Research on the Effect of Consumer Goods Trade in Policy Based on CGE Model - Theoretical Construction and Empirical Simulation of New Energy Vehicles and Home Appliance Industry
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Abstract
Evaluating the effectiveness of large-scale consumption-stimulus policies requires a comprehensive understanding of their impacts on industrial development, energy utilization, and economic transformation. This study develops a dynamic computable general equilibrium (CGE) model to investigate the effects of consumer goods trade-in policies, focusing on the new energy vehicle and home appliance sectors. By integrating production, consumption, trade, energy, and environmental modules, the model captures the transmission mechanisms of policy incentives across multiple economic sectors. Scenario-based simulations are conducted using macroeconomic and industrial data to quantify impacts on demand expansion, industrial upgrading, energy efficiency improvement, and carbon emission reduction. Results indicate that trade-in policies generate significant positive effects on industrial growth and green transformation while promoting technological upgrading. The proposed framework provides quantitative support for policy optimization and offers analytical references for energy systems, sustainable industrial development, and technology-driven economic transitions.
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References
J. Zhang, W. Li, L. Yang, et al., “Assessing the multidimensional impacts of CCS technology cost reductions: Evidence from a dynamic CGE model,” Environmental Impact Assessment Review, vol. 120, pp. 108434-108434, 2026, doi: 10.1016/j.eiar.2026.108434.
S. Zhang H, J. Yang, X. Li, et al., “Smart Power and Energy Security in the Context of Climate Change: Policy Trade-Offs Analyzed Through a CGE Model,” Emerging Markets Finance and Trade, vol. 62, no. 3, pp. 747-761, 2026, doi: 10.1080/1540496X.2025.2544662.
L. Zhang, N. Zhu, Y. Liu, et al., “Socio-economic impacts in the development of CCS and new energy storage technologies in the power Industry: A CGE model analysis,” Energy, vol. 344, pp. 139741-139741, 2026, doi: 10.1016/j.energy.2025.139741.
F. Azik, S. Mousavi N, and B. Najafi, “Economic-environmental effects of agricultural inputs subsidy reform: appli cation of CGE model,” Environment, Development and Sustainability, vol. (prepublish), pp. 1-42, 2026, doi: 10.1007/s10668-025-06974-y.
M. ˙Ince R and R. TARI, “Assessing the impact of potential energy wealth on Türkiye’s non-energy sectors: a CGE model approach,” Economia Politica, vol. (prepublish), pp. 1-39, 2026, doi: 10.1007/s40888-025-00391-0.
P. Zidouemba R, F. Traoré, and S. Odjo P, “Imperfect competition and asymmetric welfare effects of global price and productivity shocks: a CGE model analysis for Senegal,” Cogent Economics & Finance, pp. 13(1), 2025, doi: 10.1080/23322039.2025.2475160.
J. Cateia V, M. Bittencourt L V, T. Carvalho S, et al., “Trade liberalization, economic growth and welfare in Guinea-Bissau: a CGE modeling,” Cogent Economics & Finance, pp. 13(1), 2025, doi: 10.1080/23322039.2025.2477674.
X. Shen, F. Zhang, and B. Lin, “The environmental and economic effects of differentiated carbon tax across industries under the constraint of the “dual carbon” goal: A study based on a dynamic CGE model,” Journal of environmental management, vol. 394, 127649, 2025, doi: 10.1016/j.jenvman.2025.127649.
J. Wang M, L. Wang X, F. Peng, et al., “Measurement of Economic Effects of Driving Factors of Carbon Emission in the Yangtze River Delta Region,” Huan jing ke xue= Huanjing kexue, vol. 46, no. 10, pp. 6162-6172, 2025, doi: 10.13227/J.HJKX.202409252.
W. Han, J. Liu, X. Yang, et al., “The path to green transformation of the logistics sector from the perspective of ecoefficiency,” Journal of Cleaner Production, vol. 525, pp. 146547-146547, 2025, doi: 10.1016/j.jclepro.2025.146547.
Y. Wang, J. Chou, W. Zhao, et al., “Exploring the economic loss characteristics of meteorological disasters in China based on CGE model improved loss function,” Journal of Cleaner Production, vol. 524, pp. 146385-146385, 2025, doi: 10.1016/j.jclepro.2025.146385.
I. Ramlall, “Stress testing Mauritian households to local and foreign price shocks using a CGE model: Asymmetric effects on poor and rich households,” Development and Sustainability in Economics and Finance, vol. 7, pp. 100072-100072, 2025, doi: 10.1016/j.dsef.2025.100072.
Widyastutik, B. Meliany S, S. Amaliah, et al., “Linking Global CGE Models and Sectoral Analysis to Evaluate the Impact of Trade Openness in Service Sector Towards Indonesia Agricultural and Agroindustry,” Economies, vol. 13, no. 7, pp. 199-199, 2025, doi: 10.3390/economies13070199.
