Explore the Role of Synergy Agglomeration between Producer Services and Manufacturing Industry on Carbon Productivity

Qing Wu; Xueqin Cao

doi:10.54691/fxcybc85

Authors

Qing Wu
Xueqin Cao

DOI:

https://doi.org/10.54691/fxcybc85

Keywords:

Industrial Collaborative Agglomeration; Carbon Productivity; EBM-GML.

Abstract

This paper, based on the provincial data of China from 2012 to 2022, employs a two-way fixed panel model to empirically study the impact effect and transmission mechanism of the collaborative agglomeration of manufacturing and producer services on regional carbon productivity. The study finds that: the collaborative agglomeration of manufacturing and producer services can significantly enhance regional carbon productivity, with a clear function of energy saving, carbon reduction, and efficiency improvement. Non-linear impact analysis reveals that the relationship between the two presents a distinct "U" shape, with the promotional effect strengthening after passing the inflection point. Heterogeneity analysis shows that regions at different levels of manufacturing agglomeration and producer services agglomeration exhibit varying degrees and significance of impact on carbon productivity from the enhancement of the two industries' collaborative agglomeration, and the inflection points where the effect strengthens are also inconsistent. The analysis of transmission mechanisms reveals that the collaborative agglomeration of the two industries can always influence carbon productivity by promoting the optimization of factor structure, industry scale expansion, and technological progress, while the impact on industrial structure optimization and technological efficiency optimization presents a "U" shape, characterized by long-term and dynamic nature.

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References

[1] W.J. He, H.F. Zhang, X.C. Chen, et al. An Empirical Study on Population Density, Industrial Agglomeration, and Carbon Emissions in Chinese Provinces-From the Perspective of Agglomeration Economy, Congestion Effect, and Spatial Effect, Nankai Economic Studies, (2019) No.02, p.207-225.

[2] Beinhocker E, Oppenheim J, Irons B, et al. The carbon productivity challenge: Curbing climate change and sustaining economic growth, Sydney: McKinsey Global Institute, McKinsey & Company, (2008).

[3] J.H. Pan, L.F. Zhang: A Study on the Regional Differences of Carbon Productivity in China, China Industrial Economics, (2011) No.05, p.47-57.

[4] J.J. Chen, Y. Liu, M.M. Zou: Enhancement of Urban Production Efficiency under Industrial Collaborative Agglomeration - Based on the Background of Integrated Innovation and Conversion of Development Dynamics, Journal of Zhejiang University (Humanities and Social Sciences), vol.46 (2016) No.03, p.150-163.

[5] J.J. Miao, C. Hua, J.C. Feng: The Upgrading Effect of Industrial Collaborative Agglomeration and Carbon Emissions-An Empirical Analysis Based on Spatial Econometric Model, Ecological Economy, vol.36 (2020) No.02, p.28-33.

[6] B. Liu, N,J. Wang, M.J. Yu, et al. The Input of Manufacturing Service Factors and Implicit Carbon in Exports: A Study from the Perspective of Environmental Costs in Global Value Chains, Journal of Renmin University of China, vol.35 (2021) No.02, p.81-94.

[7] L.A. Greening, D.L. Greene, C. Difiglio: Energy efficiency and consumption-the rebound effect-a survey, Energy policy, vol.28 (2000) No.6-7, p.389-401.

[8] Information on https://www.gov.cn/zhengce/zhengceku/2019-09/05/content_5427530. htm.

[9] J. Yang, B.C. Yang, P. Shen: The Collaborative Agglomeration of Manufacturing and Producer Services and Green Economic Efficiency, Statistics and Decision Making, vol.40 (2024) No.19, p.101-105.

[10] R. Guo, Y.J. Yuan: The Impact of Internet Development on Industrial Collaborative Agglomeration and Its Mechanism, Statistical Research, vol.39 (2022) No.06, p.52-67.

[11] Y.A. Zheng, B.J. Shi, X.R. Cheng, et al. A Study on Total Factor Carbon Productivity and Its Spatiotemporal Differentiation in China-Based on Data from30 Chinese Provinces, Ecological Economy, vol.40 (2024) No.08, p.20-29.

[12] H.J. Shan: Re-estimation of China's Capital Stock K:1952-2006, Quantitative Economics and Technical Economics Research, vol.25 (2008) No.10, p.17-31.

[13] L.M. Du: Influencing Factors of Carbon Dioxide Emissions in China: A Study Based on Provincial Panel Data, Southern Economy, (2010) No.11, p.20-33.

[14] X.P. Liu, S.H Sheng, K.Y. Wang. Can economic spatial agglomeration improve carbon productivity? , Economic Review, (2017) No.06, p.107-121.

[15] H.f. Yue, Y. Xu, L. Wu: Empirical Analysis on the Selection of Technological Innovation Methods and the Green Transformation of Chinese Industry, China Population, Resources and Environment, vol.27 (2017) No.12, p.196-206.

[16] H. Xu, W. Liu, D. Zhang: Exploring the role of co-agglomeration of manufacturing and producer services on carbon productivity: An empirical study of 282 cities in China, Journal of Cleaner Production, vol.399 (2023), p.136674.

[17] Y. Wang , C. Sun: The Impact of Industrial Collaborative Agglomeration on Green Total Factor Productivity: From the Perspective of Collaboration between High-tech Industries and Producer Services, Economic Review, (2020) No.03, p.67-77.

[18] X.L. Wang: Impact of Service Industry Agglomeration on the Carbon Productivity of China's Service Industry(ph.D., Wuhan University of Technology, China, (2020).

[19] P.D. Zhang, X.W. Tu: The Impact of Manufacturing Agglomeration on Improving Urban Carbon Total Factor Productivity, Urban Issues, (2023) No.06, p.37-45.

[20] S.J. Zhu, Y. Xie, D.S. Wu: Research on the Energy-saving Effect of Manufacturing Service Transformation and Its Mediating Mechanism, Finance and Trade Economics, vol.41 (2020) No.11, p. 126-140.

[21] D. Shi, C. Zhang: Systematic Optimization of China's Manufacturing Industry Structure: An Analysis from the Perspective of Output Structure Optimization and Factor Structure Matching, Economic Research, vol.52 (2017) No.10, p.158-172.

[22] J. Zhang, Y.T. Fan: Innovative City Green Development: Efficiency Measurement, Externalities, and Improvement Pathways, China Population, Resources and Environment, vol.33 (2023) No.02, p.102-112.