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Review | Open Access

An environmental CGE model of China’s economy: Modeling choices and application

Yu Liu1,2( )Nenggao Zhu3,4Meifang Zhou5Xin Wen6Lingyu Yang3,4Xinbei Li3,4Jinzhu Zhang1
College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Institute of Carbon Neutrality, Peking University, Beijing 100871, China
School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
School of Economics, Beijing Technology and Business University, Beijing 100048, China
School of Economics and Management, Beihang University, Beijing 100191, China
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Abstract

This article discusses the expansion and application of computable general equilibrium (CGE) models as significant policy guidance tools for pollution reduction and emission control objectives. Based on the theoretical framework of the Australian school of CGE modeling, we have developed an integrated model that encompasses energy, environment, and economy. This model incorporates energy, environmental, and emission introduction processes, closure mechanisms, and dynamic adjustments. Before simulations, we typically conduct Back-of-the-envelope (BOTE) analyses and validate the accuracy of economic theory judgments and model simulation results through comparative analysis. The article also summarizes our research based on the CGE model, including investigations into differences under various carbon tax revenue policies, comparisons between single-region and multi-region carbon market mechanisms, rebound effects from energy efficiency improvements, impacts of different environmental tax strategies, and the cost-neutral setting of carbon neutrality goals. These findings demonstrate the widespread application and significance of CGE models in theoretical research and policy formulation.

References

[1]
Institute of Carbon Neutrality, Tsinghua University. (2023). 2023 annual report on global carbon neutrality progress. Beijing: Institute of Carbon Neutrality, Tsinghua University.
[2]

Feng, S., Zhang, K. (2018). Fuel-factor nesting structures in CGE models of China. Energy Economics, 75: 274–284.

[3]

Huang, X., Srikrishnan, V., Lamontagne, J., Keller, K., Peng, W. (2023). Effects of global climate mitigation on regional air quality and health. Nature Sustainability, 6: 1054–1066.

[4]
Liu, Y., Wen, D. H., Wang, Y., Sun, Z. Q. (2016). Assessment of impacts of Tianjin pilot emission trading schemes in china—a CGE-analysis using TermCO2 model. Climate Change Research, 12(6): 561–570. (In Chinese)
[5]

Shi, Q., Zheng, B., Zheng, Y., Tong, D., Liu, Y., Ma, H., Hong, C., Geng, G., Guan, D., He, K., et al. (2022). Co-benefits of CO2 emission reduction from China’s clean air actions between 2013−2020. Nature Communications, 13: 5061.

[6]

Nordhaus, W. D. (1993). Optimal greenhouse-gas reductions and tax policy in the “DICE” model. American Economic Review, 83: 313–317.

[7]

Rao, N. D., van Ruijven, B. J., Riahi, K., Bosetti, V. (2017). Improving poverty and inequality modelling in climate research. Nature Climate Change, 7: 857–862.

[8]

Jia, Z., Lin, B. (2022). CEEEA2.0 model: A dynamic CGE model for energy-environment-economy analysis with available data and code. Energy Economics, 112: 106117.

[9]

Hosny, A. S. (2013). Survey of recent literature on CGE trade models: With special reference to the case of Egypt. Journal of World Economic Research, 2: 9.

[10]

Zhai, F., Feng, S., Li, S. (1997). A computable general equilibrium model of the Chinese economy. Quantitative & Technical Economics Research, 03: 38–44.

[11]
Hertel, T. W. Global Trade Analysis: Modeling and Applications. Cambridge: Cambridge University Press, (1996).
[12]
Antoine, B. (2008). The expected benefits of trade liberalization for world income and development: Opening the black box of global trade modeling. IFPRI Food Policy Review 8. Washington, D.C: International Food Policy Research Institute.
[13]
Böhringer, C., Rutherford, T. F., Wiegard, W. (2003). Computable general equilibrium analysis: Opening a black box. ZEW Discussion Papers: No.03-56.
[14]
Horridge M. (2014). ORANI-G: A generic single country computable general equilibrium model. CoPS Working Paper, No. OP-93.
[15]

Johansen, L. (1963). A multi-sectoral study of economic growth: Some comments. Economica, 30: 174.

[16]
Dixon, P. B., Parmenter, B. R., Sutton, J., Vincent, D. P. (1982). ORANI: A Multisectoral Model of the Australian Economy Contributions to Economic Analysis. North-Holland Publishing Company.
[17]
Dixon, P. B., Parmenter, B. R., Powell, A. A., Wilcoxen, P. J. (1992). An introduction to intertemporal modeling. In: Notes and Problems in Applied General Equilibrium Economics. Amsterdam: Elsevier: 277–383.
[18]

Horridge, M., Wittwer, G. (2008). SinoTERM, a multi-regional CGE model of China. China Economic Review, 19: 628–634.

