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Stochastic frontier models with dependent error components

  • Murray D. Smith
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    of the stochastic frontier model are assumed to be independent random variables. By employing the copula approach to statistical modelling, the joint behaviour of U and V can be parametrized thereby allowing the data the opportunity to determine the adequacy of the independence assumption. In this context, three examples of the copula approach are given: the first is algebraic (the Logistic-Exponential stochastic frontier model with margins bound by the Farlie--Gumbel--Morgenstern copula), the second uses a cross-section of cost data sampled from the US electrical power industry and the third constructs a model for panel data that is then used to conduct a Monte Carlo exercise in which estimator bias is examined when the dependence structure is incorrectly ignored. Copyright Royal Economic Society 2007

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    Article provided by Royal Economic Society in its journal Econometrics Journal.

    Volume (Year): 11 (2008)
    Issue (Month): 1 (03)
    Pages: 172-192

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    Handle: RePEc:ect:emjrnl:v:11:y:2008:i:1:p:172-192
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