Bayesian estimation of inefficiency heterogeneity in stochastic frontier models
Michael Peter Wiper,
Jorge Galan () and
Helena Veiga ()
DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, it is not clear in general in which component of the error distribution the covariates should be included. In the classical context, some studies include covariates in the scale parameter of the inefficiency with the property of preserving the shape of its distribution. We extend this idea to Bayesian inference for stochastic frontier models capturing both observed and unobserved heterogeneity under half normal, truncated and exponential distributed inefficiencies. We use the WinBugs package to implement our approach throughout. Our findings using two real data sets, illustrate the relevant effects on shrinking and separating individual posterior efficiencies when heterogeneity affects the scale of the inefficiency. We also see that the inclusion of unobserved heterogeneity is still relevant when no observable covariates are available.
Keywords: Stochastic; Frontier; Models; Heterogeneity; Bayesian; Inference (search for similar items in EconPapers)
JEL-codes: C11 C51 C23 D24 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-eff and nep-ore
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Journal Article: Bayesian estimation of inefficiency heterogeneity in stochastic frontier models (2014)
Working Paper: Bayesian Estimation of Inefficiency Heterogeneity in Stochastic Frontier Models (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws121007
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