Evaluating the spatial spillover effect of farmland use transition on grain production – An empirical study in Hubei Province, China

Tang, Yifeng; Lu, Xinhai; Yi, Jialin; Wang, Hongzheng; Zhang, Xupeng; Zheng, Weitao

doi:10.1016/j.ecolind.2021.107478

Cited by 33 publications

(16 citation statements)

References 28 publications

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“…Finally, AEE is improved by AM through spatial spillover effects. The impact of AM on AEE is carried out under the background of spatial interaction, which has a strong spatial spillover effect (Tang et al 2021). Agricultural machinery containing agricultural technology has obvious diffusion and spillover, which depends on good technological innovation and technology diffusion, specialized division of labor and cooperation.…”

Section: Mechanism Of Am On Aeementioning

confidence: 99%

Does agricultural mechanization improve agricultural environment efficiency? Evidence from China’s planting industry

Zhu

Zhang

Piao

2022

Environ Sci Pollut Res

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It has important theoretical value and practical significance to study the impact of agricultural mechanization (AM) on agriculture environment efficiency (AEE), as AM is an important way to improve the level of rural modernization and accelerate the high-quality development of agriculture, while the increase of energy consumption of AM has brought greenhouse gas emissions. Using the panel data of 30 provinces in China from 2001 to 2019, this article adopts stochastic frontier analysis method with output oriented distance function to measure AEE based on net carbon sink, and empirically analyzes the impact of AM on AEE. The empirical analysis finds that the AEE of the whole country and all provinces shows an upward trend with time, and has significant spatial positive autocorrelation characteristics. There is a Kuznets inverted "U" relationship between AM and AEE.Meanwhile, AM has spatial spillover effect and time cumulative effect on AEE, and this basic conclusion is still robust after using instrumental variables, spatial autoregressive model, sub sample regression, changing spatial weight matrix and independent. Further research shows that the effect of AM on AEE depends on the input effect and output effect caused by AM, and the mechanism is mainly reflected in agricultural technology progress, expansion of the scale of agricultural operation, optimization of resource allocation and spatial spillover. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy-and practical implications.

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Section: Mechanism Of Am On Aeementioning

confidence: 99%

Does agricultural mechanization improve agricultural environment efficiency? Evidence from China’s planting industry

Zhu

Zhang

Piao

2022

Environ Sci Pollut Res

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“…Subsequently, the non-agricultural transfer of rural labor has increased labor costs, and farmers will use agricultural machinery, chemical fertilizers or other agricultural technical means to replace labor. Modern technologies such as agricultural mechanization could also significantly improve CLUE [33]. Meanwhile, the occupation of cultivated land for highway infrastructure construction reduced the amount of cultivated land, which could also promote farmers to change the factor input structure.…”

Section: The Effects Of Highway Infrastructure Construction On Cluementioning

confidence: 99%

“…On the one hand, the similarity of natural conditions such as precipitation, temperature and the mobility of factor input in a certain region may cause the spatial convergence of cultivated land use. Meanwhile, the network characteristics of highway infrastructure construction make it possible for a region to construct a highway which results in spatial spillover effects that impact CLUE in neighboring regions [31][32][33]. If the spatial spillover effects are not considered, it may not be possible to accurately determine the impact of highway infrastructure construction on CLUE.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Impact of the Highway Infrastructure Construction and the Threshold Effect on Cultivated Land Use Efficiency: Evidence from Chinese Provincial Panel Data

Hou

Tang

et al. 2022

Land

Self Cite

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Highway infrastructure construction is regarded as one of the effective policy tools used to promote the flow of production factors and upgrade the industrial structure in China, and it may also be an important precondition to improving Cultivated Land Use Efficiency (CLUE). This paper uses a slack-based model (SBM) based on provincial-level panel data from China from 2004 to 2017 to measure CLUE. Then a dynamic spatial Durbin model and a panel threshold regression model were established to analyze the spatial spillover effect and threshold effect of highway infrastructure construction on CLUE. The results showed that the CLUE of China has a fluctuating but overall rising trend. The dynamic spatial Durbin model demonstrated that the Chinese government’s policy of supporting highway infrastructure construction has played an important role in promoting CLUE by spatial spillover effects, and the driving effect of expressways and first–second highways on CLUE is particularly significant in this regard. More interestingly, the results of the panel threshold regression indicated that there is a single threshold effect in the influence of highway infrastructure construction on CLUE. This paper suggested that the spatial correlation between regions should be considered in the construction of regional highway infrastructure and land use planning to improve CLUE. Moreover, the planning of highway infrastructure construction should be balanced according to the actual demand of economic and agricultural development, so as to promote the full flow and reasonable allocation of cultivated land use factors among regions.

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“…The impact of mechanization on planting GTFP is carried out under the background of spatial interaction, which has a strong spatial spillover effect [20]. Agricultural machinery containing agricultural technology has obvious diffusion and spillover, which depends on good technological innovation and technology diffusion, specialized division of labor and cooperation.…”

Section: Planting Gtfp Is Influenced By Mechanization Through Spatial Spillover Effectmentioning

confidence: 99%

Does Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

Zhu¹,

Zhang²,

Piao³

2021

Preprint

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Mechanization is an important factor to improve the green total factor productivity of planting industry, which is the key way to realize the sustainable development and high-quality development of agriculture. Using the panel data of 30 provinces in China from 2001 to 2019, this paper uses the stochastic frontier analysis method of output oriented distance function to measure the green total factor productivity of planting industry based on net carbon sink, and empirically studies the impact of mechanization on the planting green total factor productivity. The empirical analysis finds that mechanization can significantly promote the planting green total factor productivity, and this basic conclusion is still robust after using instrumental variables, sub sample regression. Further research found that the path of mechanization on planting green total factor productivity is mainly reflected in technology progress and spatial spillover. The mechanism of operation scale expansion, factor allocation optimization and technical efficiency change is not significant. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.

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Evaluating the spatial spillover effect of farmland use transition on grain production – An empirical study in Hubei Province, China

Cited by 33 publications

References 28 publications

Does agricultural mechanization improve agricultural environment efficiency? Evidence from China’s planting industry

Does agricultural mechanization improve agricultural environment efficiency? Evidence from China’s planting industry

Evaluating the Impact of the Highway Infrastructure Construction and the Threshold Effect on Cultivated Land Use Efficiency: Evidence from Chinese Provincial Panel Data

Does Mechanization Improve the Green Total Factor Productivity of China’s Planting Industry?

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