Stochastic frontier models with dependent error components
Murray D. Smith
Econometrics Journal, 2008, vol. 11, issue 1, 172-192
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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