, Hui & Li, Rupeng & Zhang, Ning & Zhou, Peng & Wang, Qiang, 2020. "Assessing the role of technology in global manufacturing energy intensity change: A production-theoretical decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    5. Sueyoshi, Toshiyuki & Li, Aijun & Liu, Xiaohong, 2019. "Exploring sources of China's CO2 emission: Decomposition analysis under different technology changes," European Journal of Operational Research, Elsevier, vol. 279(3), pages 984-995.
    6. Wu, F. & Zhou, P. & Zhou, D.Q., 2020. "Modeling carbon emission performance under a new joint production technology with energy input," Energy Economics, Elsevier, vol. 92(C).
    7. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    8. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    9. Huang, Yun-Hsun, 2020. "Examining impact factors of residential electricity consumption in Taiwan using index decomposition analysis based on end-use level data," Energy, Elsevier, vol. 213(C).

    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. Wang, H. & Zhou, P. & Xie, Bai-Chen & Zhang, N., 2019. "Assessing drivers of CO2 emissions in China's electricity sector: A metafrontier production-theoretical decomposition analysis," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1096-1107.
    2. Wang, Qunwei & Hang, Ye & Su, Bin & Zhou, Peng, 2018. "Contributions to sector-level carbon intensity change: An integrated decomposition analysis," Energy Economics, Elsevier, vol. 70(C), pages 12-25.
    3. Wang, Hui & Li, Rupeng & Zhang, Ning & Zhou, Peng & Wang, Qiang, 2020. "Assessing the role of technology in global manufacturing energy intensity change: A production-theoretical decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    4. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    5. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    6. Wang, H. & Pan, Chen & Wang, Qunwei & Zhou, P., 2020. "Assessing sustainability performance of global supply chains: An input-output modeling approach," European Journal of Operational Research, Elsevier, vol. 285(1), pages 393-404.
    7. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    8. Song, Yi & Huang, Jian-Bai & Feng, Chao, 2018. "Decomposition of energy-related CO2 emissions in China's iron and steel industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 59(C), pages 103-116.
    9. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    10. Wang, H. & Ang, B.W. & Su, Bin, 2017. "A Multi-region Structural Decomposition Analysis of Global CO2 Emission Intensity," Ecological Economics, Elsevier, vol. 142(C), pages 163-176.
    11. Zhao, Zhibo & Shi, Xunpeng & Zhao, Lingdi & Zhang, Jinggu, 2020. "Extending production-theoretical decomposition analysis to environmentally sensitive growth: Case study of Belt and Road Initiative countries," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    12. Feng, Chao & Zhang, Hua & Huang, Jian-Bai, 2017. "The approach to realizing the potential of emissions reduction in China: An implication from data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 859-872.
    13. Wang, H. & Zhou, P., 2018. "Assessing Global CO2 Emission Inequality From Consumption Perspective: An Index Decomposition Analysis," Ecological Economics, Elsevier, vol. 154(C), pages 257-271.
    14. Liu, Xiao & Zhou, Dequn & Zhou, Peng & Wang, Qunwei, 2017. "What drives CO2 emissions from China’s civil aviation? An exploration using a new generalized PDA method," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 30-45.
    15. Dequn Zhou & Xiao Liu & Peng Zhou & Qunwei Wang, 2017. "Decomposition Analysis of Aggregate Energy Consumption in China: An Exploration Using a New Generalized PDA Method," Sustainability, MDPI, Open Access Journal, vol. 9(5), pages 1-13, April.
    16. Zhang, Xing-Ping & Tan, Ya-Kun & Tan, Qin-Liang & Yuan, Jia-Hai, 2012. "Decomposition of aggregate CO2 emissions within a joint production framework," Energy Economics, Elsevier, vol. 34(4), pages 1088-1097.
    17. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    18. Chen, Chien-Ming, 2013. "A critique of non-parametric efficiency analysis in energy economics studies," Energy Economics, Elsevier, vol. 38(C), pages 146-152.
    19. Kim, Kyunam & Kim, Yeonbae, 2012. "International comparison of industrial CO2 emission trends and the energy efficiency paradox utilizing production-based decomposition," Energy Economics, Elsevier, vol. 34(5), pages 1724-1741.
    20. Huang, Fei & Zhou, Dequn & Wang, Qunwei & Hang, Ye, 2019. "Decomposition and attribution analysis of the transport sector’s carbon dioxide intensity change in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 343-358.

    More about this item

    Keywords

    Production-theoretical decomposition analysis; Spatial decomposition; Multi-country comparisons; CO2 emission intensity;
    All these keywords.

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • O5 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies

    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:eneeco:v:74:y:2018:i:c:p:310-320. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.