Research Article
[Retracted] Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning
Table 2
2006–2018 China’s regional average agricultural inefficiency and its source decomposition.
| | CRS | National average | Eastern average | Central mean | Western average |
| IE | 0.537 | 0.245 | 0.703 | 0.693 | IEL | 0.023 | 0.013 | 0.021 | 0.035 | IEM | 0.013 | 0.016 | 0.011 | 0.012 | IES | 0.021 | 0.007 | 0.029 | 0.029 | IEF | 0.007 | 0.008 | 0.009 | 0.004 | IEI | 0.006 | 0.003 | 0.004 | 0.010 | IEA | 0.047 | 0.041 | 0.049 | 0.051 | IEY | 0.419 | 0.156 | 0.579 | 0.551 |
| VRS | | National average | Eastern average | Central mean | Western average | IE | 0.293 | 0.051 | 0.340 | 0.496 | IEL | 0.014 | 0.001 | 0.014 | 0.026 | IEM | 0.015 | 0.010 | 0.025 | 0.013 | IES | 0.024 | 0.003 | 0.038 | 0.033 | IEF | 0.005 | 0.002 | 0.010 | 0.003 | IEI | 0.017 | 0.005 | 0.029 | 0.019 | IEA | 0.030 | 0.012 | 0.036 | 0.044 | IEY | 0.187 | 0.017 | 0.189 | 0.356 |
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Note. A represents livestock input; Y represents total output of agriculture, forestry, animal husbandry, and fishery.
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