Forecasting China’s CO2 Emissions for Energy Consumption Based on Cointegration Approach

Abstract

Forecasting CO2 emissions is important for climate policy decision making. The paper attempts to implement empirically the long-term forecast of CO2 emissions based on cointegration theory under the business-as-usual scenario, by using statistical data from China over the period 1953 to 2016. We focus on the relationships between CO2 emissions for energy consumption and influential factors: per capita GDP, urbanization level, energy intensity, and total energy consumption. The empirical results are presented as follows: (1) continuous increase of carbon pollution resulting from energy consumption (1953-2016) indicates that China has beard great pressure of carbon reduction. (2) Though reduction of carbon intensity in 2020 would account for 50.14% that of 2005, which meets the requirements announced by Chinese government in 2009, China would bear carbon emissions for energy consumption of 14.4853 billion tCO2 by 2030, which is nearly 1.59 times that of 2016 and nearly 105 times that of 1953. The results suggest that the policymakers in China may take more effective measures such as reducing energy intensities and formulating stricter environmental regulations in order to mitigate the CO2 emissions and realize the win-win of economic and ecological benefits.