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Showing 1 results for stochastic Frontier Models
Mrs Bahareh Feizi, Dr. Ahmad Pourdarvish,
Volume 11, Issue 1 (9-2020)
Abstract
A branch of researches is devoted to semiparametric and nonparametric estimation
of stochastic frontier models to employ the advantages in the operations research
technique of data envelopment analysis. The stochastic frontier model is the
parametric competition of data envelopment technique. This paper focused on a
nonlinear autoregressive stochastic frontier production model that covers dynamic
technical inefficiency. We consider a semiparametric method for the model by
combining a parametric regression estimator with a nonparametric adjustment. The
unknown parameters are estimated using the full maximum likelihood and pairwise
composite likelihood methods. After the parameters are estimated by parametric
methods , the obtained regression function is adjusted by a nonparametric factor, and
the nonparametric factor is obtained through a natural consideration of the local -
fitting criterion. Some asymptotic and simulation results for the semiparametric
method are discussed
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