Does Financial Excess Support Land Urbanization—An Empirical Study of Cities in China

Li, Zhenghui; Zou, Fanqi; Tan, Yong; Zhu, Jinhui

doi:10.3390/land10060635

Cited by 40 publications

(25 citation statements)

References 54 publications

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“…The income gap between urban and rural areas of China has become one of the critical issues concerned by many scholars. There are many factors affecting farmers' income, such as natural conditions [1], infrastructure gap [2,3], urbanization level, and even capital stock difference [4,5], which may influence farmers' income to a certain extent. From the perspective of financial development, since the traditional financial mode (set physical outlets, etc.)…”

Section: Introductionmentioning

confidence: 99%

Spatial Spillover Effect and Threshold Effect of Digital Financial Inclusion on Farmers’ Income Growth—Based on Provincial Data of China

Wang

Liao

et al. 2022

Sustainability

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The effect of digital financial inclusion on farmers’ income growth is worth theoretical discussion and empirical testing. Based on the sample data of 30 provinces in the Chinese mainland from 2011 to 2019, this paper adopted the spatial Durbin model and the panel threshold model to empirically study the impact of digital financial inclusion on the growth of farmers’ income; furthermore, the heterogeneity of the impact was studied in terms of the difference of provincial economic development level. The results showed that: first, digital financial inclusion can significantly promote farmers’ income growth; second, digital financial inclusion has a positive spatial spillover effect on farmers’ income growth; third, the impact of digital financial inclusion on farmers’ income growth has a double threshold effect: farmers’ income growth increases with the development of digital financial inclusion; and fourth, the impact of digital financial inclusion on farmers’ income growth is heterogeneous in terms of provincial economic development level.

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Section: Introductionmentioning

confidence: 99%

Spatial Spillover Effect and Threshold Effect of Digital Financial Inclusion on Farmers’ Income Growth—Based on Provincial Data of China

Wang

Liao

et al. 2022

Sustainability

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“…In order to control the impact of other influencing factors on energy efficiency, after referring to relevant research [22,33,34], this paper selects the urbanization level (UL), energy consumption structure (ECS), environmental governance level (ERL), and openness level (OL) as control variables from the perspectives of economy, environment, and foreign trade. Generally speaking, there is a negative correlation between energy consumption structure and energy efficiency; that is, the larger the value of energy consumption structure, the lower the energy efficiency.…”

Section: Variable Definition and Data Source 231 Variable Description...mentioning

confidence: 99%

Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan

2022

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Scientific environmental policies promote energy efficiency improvement by influencing the industrial structure and investment in R&D and innovation. In view of the insufficient impact of the Air Pollution Prevention and Control Action Plan (Action Plan for short) on energy efficiency, this paper takes 30 provinces and municipalities of the Chinese Mainland during 2004–2017 as samples and investigates the impact of China’s Action Plan on energy efficiency as well as the impact path by means of the DID method. This paper finds a significant statistical relationship between the two. The following conclusions are drawn. Firstly, the Action Plan significantly promotes the improvement of provincial energy efficiency. Secondly, the Action Plan has heterogeneous impacts on the energy efficiency in different provinces. This heterogeneity is mainly reflected in the differences in resource endowments and the different intensities of environmental governance in different provinces. Thirdly, the upgrading and rationalization of the industrial structure and the investment in R&D and innovation have significantly different moderating effects on the Action Plan’s impact on energy efficiency. The industrial structure rationalization and the investment in R&D and innovation will enhance the promotion effect of the Action Plan on energy efficiency, while the “quantity” of the industrial structure upgrading will weaken this promotion effect, and the moderating effect of the “quality” of the industrial structure upgrading is not significant.

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“…The first type of variable is the control variable. Based on the existing research, this paper selects the variables that may have an impact on carbon emissions decoupling as the control variables [ 42 , 43 , 44 , 45 , 46 , 47 , 48 ]. Specifically, they are urban population density (UPD), which is obtained by dividing the population of cities under the jurisdiction of each province by the urban area, taking as the logarithm the green coverage of the built-up area (GCBA); that is, the ratio of green areas of cities under the jurisdiction of each province compared to the total area of built-up areas.…”

Section: Variable Measurementmentioning

confidence: 99%

Can the Digital Economy Facilitate Carbon Emissions Decoupling? An Empirical Study Based on Provincial Data in China

Zhong

2022

IJERPH

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The digital economy plays a dual role in the process of global carbon emissions decoupling; for this reason, its overall impact direction and mechanism are worth discussing. This paper attempts to answer the question of the role of the digital economy, based on a review of the existing literature. By constructing a panel smooth transition regression (PSTR) model, this paper empirically tests the effect of the digital economy on carbon emissions decoupling, based on panel data from 30 provinces in China from 2010 to 2019. In order to study the impact mechanism of the digital economy on carbon emissions decoupling, the mediating effect of industrial structure optimization is analyzed through a mediating effect model; the moderating effect is also explored by analyzing the network centrality characteristics of the digital economy. The core-periphery analysis method is adopted to group the samples to test the impact heterogeneity of the digital economy on carbon emissions decoupling. Based on this empirical analysis, the following conclusions are drawn. First, the digital economy has a promoting effect on carbon emissions decoupling, but this effect gradually weakens with the development of the digital economy. Second, the digital economy can promote carbon emissions decoupling through industrial structure optimization, and network centrality has a positive moderating effect on this mechanism. Third, heterogeneity exists in the promoting effect of the digital economy on carbon emissions decoupling, which is reflected in the different intensities of the promotion effect between the core nodes and the peripheral nodes in the network; the attenuation range of the promotion effect is also different when the regime switches.

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Does Financial Excess Support Land Urbanization—An Empirical Study of Cities in China

Cited by 40 publications

References 54 publications

Spatial Spillover Effect and Threshold Effect of Digital Financial Inclusion on Farmers’ Income Growth—Based on Provincial Data of China

Spatial Spillover Effect and Threshold Effect of Digital Financial Inclusion on Farmers’ Income Growth—Based on Provincial Data of China

Impact of Environmental Regulations on Energy Efficiency: A Case Study of China’s Air Pollution Prevention and Control Action Plan

Can the Digital Economy Facilitate Carbon Emissions Decoupling? An Empirical Study Based on Provincial Data in China

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