Big Data Simulation Analysis of the Impact of China’s Carbon Tax Levy on Carbon Emission Behavior under the Background of “Dual Carbon”

Abstract

Abstract This study focuses on the impact of China’s carbon tax on carbon emission behavior under the background of “double carbon”, using big data simulation analysis. The study utilizes the DICE model, combined with general equilibrium theory, to conduct in-depth theoretical analysis and numerical simulation of the carbon tax policy. It is found that the optimal carbon tax rate should be flexibly adjusted in combination with social and economic development and technological progress, and the optimal tax rate gradually rises from RMB 2.83/tonne of carbon dioxide to RMB 17.62/tonne from 1997 to 2023. Simulation results show that increasing the carbon tax rate can effectively promote the low-carbon emission reduction behavior of enterprises and thus achieve the emission reduction target. Under the fixed carbon tax policy, a 50% tax rate can significantly improve environmental quality and economic output. In contrast, steady-state values of output and carbon emissions decrease with the increase of tax rates. At the same time, the combination of carbon trading and carbon tax can more effectively incentivize enterprises to reduce carbon emissions. The results of the study show that a flexible and reasonable carbon tax policy can significantly affect carbon emission behavior, which is of great significance for realizing China’s “double carbon” goal.