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Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA

机译:具有多个环境有害变量的环境效率;用SFA和DEA估算

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摘要

The objective of this paper is to estimate comprehensive environmental efficiency measures for Dutch dairy farms. The environmental efficiency scores are based on the nitrogen surplus, phosphate surplus and the total (direct and indirect) energy use of an unbalanced panel of dairy farms. We define environmental efficiency as the ratio of minimum feasible to observed use of multiple environmentally detrimental inputs, conditional on observed levels of output and the conventional inputs. We compare two methods for the calculation of efficiency; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). This paper reveals the strengths and weaknesses for estimating environmental efficiency of the methods applied. Both SFA and DEA can estimate environmental efficiency scores. The mean technical efficiency scores (output-oriented, SFA 89%, DEA 78%) and the mean comprehensive environmental efficiency scores (SFA 80%, DEA 52%) differ between the two methods. SFA allows hypothesis testing, and the monotonicity hypothesis is rejected for the specification including phosphate surplus. DEA can calculate environmental efficiency scores for all specifications, because regularity is imposed in this method.
机译:本文的目的是评估荷兰奶牛场的综合环境效率措施。环境效率得分基于不平衡的奶牛场中氮的过剩,磷酸盐的过剩和总(直接和间接)能源使用。我们将环境效率定义为观察到的对多种环境有害输入的使用的最小可行比率,该比率取决于观察到的输出水平和常规输入。我们比较了两种计算效率的方法。即随机边界分析(SFA)和数据包络分析(DEA)。本文揭示了估算所采用方法的环境效率的优缺点。 SFA和DEA都可以估算环境效率得分。两种方法之间的平均技术效率得分(以产出为导向,SFA为89%,DEA为78%)和平均综合环境效率得分(SFA为80%,DEA 52%)。 SFA允许进行假设检验,而对于包括磷酸盐过剩在内的规范,单调性假设被拒绝。 DEA可以计算所有规格的环境效率得分,因为这种方法具有规律性。

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