[19]

Aguiar, A., Narayanan, B., McDougall, R. (2016). An overview of the GTAP 9 data base. Journal of Global Economic Analysis, 1: 181–208.

[20]
Mai, Y. H., Dixon, P., Rimmer, M. (2010). CHINAGEM: A Monash-styled dynamic CGE model of China. CoPS Working Papre No. G-201.
[21]
IPCC. (2006). IPCC guidelines for national greenhouse gas inventories. Institute for Global Environmental Strategies.
[22]

Meng, B., Liu, Y., Andrew, R., Zhou, M., Hubacek, K., Xue, J., Peters, G., Gao, Y. (2018). More than half of China’s CO2 emissions are from micro, small and medium-sized enterprises. Applied Energy, 230: 712–725.

[23]

Zhang, Z., Guan, D., Wang, R., Meng, J., Zheng, H., Zhu, K., Du, H. (2020). Embodied carbon emissions in the supply chains of multinational enterprises. Nature Climate Change, 10: 1096–1101.

[24]
Liu, Y., Xiao, H. W., Lv, Y. K. (2015). On economic effect of carbon taxes in China under several tax relief modes: Based on dynamic CGE model. Journal of Finance and Economics, 41(01):35−48. (In Chinese)
[25]

Zhang, J., Liu, Y., Zhou, M., Chen, B., Liu, Y., Cheng, B., Xue, J., Zhang, W. (2022). Regulatory effect of improving environmental information disclosure under environmental tax in China: From the perspectives of temporal and industrial heterogeneity. Energy Policy, 164: 112760.

[26]

Aguiar, A., Chepeliev, M., Corong, E. L., McDougall, R., van der Mensbrugghe, D. (2019). The GTAP data base: Version 10. Journal of Global Economic Analysis, 4: 1–27.

[27]

Feng, T. T., Li, R., Zhang, H. M., Gong, X. L., Yang, Y. S. (2021). Induction mechanism and optimization of tradable green certificates and carbon emission trading acting on electricity market in China. Resources, Conservation and Recycling, 169: 105487.

[28]

Cui, Q., Liu, Y., Ali, T., Gao, J., Chen, H. (2020). Economic and climate impacts of reducing China’s renewable electricity curtailment: A comparison between CGE models with alternative nesting structures of electricity. Energy Economics, 91: 104892.

[29]

Jia, Z., Lin, B. (2021). How to achieve the first step of the carbon-neutrality 2060 target in China: The coal substitution perspective. Energy, 233: 121179.

[30]

Wu, F., Wang, Y., Liu, Y., Liu, Y., Zhang, Y. (2021). Simulated responses of global rice trade to variations in yield under climate change: Evidence from main rice-producing countries. Journal of Cleaner Production, 281: 124690.

[31]

Dai, H., Masui, T., Matsuoka, Y., Fujimori, S. (2011). Assessment of China’s climate commitment and non-fossil energy plan towards 2020 using hybrid AIM/CGE model. Energy Policy, 39: 2875–2887.

[32]
Pearson, K. (1991). Solving nonlinear economic models accurately via a linear representation.
[33]

Liu, Y., Lu, Y. (2015). The Economic impact of different carbon tax revenue recycling schemes in China: A model-based scenario analysis. Applied Energy, 141: 96–105.

[34]

Chen, S. (2022). The inequality impacts of the carbon tax in China. Humanities and Social Sciences Communications, 9: 277.

[35]

Cao, J., Dai, H., Li, S., Guo, C., Ho, M., Cai, W., He, J., Huang, H., Li, J., Liu, Y., et al. (2021). The general equilibrium impacts of carbon tax policy in China: A multi-model comparison. Energy Economics, 99: 105284.

[36]
Caciagli, V. Emission trading schemes and carbon markets in the NDCs: Their contribution to the Paris agreement. In: Theory and Practice of Climate Adaptation. Cham: Springer, 2018: 539–571.
[37]

Zhao, X. G., Jiang, G. W., Nie, D., Chen, H. (2016). How to improve the market efficiency of carbon trading: A perspective of China. Renewable and Sustainable Energy Reviews, 59: 1229–1245.

[38]
Liu, Y., Cai, S. F., Wang, Y., Chen, Y. F. (2013). Comparative analysis of the separate carbon market and inter-provincial carbon market—Based on Chinese multi-regional CGE model-TermCo2. Finance & Trade Economics, (11): 117–127. (In Chinese)
[39]
Tan, X. J., Liu, Y., Wang, Y. (2016). The economic and environmental impacts of the Hubei pilot emission trading schemes —Based on Chinese multi-regional general equilibrium model. Wuhan University Journal(Philosophy & Social Science), 69(2): 64–72. (In Chinese).
[40]

Choi, Y., Liu, Y., Lee, H. (2017). The economy impacts of Korean ETS with an emphasis on sectoral coverage based on a CGE approach. Energy Policy, 109: 835–844.

