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Makieła Kamil (Cracow University of Economics, Poland / Wydział Zarządzania)
Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models
Central European Journal of Economic Modelling and Econometrics (CEJEME), 2017, vol. 9, nr 1, s. 69-95, rys., tab., aneks, bibliogr. 26 poz.
Słowa kluczowe
Wnioskowanie bayesowskie, Efektywność kosztowa, Analiza stochastyczna, Stochastyczny model graniczny, Metoda SFA (stochastyczna analiza graniczna)
Bayesian inference, Cost effectiveness, Stochastic analysis, Stochastic frontier model, Stochastic Frontier Analysis (SFA)
summ.; Klasyfikacja JEL: C11, C23, C51, D24
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)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka Szkoły Głównej Handlowej w Warszawie
Biblioteka Główna Uniwersytetu Ekonomicznego w Poznaniu
Pełny tekst
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