Spatial Distribution and Driving Forces of the Vegetable Industry in China
Hongru Wang,
Jun He,
Noshaba Aziz and
Yue Wang
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Hongru Wang: College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
Jun He: College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
Noshaba Aziz: College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China
Yue Wang: Institute of Agricultural Economics and Development, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Land, 2022, vol. 11, issue 7, 1-18
Abstract:
Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with “high-high” and “low-low” types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective.
Keywords: spatial distribution; spatial agglomeration; standard deviation ellipse; spatial regression model partial differential method (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:7:p:981-:d:850210
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