The Effect of High-Speed Rail on Cropland Abandonment in China

Shi, Junhui; Wang, Fang

doi:10.3390/land11071002

Cited by 5 publications

(7 citation statements)

References 76 publications

(117 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To overcome radial and angle measurement deviations in the traditional DEA model, Tone (2010) [76] proposed an SBM model which is based on the slack variable and considers unexpected output. On this basis, an unexpected output SBM model under constant returns to scale was constructed with references to the empirical strategies of Wang et al (2022) [77], which was used to estimate green total factor productivity with MaxDEA7.0 software through the Global Malmquist-Luenberger (GML) index, using 2004 as the base period. The theoretical description of this method has been thoroughly introduced [78] and is not further detailed in this study due to the limited space.…”

Section: Explained Variablesmentioning

confidence: 99%

Section: Mechanism Variablementioning

confidence: 99%

“…Industrial structure advancing level (indadv_lev). With reference to the calculation formula of the industrial structure advancing index of Wang (2022) [83], the industrial structure advancing index is defined as follows: firstly, GDP was divided into three parts according to three industries, and proportions of the added value of each part in GDP was used as a component in the spatial vector. In this way, a group of 3D vectors X 0 = (x 1,0 , x 2,0 , x 3,0 ) was formed.…”

Section: Mechanism Variablementioning

confidence: 99%

“…This hypothesis is verified in this section. With reference to the practices of Shi et al [94], the following transmission effect model was constructed to recognize the action mechanism of eco-industrial parks on the green development of cities.…”

Section: Action Mechanism Analysismentioning

confidence: 99%

See 3 more Smart Citations

A Study on the Influence of Green Industrial Policy on Urban Green Development: Based on the Empirical Data of Ecological Industrial Park Pilot Construction

2023

Sustainability

View full text Add to dashboard Cite

Balancing economic development and ecological protection is a dilemma that requires a solution. The construction of ecological industrial parks is expected to be the key to resolving this situation. Based on panel data from 276 prefecture-level cities in China spanning from 2004 to 2019, this paper presents a multi-period difference-in-differences (DID) model to identify the causal relationship between eco-industrial parks and the development of urban green spaces. The research indicates that the creation of eco-industrial parks can significantly promote the sustainable development of urban areas, with a policy promotion effect of approximately 0.0279. The analysis of the mechanism indicates that the implementation of a green industrial policy can enhance the level of sustainable development in cities. This can be accomplished by promoting eco-friendly innovation, facilitating the optimization of industrial structures, and strengthening environmental regulations. A heterogeneity analysis reveals that the impact of eco-industrial parks on promoting green development is more significant in cities located in the eastern and northern regions, as well as those with abundant human capital and financial resources. Conversely, cities situated in the central and western regions, as well as those with low levels of financial resources and non-human capital, tend to experience limited benefits from policies. The conclusions of this study can provide guidance for urban transformation and facilitate sustainable development. Moreover, these parks can function as case studies and provide valuable reference experiences for countries that have not yet established eco-industrial parks.

show abstract

Section: Explained Variablesmentioning

confidence: 99%

Section: Mechanism Variablementioning

confidence: 99%

Section: Mechanism Variablementioning

confidence: 99%

Section: Action Mechanism Analysismentioning

confidence: 99%

See 2 more Smart Citations

A Study on the Influence of Green Industrial Policy on Urban Green Development: Based on the Empirical Data of Ecological Industrial Park Pilot Construction

2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…Considering the implementation of smart city construction policy, the specific mechanisms by which smart city construction decreases carbon emission intensity were investigated from the perspectives of green technological innovation, industrial structure advances, and energy consumption levels. With reference to the research of Shi and Wang [54], the direct regression method was used for verification.…”

Section: Influencing Mechanism Testmentioning

confidence: 99%

Does Smart City Construction Decrease Urban Carbon Emission Intensity? Evidence from a Difference-in-Difference Estimation in China