[41]

Cong, R. G., Wei, Y. M. (2012). Experimental comparison of impact of auction format on carbon allowance market. Renewable and Sustainable Energy Reviews, 16: 4148–4156.

[42]

Xu, J., Qiu, R., Lv, C. (2016). Carbon emission allowance allocation with cap and trade mechanism in air passenger transport. Journal of Cleaner Production, 131: 308–320.

[43]

Lin, B., Jia, Z. (2018). Impact of quota decline scheme of emission trading in China: A dynamic recursive CGE model. Energy, 149: 190–203.

[44]

Wu, J., Fan, Y., Xia, Y. (2016). The economic effects of initial quota allocations on carbon emissions trading in China. The Energy Journal, 37: 129–152.

[45]

Tang, L., Wu, J., Yu, L., Bao, Q. (2017). Carbon allowance auction design of China’s emissions trading scheme: A multi-agent-based approach. Energy Policy, 102: 30–40.

[46]

Xiong, L., Shen, B., Qi, S., Price, L., Ye, B. (2017). The allowance mechanism of China’s carbon trading pilots: A comparative analysis with schemes in EU and California. Applied Energy, 185: 1849–1859.

[47]

Cao, J., Ho, M. S., Jorgenson, D. W., Nielsen, C. P. (2019). China’s emissions trading system and an ETS-carbon tax hybrid. Energy Economics, 81: 741–753.

[48]
Sun, R., Kuang, D., Chang, D. Q. (2014). Analysis on carbon trading effects upon energy-economic-environment and calculation of reasonable carbon price intervals. China Population, Resources and Environment, 24(07): 82–90. (In Chinese).
[49]

Brookes, L. (1990). The greenhouse effect: The fallacies in the energy efficiency solution. Energy Policy, 18: 199–201.

[50]
Jevons, W. S. (1865). The coal question: Can Britain survive? (First published in 1865, republished 1906). London: Macmillan.
[51]

Khazzoom, J. D. (1980). Economic implications of mandated efficiency in standards for household appliances. The Energy Journal, 1: 21–40.

[52]

Orea, L., Llorca, M., Filippini, M. (2015). A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand. Energy Economics, 49: 599–609.

[53]
Sorrell, S. (2007). The rebound effect: An assessment of the evidence for economy-wide energy savings from improved energy efficiency. Technical Report. London: UK Energy Research Centre.
[54]

Font Vivanco, D., McDowall, W., Freire-González, J., Kemp, R., van der Voet, E. (2016). The foundations of the environmental rebound effect and its contribution towards a general framework. Ecological Economics, 125: 60–69.

[55]

Wei, T., Liu, Y. (2017). Estimation of global rebound effect caused by energy efficiency improvement. Energy Economics, 66: 27–34.

[56]

Lu, Y., Liu, Y., Zhou, M. (2017). Rebound effect of improved energy efficiency for different energy types: A general equilibrium analysis for China. Energy Economics, 62: 248–256.

[57]

Zhou, M., Liu, Y., Feng, S., Liu, Y., Lu, Y. (2018). Decomposition of rebound effect: An energy-specific, general equilibrium analysis in the context of China. Applied Energy, 221: 280–298.

[58]

Koesler, S., Swales, K., Turner, K. (2016). International spillover and rebound effects from increased energy efficiency in Germany. Energy Economics, 54: 444–452.

[59]

Saunders, H. D. (2013). Historical evidence for energy efficiency rebound in 30 US sectors and a toolkit for rebound analysts. Technological Forecasting and Social Change, 80: 1317–1330.

[60]

Druckman, A., Chitnis, M., Sorrell, S., Jackson, T. (2011). Missing carbon reductions? Exploring rebound and backfire effects in UK households. Energy Policy, 39: 3572–3581.

[61]

Mashhadi Rajabi, M. (2022). Dilemmas of energy efficiency: A systematic review of the rebound effect and attempts to curb energy consumption. Energy Research & Social Science, 89: 102661.

[62]

Hu, Y., Wu, W. (2023). Can fossil energy make a soft landing?—The carbon-neutral pathway in China accompanying CCS. Energy Policy, 174: 113440.

[63]

Liu, Y., Hu, X., Feng, K. (2017). Economic and environmental implications of raising China’s emission standard for thermal power plants: An environmentally extended CGE analysis. Resources, Conservation and Recycling, 121: 64–72.

