The role of industrial structure upgrades in eco-efficiency evolution: Spatial correlation and spillover effects

Zhou, Yang; Kong, Ying; Sha, J.; Wang, Hankun

doi:10.1016/j.scitotenv.2019.06.182

Cited by 152 publications

(58 citation statements)

References 30 publications

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“…The indicators were selected from the level of the resident population for accurate measurement to reflect the transfer of the rural surplus labor force [52]. Second, the proportion of the tertiary industry in GDP was selected as the economic urbanization, which can better reflect the development and evolution of the industrial structure than the secondary industry [53]. In the process of economic development, agriculture was transformed into industries, and then industry was transformed into services.…”

Section: Estimation Results Of the Dynamic Panel Modelmentioning

confidence: 99%

How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

2020

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To promote the high-quality development of the Yellow River Basin, the total amount and intensity of agricultural water must be controlled. Further speaking, an urbanization development system should be established that is compatible with water resources and the water environment. We adopted the stochastic frontier analysis model to measure the agricultural water utilization efficiency of the Yellow River Basin from 2007 to 2017. We also adopted the dynamic panel difference generalized method of moments (GMM) and system GMM models to verify the driving factors, in which population urbanization, economic urbanization, and equilibrium urbanization levels were selected as the key variables. The results show that the overall efficiency of agricultural water utilization maintained a steady upward trend during the research period. The spatial differentiation was generally characterized by higher efficiency levels in the eastern region and lower levels in the western region. The variation coefficient of water utilization efficiency showed a downward trend in general, which indicates a space spillover effect. Agricultural water utilization efficiency continued to converge from 2007 to 2017, and the upper reaches area converged relatively more quickly. Regarding the influencing factors, the population urbanization, economic urbanization, balanced urbanization, crop planting ratio, and rice planting ratio had negative effects on agricultural water utilization efficiency. Urbanization did not positively affect agricultural water use efficiency as the related theories, so urbanization quality and urban–rural integration should be paid more attention. However, technology innovation was significantly positive in agricultural water utilization efficiency. The influencing factors of per capita water availability and annual precipitation did not pass the significance test. Therefore, the government should vigorously promote the development of high-quality new-type urbanization, scientifically formulate the scale and speed of urbanization, strengthen the urban, rural, and industrial integration, and promote the adjustment of planting structures and agricultural deep processing.

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Section: Estimation Results Of the Dynamic Panel Modelmentioning

confidence: 99%

How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

2020

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“…Fourthly, the cross-term of urbanization and urban primacy ratio was also selected, as the balance of urbanization development may have different effects on industrial water utilization efficiency in different urbanization stages. Fifthly, compared with the secondary industry, the proportion of the tertiary industry was more representative of the evolution of industrial structure and more suitable for the actual development of industrial upgrading [38]. Sixthly, the per capita GDP was selected as the regional economic development, as many experts have confirmed that water utilization efficiency will change with economic development [39].…”

Section: Estimation Results Of Tobit Modelmentioning

confidence: 99%

Study on Urbanization Level, Urban Primacy and Industrial Water Utilization Efficiency in the Yangtze River Economic Belt

Ding

Jia

2019

Sustainability

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Considering the undesirable output, this paper adopted the data envelopment analysis (DEA) model with the slack variable and super efficiency improvement, to measure industrial water utilization efficiency in the Yangtze River Economic Belt. The paper also creatively introduces urbanization level and urban primacy into driver factors' estimation by stochastic and fixed Tobit models, exploring how urbanization characteristics affected the water utilization in regional industrial production. The results showed that industrial water efficiency has maintained an upward trend during the whole period, while most central and western provinces have shown a U-shaped trend of decreasing first and then rising. However, the industrial water utilization efficiency of central regions is the lowest, and the eastern regions are the highest, catching up with western regions. Utilization efficiency shows an overall convergence during the research period from 2005 to 2017. Regarding the factors' estimation, both population urbanization and land urbanization negatively affected industrial water utilization efficiency, particularly blind expansion and disorderly development. The urban primacy meant the unbalance of urbanization, which would lead to urban diseases and pollution transfer, while the effects of urban primacy depended on the urbanization level. However, the utilization efficiency of industrial water did not become better automatically along with urbanization development; therefore, the scale and speed of urbanization should be scientifically formulated. The effects of the level of economic development, the advanced industrial structure, and the level of foreign investment are significantly negative. rate has increased from 14.08% in 1978 to 58.28% in 2017. The average rate of water quality qualification was only 73.2% in 2017, while the rate of water quality qualification lower than Class III was 16.1% [2]. The Class III water was mainly suitable for centralized drinking water, fishing and swimming, while the water of Class IV was mainly for industrial production and was not suitable for direct human contact. The built-up urban area was 22,182 square kilometers in 2017 and had been doubled from 12,122 square kilometers in 2005. Urbanization is always accompanied by industrialization and the transfer of rural populations, which also leads to the continuously optimization of the allocation of production factors. However, the industry cluster, the rapid growth of the urban population and the rapid expansion of construction land are also likely to cause irreversible water resources crises and water environment problems [3]. Moreover, water management and allocation, apart from the current competing demands, such as industrial water, urban water supply, agricultural irrigation, and ecosystems preservation, will be further affected, mainly by demographic and climatic changes drivers that increase the stress on water resources [4].

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“…The agglomeration effect of industrial structure upgrading refers to the influence of regional industrial structure upgrading on surrounding areas. Zhou et al (2019) [50] studied the role of industrial structure in the evolution of ecological efficiency, focusing on the spillover effect of industrial structure upgrading. Spatial interactions warrant the acceleration of economic integration between ASEAN countries to continuously attract FDI [51].…”

Section: Literature Reviewmentioning

confidence: 99%

Foreign Trade, FDI and the Upgrading of Regional Industrial Structure in China: Based on Spatial Econometric Model

et al. 2020

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The upgrading of industrial structure is the core means of coordinating economic development and environment protection. Its spatial agglomeration can also reduce environmental pollution partly. The upgrading of China’s industrial structure has become an important issue concerned by the whole society. To better understand this issue, based on the provincial data of China (1997–2017), this paper strives to explore the spatial effects of foreign trade and foreign direct investment (FDI) on the upgrading of China’s regional industrial structure by constructing the weight matrix of economic distance, and by introducing the spatial autocorrelation analysis method and spatial panel econometric model. The results show that: 1. The Moran’s I index of China’s import, export, FDI, and industrial structure upgrading has passed the 5% significance level test, displaying remarkable spatial agglomeration characteristics. 2. Foreign trade and FDI are important driving factors to upgrade China’s industrial structure. 3. Foreign trade has a significant spatial spillover effect. Imports and exports can not only promote the upgrading of local industrial structure, but also radiate to other regions, promote or inhibit the development of its industry, and further affect the national data. 4. The spatial spillover effect of FDI is not significant. Finally, some policy suggestions are put forward.

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The role of industrial structure upgrades in eco-efficiency evolution: Spatial correlation and spillover effects

Cited by 152 publications

References 30 publications

How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

How High-Quality Urbanization Affects Utilization Efficiency of Agricultural Water Resources in the Yellow River Basin under Double Control Action?

Study on Urbanization Level, Urban Primacy and Industrial Water Utilization Efficiency in the Yangtze River Economic Belt

Foreign Trade, FDI and the Upgrading of Regional Industrial Structure in China: Based on Spatial Econometric Model

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