Stochastic frontier models with flexible random coefficients

Mike G. Tsionas

Global Business and Economics Review, 2018, vol. 20, issue 1, 126-139

Abstract: We propose a stochastic frontier model with random coefficients having a flexible distribution. The distribution is modelled non-parametrically. It is shown that maximum likelihood estimation reduces to a fixed-point problem. A fixed-point iteration is proposed and we show that there is a unique regular fixed point. The fixed-point iteration is used in the context of MCMC to perform inferences for all unknown parameters including the optimal support of the distribution of random coefficients.

Keywords: stochastic frontier models; random coefficients; flexible distribution; Bayesian inference; MCMC. (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:ids:gbusec:v:20:y:2018:i:1:p:126-139

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