Stochastic frontier models with dependent error components
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
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 11 (2008)
Issue (Month): 1 (March)
|Contact details of provider:|| Postal: 2 Dean Trench Street, Westminster, SW1P 3HE|
Phone: +44 20 3137 6301
Web page: http://www.res.org.uk/
More information through EDIRC
|Order Information:||Web: http://www.ectj.org|