|
|
|
| Research on the Empirical Measurement, Spatiotemporal Distribution, and Convergence of the Development Level of Digital New Quality Productive Forces in China |
| Fan Linjie1, He Juntao1, Zhang Qian2 |
1.School of Public Affairs, Zhejiang University, Hangzhou 310058, China
2.College of Wealth Management, Ningbo University of Finance and Economics, Ningbo 315175, China |
|
|
|
Abstract The theory of new and high-quality productive forces is a profound summary of the laws of human social development, and also represents the evolution of Marxist productive forces theory in the context of China’s practice. Digital new and high-quality productive forces are an advanced form of production nurtured in the era of the digital economy. It is of great significance to explore the dynamic evolution, spatial differences, and convergence characteristics of new and high-quality productive forces in China’s cities from the spatio-temporal dimension for a better understanding. The existing research on digital new and high-quality productive forces mainly focuses on aspects such as connotation characteristics, generation logic, and effect. There are three aspects that urgently need to be enriched: first, a scientific and comprehensive indicator system has not been constructed to actually measure the development level of digital new and high-quality productive forces; second, few literatures explore the dynamic evolution and spatial difference characteristics of digital new and high-quality productive forces at the urban level from the spatio-temporal dimension, making it difficult to depict the full picture of the development of digital new and high-quality productive forces; third, there is insufficient exploration of the convergence characteristics of digital new and high-quality productive forces, making it difficult to understand the regional differences and sources of digital new and high-quality productive forces in China. To make up for the deficiencies of existing researches, this study focuses on the core proposition of the development of new and high-quality productive forces in China in the era of the digital economy. Based on the panel data of 286 prefecture-level cities across the country from 2011 to 2021, an evaluation system is constructed, which includes 17 indicators in four dimensions: digital laborers, digital objects of labor, digital means of labor, and production relations. By using the entropy weight TOPSIS method, Dagum Gini coefficient decomposition, spatial autocorrelation analysis, and convergence model, this study systematically reveals the spatio-temporal evolution laws and regional difference mechanisms of digital new and high-quality productive forces.This study finds that，first, in terms of temporal evolution, the level of digital new and high-quality productive forces nationwide shows a significant upward trend. The eastern region has always maintained a leading position, forming a gradient pattern of “the east leading-the central region catching up-the west improving-the northeast recovering”. From the perspective of different dimensions, the dimension of means of production has the fastest growth rate, mainly due to the penetration of industrial robots and the leapfrog development of digital infrastructure; the growth rate of the dimension of production relations is relatively lagging, reflecting that there is a certain time lag effect in institutional innovation. Second, the spatial distribution shows a significant characteristic of “dense in the east and sparse in the west”. High-value areas are concentrated in the urban agglomerations of the Yangtze River Delta , the Pearl River Delta , and the Beijing-Tianjin-Hebei region, forming a spatial pattern of “two cores and one belt”. The Dagum Gini coefficient decomposition shows that the overall regional differences in the development level of digital new and high-quality productive forces are narrowing. The differences between regions are the main source of overall spatial differences, and the contribution rate of differences between regions is continuously increasing while the contribution rate of transvariation density is continuously decreasing. The spatial autocorrelation analysis shows that the global Moran’s I index is rising, presenting a significant spatial agglomeration pattern. Locally, there is a pattern of coexistence of “low-low agglomeration” and “low-high agglomeration”, and the urban agglomeration in the Yangtze River Delta shows a significant positive spillover effect. Third, the convergence test finds that there are significant characteristics of σ![]() ![]() convergence and conditional β convergence nationwide and in the four major regions. Among them, the western region has the fastest convergence speed, and fiscal support and financial development are the main driving factors; the northeast region presents a unique negative effect of industrial structure, reflecting that the digital transformation of traditional industrial bases faces structural constraints. The spatial Durbin model shows that the knowledge spillover effect is significant in the eastern region, while there is an obvious competition effect in the western region. Based on this, this study puts forward four policy suggestions: promoting the coordinated development of regional digital new and high-quality productive forces, constructing a regional collaborative linkage mechanism, strengthening the spatial benefits of the development of digital new and high-quality productive forces, and developing digital new and high-quality productive forces according to local conditions.
|
|
Received: 16 October 2024
|
|
|
|
1 习近平：《习近平在黑龙江考察时强调 牢牢把握在国家发展大局中的战略定位 奋力开创黑龙江高质量发展新局面》，《人民日报》2023年9月9日，第01版。
2 习近平：《加快发展新质生产力扎实推进高质量发展》，《人民日报》2024年2月2日，第01版。
3 习近平：《关于〈中共中央关于进一步全面深化改革、推进中国式现代化的决定〉的说明》，《人民日报》2024年7月22日，第01版。
4 Perez C.， “Structural change and assimilation of new technologies in the economic and social systems，” Futures，Vol. 15， No. 5 （2018）， pp. 357-375.
