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Journal of Arid Land
Journal of Arid Land  2023, Vol. 15 Issue (2): 127-144    DOI: 10.1007/s40333-023-0007-6     CSTR: 32276.14.s40333-023-0007-6
Research article     
Dynamic analysis of agricultural green development efficiency in China: Spatiotemporal evolution and influencing factors
LIU Yiping1, LU Chengpeng1,*(), CHEN Xingpeng1,2
1Institute of County Economic Development & Rural Revitalization Strategy, Lanzhou University, Lanzhou 730000, China
2College of Earth and Environmental Science, Lanzhou University, Lanzhou 730000, China
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Abstract  

Green development of agriculture is important for achieving coordinated and high-quality regional development for China. Using provincial data from 1990 to 2020, this work explored the dynamics of agricultural green development efficiency of 31 provinces in China, its spatiotemporal characteristics, and its driving factors using a super-efficiency slacks-based measure (Super-SBM), the Malmquist productivity index (MPI), spatial autocorrelation, and a geographic detector. Results showed that the overall agricultural green development efficiency showed a U-shaped trend, suggesting a low level of efficiency. Although a gradient difference was visible among eastern, central, and western regions, the efficiency gap narrowed each year. Technological progress and efficiency both promoted agricultural green development efficiency, especially technological progress. Agricultural green development efficiency had significant spatial aggregation characteristics, but Moran's I result showed a downward trend from 2015 to 2020, indicating a risk of spatial dispersion in the later stage. The provinces with high agricultural green development efficiency were mainly concentrated in the eastern region, while those with low efficiency were concentrated in the central and western regions. Agricultural green development efficiency was influenced by various factors, which showed differences according to time and region. The impact of the labor force's education level and technological progress increased during the study period, and significantly facilitated agricultural green development efficiency in the eastern region, while the central and western regions were still affected by the scale level and environmental regulation, reflecting the advantages of the eastern region in terms of economy and technology. In the future, strengthening agricultural scientific and technological innovation and deepening interprovincial cooperation can help further improve the level of green agricultural development. In addition, local governments should formulate more precise local agricultural support policies based on macro-level policies and local conditions.

Key words： regional development      economy      technology      spatial evolution      influencing factors      super-efficiency slacks-based measure     
Received: 08 September 2022      Published: 28 February 2023
Corresponding Authors: *LU Chengpeng (E-mail: lcp@lzu.edu.cn)
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LIU Yiping, LU Chengpeng, CHEN Xingpeng. Dynamic analysis of agricultural green development efficiency in China: Spatiotemporal evolution and influencing factors. Journal of Arid Land, 2023, 15(2): 127-144.

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http://jal.xjegi.com/10.1007/s40333-023-0007-6     OR     http://jal.xjegi.com/Y2023/V15/I2/127

Index type Primary index Secondary index Index interpretation Data sources or accounting method Time
duration
Input Resource input Number of agricultural employees Labor input level of agriculture Statistical yearbooks from 31 provinces 1990-2020
Crop-sowing area Land input level of agriculture China Statistical Yearbook
Effective irrigation area Construction level of agricultural water conservancy facilities
Total power of agricultural machinery Agricultural mechanization level
Environmental input Chemical fertilizer application Agricultural chemistry level
Pesticides Amount of pesticides used China Rural Statistical Yearbook
Agricultural film Amount of agricultural film used
Output Expected Total output value of agriculture Agricultural production
Unexpected Carbon emission Total carbon emissions from fertilizer, pesticide, agricultural film, agricultural diesel, agricultural irrigation, and agricultural planting Li et al. (2011)
Nonpoint source pollution Excess nitrogen Guo et al. (2021)
Excess phosphate Wang and Zhang (2018)
Residue of agricultural film Lai et al. (2004)
Table 1 Evaluation index of agricultural green development efficiency
Fig. 1 Trends in agricultural green development efficiency at the national level during 1990-2020
Province TFP EC TC Province TFP EC TC
Anhui 1.022 1.004 1.018 Liaoning 1.022 0.992 1.030
Beijing 1.012 1.000 1.013 Inner Mongolia 1.002 0.991 1.013
Fujian 1.015 0.996 1.020 Ningxia 1.001 0.998 1.004
Gansu 1.006 0.997 1.009 Qinghai 1.016 0.998 1.019
Guangdong 1.016 0.993 1.024 Shandong 1.029 1.004 1.026
Guangxi 1.021 1.000 1.021 Shanxi 1.018 1.005 1.013
Guizhou 1.003 0.985 1.020 Shaanxi 1.014 0.998 1.017
Hainan 1.009 1.002 1.008 Shanghai 1.006 0.994 1.013
Hebei 1.012 0.997 1.016 Sichuan 1.013 0.994 1.019
Henan 1.016 1.002 1.014 Tianjin 1.019 0.995 1.025
Heilongjiang 1.021 1.001 1.021 Tibet 1.004 0.999 1.013
Hubei 1.016 0.992 1.025 Xinjiang 1.025 1.000 1.029
Hunan 1.007 0.993 1.015 Yunnan 1.004 0.992 1.013
Jilin 1.016 0.996 1.021 Zhejiang 1.014 0.999 1.017
Jiangsu 1.026 1.002 1.025 Chongqing 1.029 1.010 1.019
Jiangxi 1.019 0.996 1.024 Mean value 1.015 0.998 1.018
Table 2 Decomposition of agricultural green development efficiency in 31 Chinese provinces
Fig. 2 Decomposition of agricultural green development efficiency during different periods. TFP, total-factor productivity; EC, efficiency change index; TC, technical progress change index.
Index 1990 1995 2000 2005 2010 2015 2020
Moran's I 0.305 0.385 0.399 0.509 0.517 0.539 0.301
Z-test 2.741 3.392 3.480 4.531 4.621 4.853 2.812
P 0.007 0.004 0.003 0.001 0.001 0.001 0.007
Table 3 Moran's I values and statistical test during 1990-2020
Fig. 3 Dynamic change of Moran's I scatterplot of agricultural green development efficiency in China. (a), 1990; (b), 1995; (c), 2000; (d), 2005; (e), 2010; (f), 2015; (g), 2020.
Fig. 4 Factors affecting agricultural green development efficiency
Fig. 5 Radar chart of factors affecting agricultural green development efficiency. (a), 2000; (b), 2010; (c), 2020.
Factor Region
Eastern China Central China Western China China
Agricultural development level 0.726 0.805 0.645 0.485
Agricultural scale level 0.185 0.570 0.549 0.055
Labor force education level 0.267 0.558 0.103 0.304
Financial policies for supporting agriculture 0.095 0.429 0.410 0.321
Technological progress 0.479 0.492 0.514 0.304
Agricultural disaster rate 0.432 0.116 0.246 0.099
Environmental regulation 0.236 0.792 0.631 0.581
Agricultural industrial structure 0.415 0.105 0.382 0.251
Table 4 Zoning detection results for the factors affecting agricultural green development efficiency in 2020
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