Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency

• Autorzy: Arabinda Das
• Języki publikacji: EN

Abstrakty

EN

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. (original abstract)

Słowa kluczowe

EN

Stochastic frontier model; Stochastic models; Copula Functions; Monte Carlo simulation

PL

Stochastyczny model graniczny; Modele stochastyczne; Funkcje połączeń; Symulacja Monte Carlo

• Czasopismo: Central European Journal of Economic Modelling and Econometrics (CEJEME)
• Rocznik: 2015
• Tom: 7
• Numer: nr 2
• Strony: 111--126

Twórcy

autor

Arabinda Das

• Acharya Prafulla Chandra College, Indie

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Identyfikatory

DOI

DOI: 10.24425/cejeme.2015.119212