5 Perez C. & Freeman C.， “Structural crises of adjustment， business cycles and investment behaviour，” in Dossi G.， Freeman C. & Nelson R. R. et al. （eds.）， Technical Change and Economic Theory， London： Francis Pinter， 1988， pp. 39-62.
6 任保平：《以数字新质生产力的形成全方位推进新型工业化》，《人文杂志》2024年第3期，第1-7页。
7 周文、叶蕾：《新质生产力与数字经济》，《浙江工商大学学报》2024年第2期，第17-28页。
8 米加宁、李大宇、董昌其：《算力驱动的新质生产力：本质特征、基础逻辑与国家治理现代化》，《公共管理学报》2024年第4期，第1-14页。
9 任保平、王子月：《数字新质生产力推动经济高质量发展的逻辑与路径》，《湘潭大学学报（哲学社会科学版）》2023年第6期，第23-30页。
10 高小涵、王立娟：《数字新质生产力、现代产业体系构建与共同富裕》，《工业技术经济》2024年第6期，第20-29页。
11 张彰：《数字新质生产力、农业产业链延伸与共同富裕》，《统计与决策》2024年第9期，第37-42页。
12 褚希伟、王婧卜：《数据要素集聚、科技创新与数字新质生产力》，《商业研究》2024年第5期，第1-9页。
13 王曦：《数字新质生产力、国内国际双循环与经济高质量发展》，《统计与决策》2024年第1期，第17-22页。
14 任保平：《论新质生产力与新型工业化的双向互动》，《学术月刊》2024年第7期，第30-41页。
15 李娟、刘爱峰：《数字新质生产力对碳排放效率的影响》，《统计与决策》2024年第24期，第23-28页。
16 高祥晓、王永强、卢秀茹：《数字经济、新质生产力与农业高质量发展》，《科学管理研究》2024年第4期，第113-123页。
17 陈桂生、吴合庆：《数字新质生产力何以推进共同富裕——基于数字赋能与数字平权的解释》，《重庆大学学报（社会科学版）》2024年第4期，第131-143页。
18 德］马克思、恩格斯：《马克思恩格斯文集》第二卷，中共中央马克思恩格斯列宁斯大林作编译局编译，北京：人民出版社，2012年。
19 德］马克思、恩格斯：《马克思恩格斯选集》第二卷，中共中央马克思恩格斯列宁斯大林作编译局编译，北京：人民出版社，2012年。
20 郑尚植、赵雪：《高质量发展究竟靠谁来推动：有为政府还是有效市场？——基于面板门槛模型的实证检验》，《当代经济管理》2020年第5期，第1-7页。
21 戴魁早、刘友金：《市场化进程对创新效率的影响及行业差异——基于中国高技术产业的实证检验》，《财经研究》2013年第5期，第4-16页。
22 卢福财、王守坤：《历史脉络与实践视野下的有为政府——中国特色社会主义政治经济学的核心命题》，《管理世界》2021年第9期，第77-90页。
23 陈云贤：《中国特色社会主义市场经济：有为政府+有效市场》，《经济研究》2021年第1期，第4-19页。
24 范柏乃、朱华：《我国地方政府绩效评价体系的构建和实际测度》，《政治学研究》2005年第1期，第86-97页。
25 Okoli C. & Pawlowski S. D.， “The Delphi method as a research tool： an example， design considerations and applications，” Information & Management， Vol. 42 （2004）， pp. 15-29.
26 赵涛、张智、梁上坤：《数字经济、创业活跃度与高质量发展——来自中国城市的经验证据》，《管理世界》2020年第10期，第65-76页。
27 王贤彬、杨超群：《节能目标政策与地区能源效率》，《数量经济技术经济研究》2024年第5期，第49-70页。
28 樊纲、王小鲁、张立文：《中国各地区市场化相对进程报告》，《经济研究》2003年第3期，第9-18页。
29 Acemoglu D. & Restrepo P.， “Robots and jobs： evidence from us labor markets，” Journal of Political Economy， Vol. 128， No. 6 （2020）， pp. 2188-2244.
30 王永钦、董雯：《机器人的兴起如何影响中国劳动力市场？——来自制造业上市公司的证据》，《经济研究》2020年第10期，第159-175页。
31 李刚、迟国泰、程砚秋：《基于熵权TOPSIS的人的全面发展评价模型及实证》，《系统工程学报》2011年第3期，400-407页。
32 刘云菲、李红梅、马宏阳：《中国农垦农业现代化水平评价研究——基于熵值法与TOPSIS方法》，《农业经济问题》2021年第3期，第107-116页。
33 刘华军、杜广杰：《中国经济发展的地区差距与随机收敛检验——基于2000—2013年DMSP/OLS夜间灯光数据》，《数量经济技术经济研究》2017年第3期，第43-59页。
34 盛斌、刘宇英：《中国数字经济发展指数的测度与空间分异特征研究》，《南京社会科学》2017年第1期，第43-54页。
35 张荣天、张小林、尹鹏：《长江经济带市域土地资源承载力时空分异与影响因素探析》，《经济地理》2021年第5期，第185-192页。 |
|
|
|
2025, Vol. 55 
