Abstract:

China's manufacturing industry is facing the dual challenges of industrial structure upgrading and dual carbon target constraints, as well as the long-standing regional temporal and spatial differences between the two, which have a great impact on the implementation of the strategies of industrial structure upgrading and carbon emission reduction. Based on this, this paper firstly uses the ratio method and the Super-SBM model to measure the level of industrial structure upgrading of manufacturing industries and their carbon emission efficiency in each province and region in China from 2005 to 2019. Secondly, the paper analyzes and predicts the synergy between the industrial structure upgrading and carbon emission efficiency by using the coupling coordination degree model and the gray BP neural network model respectively. The results show that: ① During the study period, the degree of coupling and coordination between industrial structure upgrading and carbon emission efficiency of the manufacturing industry improved slowly, and the level was low, showing a spatial pattern of "high in the east and low in the west", while the coupling coordination degree of Guangdong and Jiangsu fluctuates greatly. Regional differences in factors such as foreign trade, R&D level and energy consumption structure have an impact on the degree of coordination. ② It is expected that in 2025, the coupling coordination degree will continue the spatial pattern of high in the southeast and low in the northwest, but the heterogeneity will increase. The specific eastern and central regions have a good trend of manufacturing upgrading and emission reduction, and the central region will give play to its geographical location advantage and smooth the domestic general circulation, while the western region is still in the lagging area of coordinated development, and provinces such as Gansu will be in decline. Therefore, this paper suggests that: each province and region should make targeted improvements according to the current characteristics, and may adopt the strategy of unilateral or both breakthroughs to promote the benign and coordinated development of manufacturing industry structure upgrading and carbon emission reduction.

Key words: manufacturing, industrial upgrading, carbon emission efficiency, coupling, prediction

摘要：

我国制造业正面临产业结构升级和双碳目标约束的双重挑战，两者长期存在着区域时空差异，对国家产业结构升级和碳减排战略的整体部署与实施影响极大。鉴于此，本文采用比值法和 SuperSBM模型，测算2005—2019年我国各省区制造业产业结构升级水平及其碳排放效率，并分别运用耦合协调度和灰色BP神经网络模型来分析和预测两者的协调发展程度。结果发现：①2005—2019 年，我国制造业产业结构升级与其碳排放效率的耦合协调程度提升缓慢，水平偏低，呈现“东高西低”的空间格局，波动性较大的是广东和江苏两省，省内外贸、研发水平和能源消费结构等对两省各自耦合协调度产生了影响；②预计到2025年，我国制造业产业结构升级与碳排放效率的耦合协调度将延续东南高、西北低的空间异质性。其中，东、中部省区制造业升级与减排趋势均呈现良好态势，西部地区持续处于协调发展滞后区，甘肃等省区甚至会出现衰退态势。本文建议，各省区应高度关注两项政策落实的协同态势，因地制宜作出政策整改，或单项突破或两者并进，尽快推动我国制造业产业结构升级与碳减排的良性协调发展。

关键词: 制造业, 产业结构升级, 碳排放效率, 时空耦合, 预测