Emission regulation of conventional energy-intensive industries

  • You-hua Chen
  • Chan WangEmail author
  • Pu-yan NieEmail author


Global climate change is closely related to conventional energy consumption. Taking the regulations for emissions into account, this article uses a game theory approach to identify industries depending on conventional energies to reduce emissions. This paper proposes to design a suitable supervisory system for emission regulation based on limited supervisor and asymmetric production efficiency. Two different supervision mechanism, random and selected supervisions, are employed. Some interesting conclusions are achieved. Firstly, the greater the level of competition, the smaller the number of firms with emission-reduction technology (ERT) are. Interestingly, the number of firms without ERT increases faster than does the number of firms with ERT. Secondly, under the asymmetric case, the threshold value for firms with low production costs that always employ emission-reduction technology is presented. Finally, this paper proves that firms with higher production costs have greater incentives to avoid emission restriction. Based on the above conclusions, the corresponding policy implications or regulation institutions to reduce climate changes are outlined. Random inspect is optimal if firms’ efficiency information, measured by production cost, is incomplete, while selected supervise is better if efficiency information is complete.


Regulation Equilibrium Emission restriction Industries depending on energies 

List of symbols


Number of firms




Outputs of firm i


Market size


Energy inputs of firm i


Emission of firm i


Marginal emission


Marginal costs


Number of supervisors


Probability of this firm being visited


Profits of firm i with emission-reduction technology


Expected profits of firm i without emission-reduction technology


Number of firms use emission-reduction technology


Number of firms without emission-reduction technology


Total outputs



This work is partially supported by National Natural Science Foundation of PRC (71771057, 71401057), the Humanities and Social Sciences Fund of the Ministry of Education (18YJC790156), the Guangdong Social Science Foundation (GD2018CYJ01), the Soft Science Project of Guangdong Province (2014A070704008), and Innovative Group Foundation (Humanities and Social Sciences) for Higher Education of Guangdong Province (2015WCXTD009). Sincerely thank to the anonymous reviewers.


