The conditional mode in parametric frontier models
William Horrace,
Hyunseok Jung (hj020@uark.edu) and
Yi Yang
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Hyunseok Jung: University of Arkansas
Yi Yang: Amazon.com
Journal of Productivity Analysis, 2023, vol. 60, issue 3, No 8, 333-343
Abstract:
Abstract We survey formulations of the conditional mode estimator for technical inefficiency in parametric stochastic frontier models with Normal errors and introduce new formulations for models with Laplace errors. We prove that the conditional mode estimator in the Normal-Exponential model achieves near-minimax optimality by estimating small inefficiencies as exactly zero. We also consider a rule for selecting a subset of maximally efficient firms based on zero conditional mode estimates and show that the subset has reasonably high probability of containing the most efficient firm, particularly when inefficiency is exponentially distributed. We include an empirical example demonstrating the merits of the conditional mode estimator.
Keywords: Stochastic frontier model; Firm-level inefficiency; Conditional mode; Minimax optimality; Ranking and selection (search for similar items in EconPapers)
Date: 2023
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Working Paper: The Conditional Mode in Parametric Frontier Models (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:60:y:2023:i:3:d:10.1007_s11123-023-00699-8
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DOI: 10.1007/s11123-023-00699-8
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