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Efficient estimation of true fixed-effects stochastic frontier models

Ruggero Bellio and Luca Grassetti (luca.grassetti@uniud.it)
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Ruggero Bellio: University of Udine
Luca Grassetti: University of Udine

Journal of Productivity Analysis, 2024, vol. 62, issue 1, No 6, 118 pages

Abstract: Abstract Fixed-effects modeling has become the method of choice in several panel data settings, including models for stochastic frontier analysis. A notable instance of stochastic frontier panel data models is the true fixed-effects model, which allows disentangling unit heterogeneity from efficiency evaluations. While such a model is theoretically appealing, its estimation is hampered by incidental parameters. This note proposes a simple and rather general estimation approach where the unit-specific intercepts are integrated out of the likelihood function. We apply the theory of composite group families to the model of interest and demonstrate that the resulting integrated likelihood is a marginal likelihood with desirable inferential properties. The derivation of the result is provided in full, along with some connections with the existing literature and computational details. The method is illustrated for three notable models, given by the normal-half normal model, the heteroscedastic exponential model, and the normal-gamma model. The results of simulation experiments highlight the properties of the methodology.

Keywords: Fixed effects; Marginal likelihood; Panel data; Stochastic frontier (search for similar items in EconPapers)
JEL-codes: C13 C46 C5 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11123-024-00725-3

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