X. Li, Y. Yao, Z. Chen, et al., “Analyzing the environmental and economic impact of carbon pricing policy based on an improved dynamic CGE model: Incorporating demographic characteristics of resident,” Structural Change and Economic Dynamics, vol. 74, pp. 630-644, 2025, doi: 10.1016/j.strueco.2025.05.021.
A. Votinov I, A. Zinchenko A, and K. Nersisyan A, “Using a CGE Model to Update Input-Output Tables Using Data from the Russian Federation and the Republic of Armenia,” Studies on Russian Economic Development, vol. 36, no. 2, pp. 193-202, 2025, doi: 10.1134/S1075700724700667.
A. Schreiber, D. Evans, A. Marten, et al., “Evaluating economy-wide impacts of complex regulations: A hybrid linking approach for detailed sector and CGE models,” Energy Economics, vol. 145, pp. 108458-108458, 2025, doi: 10.1016/j.eneco.2025.108458.
M. Bogmans C, P. Gomez-Gonzalez, G. Ganpurev, et al., “Power Hungry: How AI Will Drive Energy Demand,” IMF Working Papers, 2025(081), 2025, doi: 10.5089/9798229007207.001.
M. Tyelo and C. Punt, “The impact of improvement of the red meat industry on the South African economy: policy analysis using a dynamic computable general equilibrium (CGE) model,” Agrekon, vol. 64, no. 2, pp. 113-129, 2025, doi: 10.1080/03031853.2025.2521497.
L. Wen, T. Shen, and Y. Huang, “A Multi-Regional CGE Model for the Optimization of Land Resource Allocation: A Simulation of the Impact of High-Quality Development Policies in China,” Land, vol. 14, no. 3, pp. 450-450, 2025, doi: 10.3390/land14030450.
N. Vellinga and T. Tanaka, “Updating the analysis of rice import liberalization in Japan: a dynamic-stochastic CGE modelling approach,” Applied Economics, vol. 57, no. 6, pp. 690-708, 2025, doi: 10.1080/00036846.2024.2305617.
B. Xu, T. Gao, F. Li, et al., “Supplier selection in new energy vehicle exports: A tri-clustering evolutionary game method for maritime transport,” Computers & Industrial Engineering, vol. 216, pp. 111971-111971, 2026, doi: 10.1016/j.cie.2026.111971.
K. Jia and Y. Zhao, “Identification of key core technologies of new energy vehicles based on knowledge graph,” Mitigation and Adaptation Strategies for Global Change, vol. 31, no. 4, pp. 31-31, 2026, doi: 10.1007/s11027-026-10300-w.
Z. Hui, D. Zha, X. Yu, et al., “Innovation strategy responses of NEV upstream suppliers under China’s dual-credit policy,” Energy Policy, vol. 214, pp. 115228-115228, 2026, doi: 10.1016/j.enpol.2026.115228.
S. Qin, Y. Xiong, and Q. Cheng, “Effective incentive or limited effect? China’s new energy vehicle promotion policy and enterprise electrification technology transformation,” Technological Forecasting & Social Change, vol. 227, pp. 124642-124642, 2026, doi: 10.1016/j.techfore.2026.124642.
D. Zhao, W. Li, H. Wang, et al., “Research on the alliance cooperation of new energy vehicle enterprises under blockchain-enabled carbon trading policies,” Computers & Industrial Engineering, vol. 216, pp. 111961-111961, 2026, doi: 10.1016/j.cie.2026.111961.
J. Chen and A. Wang, “Driving towards sustainability: Analyzing the purchase intentions of new energy vehicles among young consumers,” Journal of Global Scholars of Marketing Science, vol. 36, no. 2, pp. 265-292, 2026, doi: 10.1080/21639159.2026.2628031.
S. Ye, X. Zhao, P. Dai F, et al., “Sales forecast of new energy vehicles in China based on multi-source information fusion and link prediction,” Journal of environmental management, vol. 404, 129359, 2026, doi: 10.1016/j.jenvman.2026.129359.
J. Sun, Z. Gong, Y. Xu, et al., “A consensus model considering trust-based interactive weight allocation for the procurement of new energy vehicles,” Engineering Applications of Artificial Intelligence, vol. 172, pp. 114320-114320, 2026, doi: 10.1016/j.engappai.2026.114320.
P. Li, J. Ye, W. Liao, et al., “Designing Al-Ce-Si-Mg alloys for new energy vehicle thermal management: Tailoring microstructure and performance through silicon content,” Journal of Alloys and Compounds, vol. 1059, pp. 187121-187121, 2026, doi: 10.1016/j.jallcom.2026.187121.
H. Chen, H. Wang, J. Li, et al., “A research on the residual value of secondhand new energy vehicles based on CatBoost-BiLSTM model,” Journal of Big Data, vol. 13, no. 1, pp. 41-41, 2026, doi: 10.1186/s40537-026-01374-z.