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Measuring the technical efficiency of cotton farms in Turkey using stochastic frontier and data envelopment analysis.

机译:使用随机边界和数据包络分析来衡量土耳其棉花农场的技术效率。

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The determination of technical efficiency for cotton farms can be invaluable in estimating optimum farming practices and in identifying strategic options for the industry. This paper investigates the productive efficiency of a sample of farmers in Turkey's Aegean region by estimating a stochastic frontier production function (SFA), constant returns to scale (CRS) and variable returns to scale (VRS) using output-oriented data envelopment analysis (DEA). Data were obtained from 198 cotton farms using structured questionnaire interviews. The estimates of technical efficiency based on these two frontier methods were compared. While efficiency scores for cotton farms differed between the SFA and the DEA models, the mean efficiency scores are quite low for the CRS DEA model compared with the VRS DEA and SFA approaches. The mean efficiency measure (0.91) obtained from the stochastic frontier was higher than that calculated from the VRS DEA (0.77) and CRS DEA (0.25). This study suggests that more efficient political instruments need to be adopted to review current subsidies because of increasing outlays for diesel oil used in cotton farming.
机译:确定棉花农场的技术效率对于评估最佳耕作方法和确定该行业的战略选择而言是无价的。本文通过使用面向输出的数据包络分析(DEA)估计随机前沿生产函数(SFA),规模收益率不变(CRS)和规模收益率可变(VRS),调查了土耳其爱琴海地区农民的生产效率。 )。使用结构化问卷访问从198个棉场获得数据。比较了基于这两种前沿方法的技术效率估算。虽然SFA和DEA模型之间的棉花农场效率得分不同,但与VRS DEA和SFA方法相比,CRS DEA模型的平均效率得分非常低。从随机边界获得的平均效率度量(0.91)高于从VRS DEA(0.77)和CRS DEA(0.25)计算得出的平均效率度量。这项研究表明,由于用于棉花种植的柴油支出增加,因此需要采用更有效的政治手段来审查当前的补贴。

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