Sensitivity Analysis to Efficiency Scores : How to Bootstrap in Nonparametric Frontier Models
Efficiency scores of production units are generally measured relative to an estimated production frontier. Nonparametric estimators (DEA, FDH, ... ) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data generating process in this complex framework and to propose a reasonable estimator of it. This provides a general methodology of bootstrapping in nonparametric frontier models. Some adapted methods are illustrated in analyzing the bootstrap sampling variations of input efficiency measures of electricity plants.
|Date of creation:||01 Jun 1995|
|Date of revision:|
|Contact details of provider:|| Postal: |
Fax: +32 10474304
Web page: http://www.uclouvain.be/core
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:cor:louvco:1995043. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alain GILLIS)
If references are entirely missing, you can add them using this form.