The impact of urban sprawl on green total factor productivity: A spatial econometric analysis in China

Liu, Shucheng; Wu, Peijin

doi:10.3389/fenvs.2023.1095349

Cited by 5 publications

(5 citation statements)

References 66 publications

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“…The spatial autocorrelation and convergence models were used to analyze China's evolution characteristics and spatial pattern of green development. Li and Liu (2019) analyzed the economic growth clusters in the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei regions in China through an inefficiency model and found that resources and environment were the main factors leading to the GTFP inefficiency [41]. Amani et al (2019) considered the use of relaxation-based measurement (SBM) model transformation index in variable return on Scale (VRS) to develop MPI [42].…”

Section: Introductionmentioning

confidence: 99%

Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity

Huang

Yin

Guo

et al. 2022

IJERPH

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Green development is an effective way to reconcile the main contradictions between resources, environment, and regional development. Green total factor productivity (GTFP) is an important index to measure green development; an undesirable output-oriented SBM-DEA model and GML model can be used to calculate GTFP. China’s 30 provinces (municipalities and autonomous regions) are divided into three groups: eastern, central, and western. The common frontier function and group frontier function are established, respectively, to deeply explore the temporal and spatial evolution characteristics and center of gravity shift of inter-provincial green total factor productivity (GTFP) in China, and test the convergence under group frontier, to compare the convergence problems under different regions. This study aims to point out the differences in economic growth in different regions of China, foster regional coordination and orderly progress, promote China’s green development process, and improve the high-quality economic development level. According to the results, the efficiency of green development is more reasonable under the frontier groups. The average TGR in the eastern region was 0.993, indicating that it reached 99.3% of the meta-frontier green development efficiency technology. The inter-provincial GTFP in China gradually increased, with an average value of 1.043, which means China’s green development and ecological civilization construction have achieved remarkable results and the three regions showed significant differences. Judging from the shift path of the spatial center of gravity, the spatial distribution pattern of inter-provincial GTFP in China tends to be concentrated and stable as a whole. Moreover, σ convergence only exists in the western region, while absolute β convergence and conditional β convergence exist in eastern, central, and western regions, indicating that the GTFP of different regions will converge to their stable states over time. The results provide a basis for improving the efficiency of institutional allocation of environmental resources, implementing regional differentiated environmental regulation policies, and increasing the value creation of factor resources, which is of great significance for realizing the high-quality economic development in which resources, environment, and economy are coordinated in China.

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Section: Introductionmentioning

confidence: 99%

Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity

Huang

Yin

Guo

et al. 2022

IJERPH

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“…In order to explore the dynamic changes of the innovation efficiency of the cultural industry in the Yangtze River economic belt, the Malmquist index Referring to the research of relevant scholars [33]- [35], the influencing factors of the spatial econometric model are selected as sulfur dioxide emissions in exhaust gas (SDE), investment completed in industrial pollution control (IPC), per capita GDP (AGDP), patent applications of domestic applicants (NPA), total printing of books published (100 million copies) (BPG) and total import and export volume of foreign-funded enterprises (TEF).…”

Section: Innovation Efficiency Of Cultural Industry In the Yangtze Ri...mentioning

confidence: 99%

An Empirical Study on the Spatial Effect of Cultural Industry Innovation Efficiency

Guo,

Zeng

2024

Pol. J. Environ. Stud.

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In order to cope with severe environmental crises such as pollution and climate, the Chinese government has put forward the strategic goal of "double carbon" and vigorously developed green emerging industries such as cultural industry. Based on the super efficiency model and the input oriented Malmquist index model, this paper comprehensively measures the innovation efficiency of cultural industry, and selects the panel data of the Yangtze River economic belt from 2015 to 2021 for empirical analysis. In addition, the spatial econometric model is introduced to explore the driving factors affecting the innovation efficiency of cultural industry from the perspective of time and space. The results show that: (1) the overall innovation efficiency of the cultural industry in the Yangtze River economic belt is high, but there is significant spatial heterogeneity. (2) The average Malmquist index of the innovation efficiency of the cultural industry in the Yangtze River economic belt is 1.123, which reflects the continuous improvement of the level of industrial innovation. Environmental factors such as sulfur dioxide emissions in waste gas, investment in industrial pollution control, and per capita GDP have a significant impact on the innovation efficiency of cultural industry in the Yangtze River economic belt. Finally, the paper puts forward policy suggestions to promote the high-quality development of cultural industry from the perspective of technology, policy and environment.

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“…For example, Sun et al investigated the nonlinear effect of environmental regulation on AGTFP, and pointed out that there is a threshold effect of environmental regulation on AGTFP; that is, when the threshold interval of environmental regulation intensity is reached, its negative effect on AGTFP gradually increases [21]. Liu et al pointed out that urban expansion can significantly inhibit AGTFP in a given region, but because of the presence of spatial and geographical correlation, urban sprawl is conducive to the improvement of AGTFP in neighboring cities [22]. Ge et al proposed that registered residence urbanization and permanent urbanization can improve AGTFP by optimizing factor allocation, capital expansion, and technological spillover [23].…”

Section: Literature Reviewmentioning

confidence: 99%

Digital Financial Inclusion, Land Transfer, and Agricultural Green Total Factor Productivity

2023

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Improving agricultural green total factor productivity is important for achieving high-quality economic development and the SDGs. Digital inclusive finance, which combines the advantages of digital technology and inclusive finance, represents a new scheme that can ease credit constraints and information ambiguity in agricultural production. First, this study focused on agro-ecological functions; we incorporated total agricultural carbon sequestration and emissions extraction into the evaluation system and used the mixed-direction-distance function to calculate agricultural green total factor productivity. Then, based on panel data from 31 provinces in China collected from 2011 to 2021, we used the two-way fixed effect model, the interactive fixed effect, and the plausibly exogenous variable method to test the impact of digital financial inclusion on agricultural green total factor productivity, and its mechanism of action. The panel-corrected standard error and fixed effect Driscoll–Kraay methods were used to account for the unobserved heterogeneity and cross-section dependence in the panel data. The results showed that digital financial inclusion can significantly improve agricultural green total factor productivity. This conclusion remained valid following robustness tests using the spatial econometric model and the method of changing explanatory variables. Digital financial inclusion can improve agricultural green total factor productivity by facilitating the transfer of agricultural land. Sound digital infrastructure and strict green credit policies enhance the role of digital inclusive finance in promoting the green development of agriculture. These conclusions could help the financial sector to formulate flexible, accurate, reasonable, and appropriate financial policies and products that would support agriculture, and enhance the role of digital inclusive finance in promoting sustainable agricultural development.

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The impact of urban sprawl on green total factor productivity: A spatial econometric analysis in China

Cited by 5 publications

References 66 publications

Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity

Regional Differences and Convergence of Inter-Provincial Green Total Factor Productivity in China under Technological Heterogeneity

An Empirical Study on the Spatial Effect of Cultural Industry Innovation Efficiency

Digital Financial Inclusion, Land Transfer, and Agricultural Green Total Factor Productivity

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