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Share green growth: Regional evaluation of green output performance in China

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  • Song, Malin
  • Zhu, Shuai
  • Wang, Jianlin
  • Zhao, Jiajia

Abstract

Reducing carbon emissions is much more difficult than reducing other pollutants through current technology. Promoting the efficiency of energy use and developing clean energy are the only two economically feasible approaches for the future. However, without low-carbon technology, pursuing green growth could negatively affect production activities. In this study, we develop a directional distance function (DDF) model based on the slacks of the output-oriented slack-based measure. Along an endogenously determined directional vector, we can calculate the efficiency scores by reducing the undesirable output and expanding desirable output simultaneously. The global Malmquist index is integrated with the DDF model to capture the dynamic change of output performance. Based on the output performance of green growth, we use counterfactual thinking to evaluate GDP losses caused by limiting carbon emissions. The empirical study using the provincial data of China shows that technological progress, not efficiency change, pushes green growth in China. We also find that pursuing green growth in China would lead to a GDP loss of 7%–8%. Furthermore, a sub-regional analysis shows that the eastern regions were almost immune to the strict carbon-control policy, while the midwestern regions were affected severely. To alleviate the GDP loss, we offer suggestion on setting up a green growth sharing mechanism among regions.

Suggested Citation

  • Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
  • Handle: RePEc:eee:proeco:v:219:y:2020:i:c:p:152-163
    DOI: 10.1016/j.ijpe.2019.05.012
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    1. Peter Bogetoft & Jens Hougaard, 1999. "Efficiency Evaluations Based on Potential (Non-Proportional) Improvements," Journal of Productivity Analysis, Springer, vol. 12(3), pages 233-247, November.
    2. Perroni, Marcos G. & Gouvea da Costa, Sergio E. & Pinheiro de Lima, Edson & Vieira da Silva, Wesley, 2017. "The relationship between enterprise efficiency in resource use and energy efficiency practices adoption," International Journal of Production Economics, Elsevier, vol. 190(C), pages 108-119.
    3. Marshall Burke & Solomon M. Hsiang & Edward Miguel, 2015. "Global non-linear effect of temperature on economic production," Nature, Nature, vol. 527(7577), pages 235-239, November.
    4. Hallegatte, Stephane & Heal, Geoffrey & Fay, Marianne & Treguer, David, 2011. "From growth to green growth -- a framework," Policy Research Working Paper Series 5872, The World Bank.
    5. Ockwell, David G. & Watson, Jim & MacKerron, Gordon & Pal, Prosanto & Yamin, Farhana, 2008. "Key policy considerations for facilitating low carbon technology transfer to developing countries," Energy Policy, Elsevier, vol. 36(11), pages 4104-4115, November.
    6. Lema, Adrian & Lema, Rasmus, 2016. "Low-carbon innovation and technology transfer in latecomer countries: Insights from solar PV in the clean development mechanism," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 223-236.
    7. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    8. Urban, Frauke, 2018. "China's rise: Challenging the North-South technology transfer paradigm for climate change mitigation and low carbon energy," Energy Policy, Elsevier, vol. 113(C), pages 320-330.
    9. R. Färe & S. Grosskopf & G. Whittaker, 2013. "Directional output distance functions: endogenous directions based on exogenous normalization constraints," Journal of Productivity Analysis, Springer, vol. 40(3), pages 267-269, December.
    10. Knox Lovell, C. A. & Pastor, Jesus T. & Turner, Judi A., 1995. "Measuring macroeconomic performance in the OECD: A comparison of European and non-European countries," European Journal of Operational Research, Elsevier, vol. 87(3), pages 507-518, December.
    11. Erik Haites & Maosheng Duan & Stephen Seres, 2006. "Technology transfer by CDM projects," Climate Policy, Taylor & Francis Journals, vol. 6(3), pages 327-344, May.
    12. Matthieu Glachant & Antoine Dechezleprêtre, 2017. "What role for climate negotiations on technology transfer?," Climate Policy, Taylor & Francis Journals, vol. 17(8), pages 962-981, November.
    13. Stefan Dercon, 2014. "Climate change, green growth, and aid allocation to poor countries," Oxford Review of Economic Policy, Oxford University Press, vol. 30(3), pages 531-549.
    14. Kober, Tom & Summerton, Philip & Pollitt, Hector & Chewpreecha, Unnada & Ren, Xiaolin & Wills, William & Octaviano, Claudia & McFarland, James & Beach, Robert & Cai, Yongxia & Calderon, Silvia & Fishe, 2016. "Macroeconomic impacts of climate change mitigation in Latin America: A cross-model comparison," Energy Economics, Elsevier, vol. 56(C), pages 625-636.
    15. Tsan-Ming Choi & Kannan Govindan & Xiang Li & Yongjian Li, 2017. "Innovative supply chain optimization models with multiple uncertainty factors," Annals of Operations Research, Springer, vol. 257(1), pages 1-14, October.
    16. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    17. Carsten Gandenberger & Miriam Bodenheimer & Joachim Schleich & Robert Orzanna & Lioba Macht, 2016. "Factors driving international technology transfer: empirical insights from a CDM project survey," Climate Policy, Taylor & Francis Journals, vol. 16(8), pages 1065-1084, November.
    18. Shen, Zhiyang & Boussemart, Jean-Philippe & Leleu, Hervé, 2017. "Aggregate green productivity growth in OECD’s countries," International Journal of Production Economics, Elsevier, vol. 189(C), pages 30-39.
    19. Stefan Dercon, 2014. "Climate change, green growth, and aid allocation to poor countries," Oxford Review of Economic Policy, Oxford University Press, vol. 30(3), pages 531-549.
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