Can Innovation-Driven Policy Reduce China’s Carbon Emission Intensity?—A Quasi-Natural Experiment Based on the National Innovative City Pilot Policy

Zicheng Wang () and Xiaoliang Zhou ()
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Zicheng Wang: School of Economics and Management, Fuzhou University, Fuzhou 350108, China
Xiaoliang Zhou: School of Economics and Management, Fuzhou University, Fuzhou 350108, China

Sustainability, 2023, vol. 15, issue 5, 1-17

Abstract: Innovation and carbon neutrality are hot topics nowadays and are important issues related to development quality, efficiency, and long-term sustainability. The purpose of this paper was to analyze the impact of innovation-driven policy on reducing carbon emission intensity. Using urban panel data from 2003 to 2018, this paper constructed a time-varying difference-in-difference model based on the natural experiment of national innovative city pilot policy and systematically examined the specific effects and mechanisms of innovation-driven policy on reducing carbon emission intensity. It was found that the innovation-driven policy represented by the national innovative city pilot policy can significantly reduce the carbon emission intensity in China, and this result was still valid after various robustness tests. The mechanism analysis showed that a reduction in carbon emission intensity was mainly achieved by innovation-driven promotion of green production technology progress and improvements in energy use efficiency. Further heterogeneity analysis showed that the policy had a more significant carbon reduction effect in cities with a strong innovation capability, large size, and low level of industrial structure. These research conclusions provide useful references for further understanding of the economic and social benefits of innovation-driven policy and effectively unleashing the carbon emission reduction effects of innovation-driven policy and promoting sustainable development.

Keywords: innovation-driven policy; carbon emission intensity; national innovative city; time-varying difference-in-difference model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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