Prediction of China’s Economic Structural Changes under Carbon Emission Constraints: Based on the Linear Programming Input–Output (LP-IO) Model

Xiaoxiang Xu and Mingqiu Liao
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Xiaoxiang Xu: School of Economics, Capital University of Economics and Business, Beijing 100070, China
Mingqiu Liao: School of Economics, Capital University of Economics and Business, Beijing 100070, China

Sustainability, 2022, vol. 14, issue 15, 1-13

Abstract: China has established a carbon emission reduction goal for 2030. For the Chinese government, there is a dilemma between reducing carbon emissions while still striving to maintain continuous economic growth in future. To achieve these “dual goals”, it is necessary to predict the optimal industrial structure under these constraints in 2030. By integrating the linear programming input–output model (LP-IO) with the RAS updating technique, this paper predicts the industrial structure in China in 2030 and compares it with the year 2018. The results show that China’s industry structure will experience major changes. In particular, most of the industries related to manufacturing, such as mining, petroleum, and metal, will lose their important positions in the economic system, while service industries such as culture, sports, and public service will take over the position as pillars of the economy. Additionally, carbon emissions in 2030 will be at least 12.8 billion tons. Based on these findings, it is suggested that the Chinese government should increase investment in service industries in advance to meet the goal of reducing carbon emissions earlier.

Keywords: linear programming input–output model; carbon emission; industry structure adjustment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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