Work

Bayesian stochastic frontier models under the skew-normal half-normal settings

Year: 2025

Type: article

Abstract: Recently, a skew normal-based stochastic frontier model has emerged as a promising tool for efficiency analysis. In this paper, a Bayesian framework for statistical inference is presented, incorporating both informative and non-informative prior knowledge. The efficacy of the Bayesian approach is evaluated through rigorous examination using both simulation data and real data from a manufacturing productivity study. A comprehensive comparison with the conventional maximum likelihood approach is conducted. Results from both simulated and empirical investigations unequivocally demonstrate the superior performance of the Bayesian methodology.

Source: Journal of Productivity Analysis

DOI: 10.1007/s11123-025-00757-3

Authors: Zheng Wei, S. T. Boris Choy, Tonghui Wang, Xiaonan Zhu

Institutions: Texas A&M University – Corpus Christi, The University of Sydney, New Mexico State University, University of North Alabama

Language: English

Topic: Efficiency Analysis Using DEA

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $3,190

OpenAlex ID: W4408864591

FWCI: 1.589

Cites: 37

Cited by: 2

Related to: 10