Zhang

Xiao

2022

Sustainability

View full text Add to dashboard Cite

Climatic changes and environmental pollution caused by traditional urban development models have increased due to accelerated urbanisation and industrialisation. As a new model of urban development, smart city construction relies on digital technology reform to achieve intelligent urban governance, which is crucial for reducing carbon emission intensity and achieving regional green development. This paper constructs a multi-period DID model based on panel data from 283 cities from 2007 to 2019 to explore the impact of smart city construction on urban carbon emission intensity. This study found that smart city construction decreased urban carbon emissions intensity significantly and decreased carbon emissions per unit GDP in pilot areas by 0.1987 tonnes/10,000 CNY compared to that in non-pilot areas. According to a heterogeneity analysis, the integration of smart city developments could decrease carbon emission intensity in northern China’s cities and resource-based cities significantly but had an insignificant influence on carbon emission intensity in southern China’s cities and non-resource-based cities. The reason for this finding is that northern cities and resource-based cities have a higher carbon emission intensity and enjoy more marginal benefits from smart city construction. Based on an analysis of the influencing mechanisms, smart city construction can decrease urban carbon emission intensity by stimulating green innovation vitality, upgrading industrial structures, and decreasing energy consumption. These research conclusions can provide directions for urban transformation and low-carbon development, as well as a case study and experience for countries that have not yet established smart city construction.

show abstract

Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model ——13120 Farming Households in 26 Provinces of China as an Example

Xiangdong,

Decheng

2023

Preprint

View full text Add to dashboard Cite

Cropland abandonment is a widespread phenomenon with an increasing trend around the world, including China. Cropland abandonment is the result of a multi-scale and multi-factor nested structure, in order to comprehensively identify the individual and background effects, the study explores the causes of the differences in farmland abandonment levels at two levels: farm household and village, based on a hierarchical linear model. The results show that: (1) 83.63% of the differences in farm abandonment rates are differences in farm households while 16.37% are differences in their villages; (2) whether head of household is healthier, per capita cropland area, ratio of transferred farmland, possession of large-scale agricultural production machinery or livestock for agricultural production, ratio of agricultural income, and whether there are village cadres have a significant negative impact on abandonment rates at the farm household level; while at the village level, commuting distance, whether it is a suburb of a large or medium-sized city, topography of the village is plain or not, and ratio of the number of people in agricultural production in the village have a significant positive impact on abandonment rates, while whether it has experienced land expropriation has a significant positive effect on the abandonment rate; (3) commuting distance weakens the negative correlation between the ratio of transferred cropland and the ratio of agricultural income and the abandonment rate; whether it is a suburb of a large or medium-sized city strengthens the negative correlation between whether it owns large-scale agricultural production machinery or livestock and the abandonment rate; whether the topography of the village is plain weakens the negative correlation between the possession of large agricultural production machinery or livestock for agricultural production and the agricultural income ratio and the abandonment rate; ratio of the number of people in agricultural production in the village weakens the negative correlation between the ratio of transferred cropland and abandonment rate; and whether the village has experienced land expropriation strengthens the negative correlation between the ratio of agricultural income and abandonment rate.

show abstract

The Effect of High-Speed Rail on Cropland Abandonment in China

Cited by 5 publications

References 76 publications

A Study on the Influence of Green Industrial Policy on Urban Green Development: Based on the Empirical Data of Ecological Industrial Park Pilot Construction

A Study on the Influence of Green Industrial Policy on Urban Green Development: Based on the Empirical Data of Ecological Industrial Park Pilot Construction

Does Smart City Construction Decrease Urban Carbon Emission Intensity? Evidence from a Difference-in-Difference Estimation in China

Study on the Causes of Differences in Cropland Abandonment Levels among Farming Households Based on Hierarchical Linear Model ——13120 Farming Households in 26 Provinces of China as an Example

Contact Info

Product

Resources

About