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Efficiency analysis trees: A new methodology for estimating production frontiers through decision trees

机译:效率分析树:通过决策树估算生产边界的新方法

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In this paper, we introduce a new methodology based on regression trees for estimating production frontiers satisfying fundamental postulates of microeconomics, such as free disposability. This new approach, baptized as Efficiency Analysis Trees (EAT), shares some similarities with the Free Disposal Hull (FDH) technique. However, and in contrast to FDH, EAT overcomes the problem of overfitting by using cross-validation to prune back the deep tree obtained in the first stage. Finally, the performance of EAT is measured via Monte Carlo simulations, showing that the new approach reduces the mean squared error associated with the estimation of the true frontier by between 13% and 70% in comparison with the standard FDH. (C) 2020 Elsevier Ltd. All rights reserved.
机译:在本文中,我们介绍了一种基于回归树的新方法,用于估算满足微观​​经济学的基本型物体的生产前沿,例如自由可用性。这种新方法,作为效率分析树(饮食),与免费处置船体(FDH)技术共享一些相似之处。然而,与FDH相比,饮食克服了通过使用交叉验证来修剪第一阶段获得的深树的过度装备的问题。最后,通过Monte Carlo模拟测量吃的性能,表明新方法与标准FDH相比,新方法减少了与真实边疆估计的平均平方误差与标准FDH相比的13%和70%。 (c)2020 elestvier有限公司保留所有权利。

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