Scopus İndeksli Açık & Kapalı Erişimli Yayınlar

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    New Bayesian Estimators for the Incidence of Inefficiency in the Cases Without a Rule of Thumb
    (2021) Unsal, Mehmet Guray
    Recently, the incidence of inefficiency (IOI) is a subject to obtain the statistical properties of Data Envelopment Analysis by considering it as a variable. In this paper, new Bayesian estimators which reflect the empirical distribution structure of the IOI for the cases without a rule of thumb are investigated. A simulation study is conducted to observe the effects of the right (positively) skewed prior. Furthermore, the IOI value of the cities in Turkey is estimated by using the right skewed prior. It can be observed that the effects of the right skewed priors on the Bayesian estimators are successful in terms of absolute errors. Highlights In this study, new Bayesian estimators for the incidence of inefficiency are investigated for the cases without a rule of thumb. It is observed that the right (positively) skewed priors can be used for the cases without a rule of thumb. The effects of the prior on the Bayesian estimators are successful in terms of absolute errors. The incidence of inefficiency value for socio-economic data of the cities in Turkey is estimated by using the right skewed prior.