Expected efficiency ranks from parametric stochastic frontier models
作者： William C. Horrace , Seth Richards-Shubik , Ian A. Wright
DOI: 10.1007/S00181-014-0808-8
关键词: Statistics 、 Conditional probability 、 Mathematics 、 Conditional variance 、 Conditional probability distribution 、 Point estimation 、 Parametric statistics 、 Ranking 、 Monte Carlo method 、 Order statistic 、 Econometrics
摘要: In the stochastic frontier model, we extend multivariate probability statements of Horrace (J Econom, 126:335–354, 2005) to calculate conditional that a firm is any particular efficiency rank in sample. From this, construct expected for each firm. Compared traditional ranked point estimates, firm-level ranks are more informative about degree uncertainty ranking. The may be useful empiricists. A Monte Carlo study and an empirical example provided.
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