Industrial Structure Upgrading, Green Total Factor Productivity and Carbon Emissions

In global climate change, improving carbon productivity holds great importance for China’s sustainable growth. Based on panel data of 30 Chinese provinces and cities from 1997–2017, the drivers, spatial effects, and convergence characteristics of carbon productivity in China are explored by combining a factor decomposition framework and a spatial panel model. The findings show that (1) China’s carbon productivity shows continuous positive growth, and the substitution effect of capital for energy dominates this changing pattern; (2) There is a β-convergence trend and club convergence in China’s carbon productivity, and the spatial technology spillover accelerates the convergence rate; (3) With its accelerated industrial transformation and technological upgrading, China’s current carbon productivity converges faster than its earlier stage, and the role of physical capital investment has gradually shifted to suppression. In contrast, the positive push of human capital investment has been strengthened; (4) From the perspective of the realization mechanism, the convergence of carbon productivity in China mainly comes from the convergence of energy restructuring and capital-energy substitution. These findings can help China narrow the inter-provincial carbon productivity gap in terms of improving factor structure, upgrading technology, etc., and provide references for sustainable growth decision making in China and around the world.

Section: Discussion Of Empirical Resultscontrasting

confidence: 66%

Section: Discussion Of Empirical Resultsmentioning

confidence: 99%

Sustainable Growth Drivers: Unveiling the Role Played by Carbon Productivity

Song

Meng

et al. 2022

“…The “accumulation” stage and “leap” stage of industrial upgrading may have different impacts on green growth. Existing studies, such as Wei and Zhang [ 80 ], Liang et al [ 81 ], Yang et al [ 82 ], and Zhang et al [ 83 ], demonstrate the nonlinear relationship between the two. In the initial stage of industrial upgrading, since a large amount of capital and labour flow into the secondary and tertiary industries, and market-driven industrial changes often lack scientific policy supporting facilities [ 84 ], this type of industrial upgrading is relatively extensive.…”

Section: Literature Review and Hypothesis Proposalmentioning

confidence: 99%

Does Human Capital Matter for China’s Green Growth?—Examination Based on Econometric Model and Machine Learning Methods

Liu

Cao

Fan

2022

To tackle the increasingly severe environmental challenges, including climate change, we should pay more attention to green growth (GG), a path to realize sustainability. Human capital (HC) has been considered a crucial driving factor for developing countries to move towards GG, but the impact and mechanisms for emerging economies to achieve GG need to be further discussed. To bridge this gap, this paper investigates the relation between HC and GG in theory and demonstration perspective. It constructs a systematic theoretical framework for their relationship. Then, it uses a data envelopment analysis (DEA) model based on the non-radial direction distance function (NDDF) to measure the GG performance of China’s 281 prefecture level cities from 2011 to 2019. Ultimately, it empirically tests the hypothesis by using econometric model and LightGBM machine learning (ML) algorithm. The empirical results indicate that: (1) There is a U-shaped relationship between China’s HC and GG. Green innovation and industrial upgrading are transmission channels in the process of HC affecting GG. (2) Given other factors affecting GG, HC and economic growth contribute equally to GG (17%), second only to city size (21%). (3) China’s HC’s impact on GG is regionally imbalanced and has city size heterogeneity.

“…From the perspective of “increasing quantity”, enterprises can improve production tools through technological innovation in the process of industrial-structure upgrading, enhance the productivity of input factors and promote sustained economic growth [ 44 ]. Industrial-structure upgrading can also improve TFP through specialization in the division of labor and technology spillover [ 45 ]. Duarte and Restuccia (2020) found that the development of high-end productive services had a positive effect on TFP in a study of different industrial sectors [ 46 ].…”

Section: Theoretical Analysis and Research Hypothesesmentioning

confidence: 99%

Agglomeration of Productive Services, Industrial Structure Upgrading and Green Total Factor Productivity: An Empirical Analysis Based on 68 Prefectural-Level-and-Above Cities in the Yellow River Basin of China

Dong

Chen

Zhuang

et al. 2022

Improving green total factor productivity (GTFP) is the inherent requirement for practicing the philosophy of green development and achieving regional high-quality development. Based on panel data for 68 prefectural-level-and-above cities in the Yellow River Basin of China from 2006 to 2019, we measured their GTFPs and degrees of productive-services agglomeration using the non-radial directional distance function and industrial agglomeration index formulas, respectively. Furthermore, we empirically investigated the interactive relationship between agglomeration of productive services, industrial-structure upgrading, and GTFP using the dual fixed-effects model, the mediating-effect model, and the moderating-effect model. The findings were as follows. (1) Both specialized and diversified agglomeration of productive services significantly improved the GTFPs of cities in the Yellow River Basin, and the promoting effect of specialized agglomeration was stronger than that of diversified agglomeration. (2) The diversified agglomeration of productive services (hereinafter referred to as diversified agglomeration) made a significant contribution to GTFP in all sample cities of the Yellow River Basin, while the specialized agglomeration of productive services (hereinafter referred to as specialized agglomeration) only significantly improved GTFP in the upstream cities and had no significant effect on the midstream and downstream cities. (3) When examined according to city size, specialized agglomeration was found to have a positive impact on the GTFPs of small and medium-sized cities in the Yellow River Basin but a non-significant negative impact on large cities, while the effect of diversified agglomeration on GTFP was found not to be significant. (4) Industrial-structure upgrading played partially mediating and negative moderating roles in the process of specialized agglomeration affecting the GTFPs of cities in the Yellow River Basin, but it did not become a mediating channel and moderating factor that influenced diversified agglomeration in relation to GTFP.