  1. Aldieri, L., & Vinci, C. P. (2017). The role of technology spillovers in the process of water pollution abatement for large international firms. Sustainability, 9(5), 868.CrossRefGoogle Scholar
  2. Anderson, M. L., & Auffhammer, M. (2014). Pounds that kill: The external costs of vehicle weight. Review of Economic Studies, 81(2), 535–571.CrossRefGoogle Scholar
  3. Basu, K., & Dixit, A. (2017). Too small to regulate. Journal of Quantitative Economics, 15(1), 1–14.CrossRefGoogle Scholar
  4. Camps-Calvet, M., Langemeyer, J., Calvet-Mir, L., & Gómez-Baggethun, E. (2016). Ecosystem services provided by urban gardens in Barcelona, Spain: Insights for policy and planning. Environmental Science & Policy, 62, 14–23.CrossRefGoogle Scholar
  5. Chanda, T., Debnath, G. K., Hossain, M. E., Islam, M. A., & Begum, M. K. (2012). Adulteration of raw milk in the rural areas of Barisal district of Bangladesh. Bangladesh Journal of Animal Science, 41(2), 112–115.CrossRefGoogle Scholar
  6. Chen, Y. H., Huang, S. J., Mishra, A. K., & Wang, X. H. (2018). Effects of input capacity constraints on food quality and regulation mechanism design for food safety management. Ecological Modelling, 2018(385), 89–95.CrossRefGoogle Scholar
  7. Chen, Z. Y., & Nie, P. Y. (2016). Effects of carbon tax on social welfare: A case study of China. Applied Energy, 183, 1607–1615.CrossRefGoogle Scholar
  8. Chen, Y. H., Nie, P. Y., Wang, C., & Meng, Y. (2019). Effects of corporate social responsibility considering emission restrictions. Energy Strategy Reviews, 24, 121–131.CrossRefGoogle Scholar
  9. Chen, Y. H., Nie, P. Y., & Yang, Y. C. (2017a). Energy management contract with subsidy. Journal of Renewable and Sustainable Energy, 9(5), 055903. Scholar
  10. Chen, Y. H., Wen, X. W., Wang, B., & Nie, P. Y. (2017b). Agricultural pollution and regulation: How to subsidize agriculture? Journal of Cleaner Production, 164, 258–264.CrossRefGoogle Scholar
  11. Coase, R. (1960). The problem of social cost. Journal of Law and Economics, 3, 1–44.CrossRefGoogle Scholar
  12. Esty, D. (2016). Regulatory transformation: lessons from Connecticut’s department of energy and environmental protection. Public Administration Review, 76(3), 403–412.CrossRefGoogle Scholar
  13. Golosov, M., Hassler, J., Krusell, P., & Tsyvinski, A. (2014). Optimal taxes on fossil fuel in general equilibrium. Econometrica, 82(1), 41–88.CrossRefGoogle Scholar
  14. Hájek, P., & Stejskal, J. (2018). R&D cooperation and knowledge spillover effects for sustainable business innovation in the chemical industry. Sustainability, 10(4), 1064.CrossRefGoogle Scholar
  15. He, J. K., Deng, J., & Su, M. S. (2010). CO2 emission from China’s energy sector and strategy for its control. Energy, 35, 494–498.Google Scholar
  16. Joëts, M. (2015). Heterogeneous beliefs, regret, and uncertainty: The role of speculation in energy price dynamics. European Journal of Operational Research, 247(1), 204–215.CrossRefGoogle Scholar
  17. Kim, Y. G., & Lim, J. S. (2014). An emissions trading scheme design for power industries facing price regulation. Energy Policy, 75, 84–90.CrossRefGoogle Scholar
  18. Kim, H., & Thompson, H. (2014). Wages in a factor proportions model with energy input. Economic Modelling, 36, 495–501.CrossRefGoogle Scholar
  19. Krutilla, K., & Alexeev, A. (2014). The political transaction costs and uncertainties of establishing environmental rights. Ecological Economics, 107, 299–309.CrossRefGoogle Scholar
  20. Lahiri, S., & Ono, Y. (2007). Relative emission standard versus tax under oligopoly: the role of free entry. Journal of Economics, 91(2), 107–128.CrossRefGoogle Scholar
  21. Larsen, U., Pierobon, L., Baldi, F., Haglind, F., & Ivarsson, A. (2015). Development of a model for the prediction of the fuel consumption and nitrogen oxides emission trade-off for large ships. Energy, 80, 545–555.CrossRefGoogle Scholar
  22. Leopold, A. (2016). Energy related system dynamic models: a literature review. Central European Journal of Operations Research, 24(1), 231–261.CrossRefGoogle Scholar
  23. Li, J. S., Chen, G. Q., Hayat, T., & Alsaedi, A. (2015). Mercury emissions by Beijing’s fossil energy consumption: Based on environmentally extended input–output analysis. Renewable and Sustainable Energy Reviews, 41, 1167–1175.CrossRefGoogle Scholar
  24. Lin, B., & Tan, R. (2017). Sustainable development of China’s energy intensive industries: From the aspect of carbon dioxide emissions reduction. Renewable and Sustainable Energy Reviews, 77, 386–394.CrossRefGoogle Scholar
  25. López-Rodríguez, M. D., Castro, A. J., Castro, H., Jorreto, S., & Cabello, J. (2015). Science–policy interface for addressing environmental problems in arid Spain. Environmental Science & Policy, 50, 1–14.CrossRefGoogle Scholar
