Analysis on the spatiotemporal pattern and driving force of the spatial deviation index of grain and economy in counties in China

Studying the spatial relationship and driving forces between grain production and economic development in China can assist in the coordinated development of economic growth and grain production in both China and other developing countries. Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China's county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. The results show that (1) from 2000 to 2019, China's SDIGE showed a development trend of "up-down-up," and the highest SDIGE was in the northeast region, the lowest in the east region, and the spatial pattern of "high in the northeast-low in the east coast" was increasingly prominent. (2) In terms of spatial difference, the overall difference of SDIGE in China from 2000 to 2019 showed a rising trend of development; The average contribution rate of the regional difference to the overall difference was the lowest, maintained at about 17.82%; The average contribution rate of intra city and inter-county differences to the overall difference is the highest, which is about 34.20%. (3) In terms of the driving force, the level of economic development hurts SDIGE, while population density, industrial structure, fiscal decentralisation, and terrain fluctuation have a positive and negative impact on SDIGE. To alleviate the imbalance between China's economic development and grain production, it is necessary to implement differentiated policy measures tailored to the specific characteristics of different regions to assist agricultural producers and enhance the stability of grain production.

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Publication Details

Journal
PLoS ONE
Published
2024-12-19
DOI
https://doi.org/10.1371/journal.pone.0306970
Primary Topic
Spatial and Panel Data Analysis
Type
article
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Analysis on the spatiotemporal pattern and driving force of the spatial deviation index of grain and economy in counties in China

Kuan Zhang, Jia Chen
PLoS ONE
Spatial and Panel Data Analysis
article

Analysis on the spatiotemporal pattern and driving force of the spatial deviation index of grain and economy in counties in China

Kuan Zhang, Jia Chen
article en

Abstract

Studying the spatial relationship and driving forces between grain production and economic development in China can assist in the coordinated development of economic growth and grain production in both China and other developing countries. Based on panel data from 2000 to 2019 covering 2018 county-level units in China, this study comprehensively investigated the spatial distribution, spatial differences, dynamic evolution of distribution, and driving factors of China's county-level spatial deviation index of grain and economy (SDIGE) using methods such as the standard deviation ellipse method, the three-stage nested decomposition of Theil index, kernel density estimation, and geographically weighted regression (GWR) model. The results show that (1) from 2000 to 2019, China's SDIGE showed a development trend of "up-down-up," and the highest SDIGE was in the northeast region, the lowest in the east region, and the spatial pattern of "high in the northeast-low in the east coast" was increasingly prominent. (2) In terms of spatial difference, the overall difference of SDIGE in China from 2000 to 2019 showed a rising trend of development; The average contribution rate of the regional difference to the overall difference was the lowest, maintained at about 17.82%; The average contribution rate of intra city and inter-county differences to the overall difference is the highest, which is about 34.20%. (3) In terms of the driving force, the level of economic development hurts SDIGE, while population density, industrial structure, fiscal decentralisation, and terrain fluctuation have a positive and negative impact on SDIGE. To alleviate the imbalance between China's economic development and grain production, it is necessary to implement differentiated policy measures tailored to the specific characteristics of different regions to assist agricultural producers and enhance the stability of grain production.

PLoS ONEVol. 19(12)
Sichuan Agricultural University (CN), Southwest Jiaotong University Hope College, Southwest Jiaotong University (CN)
Openalex Percentile: Top 71%
Spatial and Panel Data Analysis
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