A Semiparametric Stochastic Frontier Model with Correlated Effects

Gholamreza Hajargasht and William Griffiths ()

A chapter in Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B, 2019, vol. 40B, pp 1-28 from Emerald Group Publishing Limited

Abstract: We consider a semiparametric panel stochastic frontier model where one-sided firm effects representing inefficiencies are correlated with the regressors. A form of the Chamberlain-Mundlak device is used to relate the logarithm of the effects to the regressors resulting in a lognormal distribution for the effects. The function describing the technology is modeled nonparametrically using penalized splines. Both Bayesian and non-Bayesian approaches to estimation are considered, with an emphasis on Bayesian estimation. A Monte Carlo experiment is used to investigate the consequences of ignoring correlation between the effects and the regressors, and choosing the wrong functional form for the technology.

Keywords: Technical efficiency; endogeneity; penalized splines; Gibbs sampling; maximum simulated likelihood; lognormal distribution (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-90532019000040b002

DOI: 10.1108/S0731-90532019000040B002

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