  26. Mansouri, S. A., Aktas, E., & Besikci, U. (2016). Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption. European Journal of Operational Research, 248(3), 772–788.CrossRefGoogle Scholar
  27. Maximilian, A., & Wolfram, C. D. (2014). Powering up china: income distributions and residential electricity consumption. American Economic Review, 104(5), 575–580.CrossRefGoogle Scholar
  28. Menegaki, A. N., & Tsagarakis, K. P. (2015). Rich enough to go renewable, but too early to leave fossil energy? Renewable and Sustainable Energy Reviews, 41, 1465–1477.CrossRefGoogle Scholar
  29. Metcalf, G. E. (2014). The economics of energy security. Annual Review of Resource Economics, 6, 155–174.CrossRefGoogle Scholar
  30. Nie, P. Y. (2012). Monopoly with pollution emission. Journal of Environmental Planning and Management, 55(6), 705–711.CrossRefGoogle Scholar
  31. Nie, P. Y. (2015). Analysis of conventional energy supply resource diversity. Applied Thermal Engineering, 89, 663–668.CrossRefGoogle Scholar
  32. Nie, P. Y., Chen, Y. H., Yang, Y. C., & Wang, X. H. (2016a). Subsidies in carbon finance for promoting renewable energy development. Journal of Cleaner Production, 139, 677–684.CrossRefGoogle Scholar
  33. Nie, P. Y., Wang, C., & Yang, Y. C. (2017). Comparison of energy efficiency subsidies under market power. Energy Policy, 110, 144–149.CrossRefGoogle Scholar
  34. Nie, P. Y., & Yang, Y. C. (2016a). Effects of energy price fluctuations on industries with energy inputs: An application to China. Applied Energy, 165, 329–334.CrossRefGoogle Scholar
  35. Nie, P. Y., & Yang, Y. C. (2016b). Renewable energy strategies and energy security. Journal of Renewable and Sustainable Energy, 8(6), 065903.CrossRefGoogle Scholar
  36. Nie, P. Y., Yang, Y. C., Chen, Y. H., & Wang, Z. H. (2016b). How to subsidize energy efficiency under duopoly efficiently? Applied Energy, 175, 31–39.CrossRefGoogle Scholar
  37. Pigou, A. C. (1932). The economics of welfare. London: MacMilan and Co.Google Scholar
  38. Rio, P. D. (2014). On evaluating success in complex policy mixes: the case of renewable energy support schemes. Policy Science, 47(3), 267–287.CrossRefGoogle Scholar
  39. Sacco, D., & Schmutzler, A. (2011). Is there a U-shaped relation between competition and investment? International Journal of Industrial Organization, 29, 65–73.CrossRefGoogle Scholar
  40. Siddiqui, M. S. (2015). Environmental taxes and international spillovers: The case of a small open economy. Energy Economics, 48, 70–80.CrossRefGoogle Scholar
  41. Sunstein, C. R. (2014). On not revisiting official discount rates: institutional inertia and the social cost of carbon. American Economic Review, 104(5), 547–551.CrossRefGoogle Scholar
  42. Tao, A. Y., Wang, X. H., & Yang, B. Z. (2018). Duopoly models with a joint capacity constraint. Journal of Economics, 125(2), 159–172.CrossRefGoogle Scholar
  43. Wang, X., Liu, C., & Hawkins, C. V. (2017a). Local government strategies for financing energy efficiency initiatives. The American Review of Public Administration. Scholar
  44. Wang, C., Nie, P. Y., Peng, D. H., & Li, Z. H. (2017b). Green insurance subsidy for promoting clean production innovation. Journal of Cleaner Production, 148, 111–117.CrossRefGoogle Scholar
  45. Weber, V., & Vogel, P. (2014). Contingent certificate allocation rules and incentives for power plant investment and disinvestment. Journal of Regulatory Economics, 46(3), 292–317.CrossRefGoogle Scholar
  46. Wolf, M. (2014). “Too big to fail” is too big to ignore. Financial Times, April 16, p. 7.Google Scholar
  47. Yang, D. X., Chen, Z. Y., & Nie, P. Y. (2016). Output subsidy of renewable energy power industry under asymmetric information. Energy, 117, 291–299.CrossRefGoogle Scholar
  48. Yang, D. X., & Nie, P. Y. (2016). Influence of optimal government subsidies for renewable energy enterprises. IET Renewable Power Generation, 10(9), 1413–1421.CrossRefGoogle Scholar
  49. Zhao, S. P., Yu, Y., Liu, N., He, J. J., & Chen, J. B. (2014). Effect of traffic restriction on atmospheric particle concentrations and their size distributions in urban Lanzhou, Northwestern China. Journal of Environmental Sciences, 26(2), 362–370.CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.College of Economics and ManagementSouth China Agricultural UniversityGuangzhouPeople’s Republic of China
  2. 2.Institute of Guangdong Economy and Social Development, School of Finance, Collaborative Innovation Center of Scientific Finance and IndustryGuangdong University of Finance and Economics (GDUFE)GuangzhouPeople’s Republic of China

Personalised recommendations