A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers
學年 109
學期 1
出版(發表)日期 2020-08-19
作品名稱 A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers
作品名稱(其他語言)
著者 Christine Amsler; Yi Yi Chen; Peter Schimdt; Hung Jen Wang
單位
出版者
著錄名稱、卷期、頁數 Empirical Economics 60, p.353–363
摘要 This paper proposes a stochastic frontiermodel with three composed errors, and therefore six error components. As in the metafrontier literature, firms belong to groups with a group-specific frontier. A firm has a level of short-run and long-run inefficiency relative to its group-specific frontier, as in existing models with two composed errors and four error components. But now there is also a group-specific inefficiency, that is, a shortfall of the group-specific frontier from the best practice metafrontier. The paper shows how to estimate this model and how to extract predictions of the various inefficiencies.
關鍵字 Stochastic frontier;Panel data;Hierarchical model;Metafrontier;Inefficiency
語言 en
ISSN 1435-8921
期刊性質 國外
收錄於 SSCI EconLit
產學合作 國外
通訊作者 schmidtp@msu.edu
審稿制度
國別 DEU
公開徵稿
出版型式 ,電子版
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