The Evaluation Of Agricultural Production Efficiency In Donting Lake Region Based On Three-stage DEA

The evaluation of agricultural production efficiency is the foundation of management,and traditional evaluations usually use stochastic frontier analysis(SFA)of parameters separately.With non parametric Data envelopment analysis(DEA),SFA analysis considers the influence of environmental factors,but the function form is set subjectively.DEA method does not need to set the function form manually.However,the lack of analysis of environmental factors,the combined analysis of SFA and DEA can give play to their advantages and overcome their respective disadvantages.Dongting Lake Area is not only an important agricultural area in Hunan Province,but also plays an important role in the national food security strategy.Using the SFA and DEA combination method,the agricultural production and related environmental impact data of Dongting Lake Area from 2000 to 2021 are used to evaluate the long-term changes in agricultural production efficiency.Its research results can provide guidance for regional agricultural management,The evaluation method combining parameters and non parameters also provides a reference for the evaluation of agricultural production efficiency.The main conclusions are as follows:(1)Natural and socio-economic environmental variables have a significant impact on agricultural production efficiency.The agricultural production efficiency of Yueyang City in 2006 and 2018,without considering the impact of environmental variables,ranked 2nd and 10th,and after excluding environmental factors,ranked 6th and 3rd;The agricultural production efficiency of Changde City,which does not consider environmental factors,ranked 10th and 2nd in 2006 and 2011,and 4th and 11th after excluding environmental factors;Yiyang City,which does not consider the impact of environmental variables,ranked 9th and 6th in terms of agricultural production efficiency in 2016 and 2018,and 7th and 3rd after excluding environmental factors.This means that environmental factors are an important factor in evaluating agricultural production efficiency.(2)Stochastic frontier regression analysis found that the five input factors of agricultural production in Dongting Lake area,namely,the number of agricultural employees,crop planting area,total power of agricultural machinery,irrigated farmland area,and fertilizer application amount,were mainly affected by three environmental factors,namely,urbanization,natural disasters,and the proportion of agricultural,forestry,water and water expenditure in the financial sector.There are significant differences in the nature and degree of the impact of environmental factors on agricultural investment.Urbanization has a negative impact on agricultural workers,a significant positive impact on fertilizer application,a negative impact on agricultural investment from natural disasters,and a positive impact on investment from the proportion of agricultural,forestry,and water expenditure to fiscal expenditure.(3)The maximum agricultural production efficiency values of Yueyang City,Changde City,and Yiyang City evaluated based on the three-stage DEA model of SBM are 0.911(2019),0.837(2019),and 0.880(2020),respectively.The weighted minimum agricultural production efficiency values of corresponding cities are 0.525(2000),0.475(2001),and 0.563(2001),respectively.From the trend of time change,the relative value of agricultural production efficiency gradually increases,It shows that the agricultural production performance in Dongting Lake area has gradually improved.(4)Research has shown that there is complementarity between different models,and the degree of impact of environmental factors on agricultural input factors is sensitive to the model;The agricultural production efficiency evaluated by three stage DEA models with different parameters and non parameters also varies depending on the model.This study not only analyzes the agricultural production efficiency of Dongting Lake Ecological Economic Zone from the perspective of temporal and spatial differentiation,but also provides a new analytical paradigm for the measurement of regional agricultural production efficiency.