A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers

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题名:	A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers
作者:	Christine Amsler;Yi Yi Chen;Peter Schimdt;Hung Jen Wang
关键词:	Stochastic frontier;Panel data;Hierarchical model;Metafrontier;Inefficiency
日期:	2020-08-19
上传时间:	2021-01-21 12:10:15 (UTC+8)
出版者:	Springer-Verlag GmbH Germany, part of Springer Nature 2020
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.
關聯:	Empirical Economics 60, p.53–363
DOI:	10.1007/s00181-020-01929-w
显示于类别:	[經濟學系暨研究所] 期刊論文

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