[64]
Liu, Y., Hu X H., Wang, Y. (2017). Optimal selection of environmental taxation from a cost-benefit perspective. Macroeconomics, 5: 80–90. (In Chinese)
[65]
Liu, Y., Hu, X. H. (2017). Environmental tax and SO2 and NO x emissions-a sector level decomposition analysis. China Environmental Science, 37(1): 392–400. (In Chinese).
[66]

Hu, X., Liu, Y., Yang, L., Shi, Q., Zhang, W., Zhong, C. (2018). SO2 emission reduction decomposition of environmental tax based on different consumption tax refunds. Journal of Cleaner Production, 186: 997–1010.

[67]
Liu, Y., Yang, S. X., Zhang, J. Z., Zhou, M. F., Liu, Y. W., Zhang, W. (2023). The moderating effect of improved environmental information disclosure on environmental taxation: Based on China’s environmental CGE model. Management Review 35(2): 3. (In Chinese).
[68]

Du, M., Chai, S., Wei, W., Wang, S., Li, Z. (2022). Will environmental information disclosure affect bank credit decisions and corporate debt financing costs? Evidence from China’s heavily polluting industries. Environmental Science and Pollution Research, 29: 47661–47672.

[69]

Tian, X. L., Guo, Q. G., Han, C., Ahmad, N. (2016). Different extent of environmental information disclosure across Chinese cities: Contributing factors and correlation with local pollution. Global Environmental Change, 39: 244–257.

[70]

Hu, G., Wang, X., Wang, Y. (2021). Can the green credit policy stimulate green innovation in heavily polluting enterprises? Evidence from a quasi-natural experiment in China. Energy Economics, 98: 105134.

[71]

Wu, S., Wu, L., Zhao, X. (2022). Impact of the green credit policy on external financing, economic growth and energy consumption of the manufacturing industry. Chinese Journal of Population, Resources and Environment, 20: 59–68.

[72]
Liu, Y., Yang, L.Y., Li, X. B., Jiang, C. Zhang, J. (2022). Research on the pathway for China’s transformation and development toward carbon neutrality. Journal of Beijing Institute of Technology (Social Sciences Edition), 24(4): 27–36. (In Chinese)
[73]
Anderl, T. (2021). CO2 abatement economics-a practical view. https://doi.org/10.21203/rs.3.rs-1187536/v1.
[74]

Keyaerts, N., Delarue, E., Rombauts, Y., D’haeseleer, W. (2014). Impact of unpredictable renewables on gas-balancing design in Europe. Applied Energy, 119: 266–277.

[75]
Dupont, B., Tant, J., Belmans, R. (2012). Automated residential demand response based on dynamic pricing. In Proceedings of the 2012 3rd IEEE PES ISGT Europe. https://ieeexplore.ieee.org/document/6465806/.
[76]

Allan, G., Hanley, N., McGregor, P., Swales, K., Turner, K. (2007). The impact of increased efficiency in the industrial use of energy: A computable general equilibrium analysis for the United Kingdom. Energy Economics, 29: 779–798.

[77]

Broberg, T., Berg, C., Samakovlis, E. (2015). The economy-wide rebound effect from improved energy efficiency in Swedish industries–A general equilibrium analysis. Energy Policy, 83: 26–37.

[78]
IRENA. (2022). China’s route to carbon neutrality: Perspectives and the role of renewables. https://www.irena.org/publications/2022/Jul/Chinas-Route-to-Carbon-Neutrality.
[79]

Khanna, N., Fridley, D., Zhou, N., Karali, N., Zhang, J., Feng, W. (2019). Energy and CO2 implications of decarbonization strategies for China beyond efficiency: Modeling 2050 maximum renewable resources and accelerated electrification impacts. Applied Energy, 242: 12–26.

[80]

Luderer, G., Madeddu, S., Merfort, L., Ueckerdt, F., Pehl, M., Pietzcker, R., Rottoli, M., Schreyer, F., Bauer, N., Baumstark, L., et al. (2022). Impact of declining renewable energy costs on electrification in low-emission scenarios. Nature Energy, 7: 32–42.

[81]

Ebrahimi, S., Mac Kinnon, M., Brouwer, J. (2018). California end-use electrification impacts on carbon neutrality and clean air. Applied Energy, 213: 435–449.

[82]
Feng, S. H., Peng, X. J., Adams P. (2021). Energy and Economic Implications of Carbon Neutrality in China–A dynamic general equilibrium analysis. CoPS documentation. https://www.copsmodels.com/elecpapr/g-318.htm.
Energy and Climate Management
Article number: 9400002
Cite this article:
Liu Y, Zhu N, Zhou M, et al. An environmental CGE model of China’s economy: Modeling choices and application. Energy and Climate Management, 2025, 1(1): 9400002. https://doi.org/10.26599/ECM.2024.9400002

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Received: 30 December 2023
Revised: 24 January 2024
Accepted: 07 March 2024
Published: 08 May 2024
© The author(s) 2025.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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