Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis

Bayesian Model Averaging and Prior Sensitivity in Stochastic Frontier Analysis

This paper discusses Bayesian model averaging (BMA) in Stochastic Frontier Analysis and investigates inference sensitivity to prior assumptions made about the scale parameter of (in)efficiency. We turn our attention to the “standard” prior specifications for the popular normal-half-normal and normal...

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Bibliographic Details
Main Authors: Kamil Makieła, Błażej Mazur
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Econometrics
Subjects:
stochastic frontier analysis
Bayesian model averaging
Bayesian inference
model uncertainty
efficiency analysis
public policy
Online Access:https://www.mdpi.com/2225-1146/8/2/13

Internet

https://www.mdpi.com/2225-1146/8/2/13

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