Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models

• Autorzy: Kamil Makieła
• Języki publikacji: EN

Abstrakty

EN

The paper investigates Bayesian approach to estimate generalized true random-effects models (GTRE). The analysis shows that under suitably defined priors for transient and persistent inefficiency terms the posterior characteristics of such models are well approximated using simple Gibbs sampling. No model re-parameterization is required. The proposed modification not only allows us to make more reasonable (less informative) assumptions as regards prior transient and persistent inefficiency distribution but also appears to be more reliable in handling especially noisy datasets. Empirical application furthers the research into stochastic frontier analysis using GTRE models by examining the relationship between inefficiency terms in GTRE, true random-effects, generalized stochastic frontier and a standard stochastic frontier model. (original abstract)

Słowa kluczowe

EN

Bayesian inference; Cost effectiveness; Stochastic analysis; Stochastic frontier model; Stochastic Frontier Analysis (SFA)

PL

Wnioskowanie bayesowskie; Efektywność kosztowa; Analiza stochastyczna; Stochastyczny model graniczny; Metoda SFA (stochastyczna analiza graniczna)

• Czasopismo: Central European Journal of Economic Modelling and Econometrics (CEJEME)
• Rocznik: 2017
• Tom: 9
• Numer: nr 1
• Strony: 69--95

Twórcy

autor

Kamil Makieła

• Cracow University of Economics, Poland

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