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Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency

Listed author(s):
  • Arabinda Das

    ()

    (Acharya Prafulla Chandra College)

Registered author(s):

    The paper considers the modeling and estimation of the stochastic frontier model where the error components are assumed to be correlated and the inefficiency error is assumed to be autocorrelated. The multivariate Farlie-Gumble-Morgenstern (FGM) and normal copula are used to capture both the contemporaneous and the temporal dependence between, and among, the noise and the inefficiency components. The intractable multiple integrals that appear in the likelihood function of the model are evaluated using the Halton sequence based Monte Carlo (MC) simulation technique. The consistency and the asymptotic efficiency of the resulting simulated maximum likelihood (SML) estimators of the present model parameters are established. Finally, the application of model using the SML method to the real life US airline data shows significant noise-inefficiency dependence and temporal dependence of inefficiency.

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    File URL: http://cejeme.eu/publishedarticles/2015-12-01-635740567480000000-8975.pdf
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    Article provided by CEJEME in its journal Central European Journal of Economic Modelling and Econometrics.

    Volume (Year): 7 (2015)
    Issue (Month): 2 (June)
    Pages: 111-126

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    Handle: RePEc:psc:journl:v:7:y:2015:i:2:p:111-126
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