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Measuring port efficiency using bootstrapped DEA: the case of Vietnamese ports

机译:使用自举DEA来衡量港口效率:越南港口的情况

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摘要

Standard data envelopment analysis (DEA) tends to be sensitive to the number of variables of a chosen sample, and it is unable to account for their random nature. Standard DEA can exhibit statistical inconsistency, biased results, and an arguable inference process. Thus, in this study, an efficiency evaluation method is used to overcome these limitations, especially since no studies of port efficiency have addressed this issue. This study applies bootstrapped DEA to a sample of the 43 largest Vietnamese ports and compares the results with those from stochastic frontier analysis (SFA) and standard DEA. The results show that while the efficiency scores obtained from the three methods provide useful and consistent measures of the ports' efficiency, they differ significantly. Furthermore, while the efficiency scores produced by bootstrapped DEA are consistent, unbiased, and not sensitive to the sample size, standard DEA and SFA yield efficiency scores that are much larger than bootstrapped DEA. In addition, bootstrapped DEA provides the confidence intervals for efficiency scores and allows for hypothesis tests of port performance.
机译:标准数据包络分析(DEA)往往对所选样本变量的数量敏感,并且无法解释其随机性。标准DEA可能表现出统计上的不一致,偏差的结果和可争论的推理过程。因此,在这项研究中,使用效率评估方法来克服这些局限性,特别是因为没有港口效率研究解决了这个问题。本研究将自举DEA应用于43个越南最大港口的样本,并将结果与​​随机前沿分析(SFA)和标准DEA的结果进行比较。结果表明,尽管从这三种方法获得的效率得分可提供有用且一致的港口效率衡量指标,但它们之间存在显着差异。此外,尽管自举DEA产生的效率得分是一致的,无偏见的,而且对样本量不敏感,但标准DEA和SFA的效率得分远高于自举DEA。此外,自举DEA为效率得分提供了置信区间,并允许对端口性能进行假设检验。

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