1. Spatial and temporal variation and convergence in the efficiency of high-standard farmland construction: Evidence in China.
- Author
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Liu, Hui and Zhang, Wei
- Subjects
- *
SPATIAL variation , *DATA envelopment analysis , *GINI coefficient - Abstract
To assess the efficiency of high-standard farmland construction (HSFC), this study utilized data spanning from 1998 to 2020 obtained from 30 provinces, autonomous regions, and municipalities in China. This assessment was conducted using a three-stage super-efficient slack-based measure data envelopment analysis(SBM-DEA)model. Furthermore, we investigated the spatial and temporal variances and convergence of HSFC efficiency using the Dagum Gini coefficient and convergence analysis. The results firstly show that from 2007 to 2020, China's HSFC efficiency displayed fluctuations and declines, significantly influenced by environmental and stochastic factors. Secondly, it showed that the gap in China's HSFC efficiency has widened, with super-variable density being demonstrated as the primary source of spatial imbalance in HSFC efficiency. Thirdly, it showed that the deviation in the efficiency of HSFC in the central region of China from the average level has shown a gradually declining trend, while the deviation in the efficiency of HSFC in the national, western, eastern, and northeastern regions has not presented a downward trend. Fourthly, it demonstrated that over time, the efficiency of building high-standard agriculture throughout the nation and its four main areas will converge to the same level. • The three-stage super efficiency model is used to measure the efficiency. • The efficiency of high-standard farmland construction is affected by external environmental factors. • The gap of construction efficiency in various parts of our country expands unceasingly. • Hypervariable density is the main source of spatial imbalance in the efficiency. • There was β absolute convergence and β conditional convergence across the country. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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