Zero-inefficiency stochastic frontier models with varying mixing proportion:a semiparametric approach

Tran, Kien C. and Tsionas, Efthymios (2016) Zero-inefficiency stochastic frontier models with varying mixing proportion:a semiparametric approach. European Journal of Operational Research, 249 (3). pp. 1113-1123. ISSN 0377-2217

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Abstract

In this paper, we propose a semiparametric version of the zero-inefficiency stochastic frontier model of Kumbhakar, Parmeter, and Tsionas (2013) by allowing for the proportion of firms that are fully efficient to depend on a set of covariates via unknown smooth function. We propose a (iterative) backfitting local maximum likelihood estimation procedure that achieves the optimal convergence rates of both frontier parameters and the nonparametric function of the probability of being efficient. We derive the asymptotic bias and variance of the proposed estimator and establish its asymptotic normality. In addition, we discuss how to test for parametric specification of the proportion of firms that are fully efficient as well as how to test for the presence of fully inefficient firms, based on the sieve likelihood ratio statistics. The finite sample behaviors of the proposed estimation procedure and tests are examined using Monte Carlo simulations. An empirical application is further presented to demonstrate the usefulness of the proposed methodology.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 249, 3, 2016 DOI: 10.1016/j.ejor.2015.10.019
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1802
Subjects:
ID Code:
78589
Deposited By:
Deposited On:
09 Mar 2016 08:48
Refereed?:
Yes
Published?:
Published
Last Modified:
05 Apr 2020 03:51