Goodness of fit tests in stochastic frontier models

Wei Siang Wang; Christine Amsler; Peter Schmidt

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Goodness of fit tests in stochastic frontier models

机译：随机边界模型中的拟合优度

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摘要

In this paper we discuss goodness of fit tests for the distribution of technical inefficiency in stochastic frontier models. If we maintain the hypothesis that the assumed normal distribution for statistical noise is correct, the assumed distribution for technical inefficiency is testable. We show that a goodness of fit test can be based on the distribution of estimated technical efficiency, or equivalently on the distribution of the composed error term. We consider both the Pearson X~2 test and the Kolmogorov-Smirnov test. We provide simulation results to show the extent to which the tests are reliable in finite samples.

机译：在本文中，我们讨论了随机边界模型中技术效率低下分布的拟合检验的优缺点。如果我们维持统计噪声假定正态分布正确的假设，则技术效率低下的假定分布是可检验的。我们证明拟合优度可以基于估计的技术效率的分布，或者等效地基于组合误差项的分布。我们同时考虑了Pearson X〜2测试和Kolmogorov-Smirnov测试。我们提供了仿真结果，以显示有限样本中测试的可靠程度。

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来源
《Journal of productivity analysis》 |2011年第2期|p.95-118|共24页
作者
Wei Siang Wang; Christine Amsler; Peter Schmidt;
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作者单位

Nanyang Technological University, Singapore, Singapore;

Michigan State University, East Lansing, MI, USA;

Michigan State University, East Lansing, MI, USA,Yonsei University, Seoul, South Korea;

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正文语种 eng
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关键词
stochastic frontier model; goodness of fit test; kolmogorov-smirnov test;

机译：随机边界模型;拟合优度检验;kolmogorov-smirnov检验;

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Goodness of fit tests in stochastic frontier models

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