Another Look at the American Electrical Utility Data
AbstractThe American electric utility data, which are frequently analyzed in the context of frontier models, can be explained by a linear model without inefficiencies. the observed maximum likelihood for this linear model is very mildly smaller than the maximum likelihood for more flexible stochastic frontier models and the log-likelihood-ratio statistic for an approxImate [chi. exp2] test of the simple least squares model against normal exponential and normal-gamma stochastic frontier models is far from significant.
Download InfoIf 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.
Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 1994007.
Date of creation: 01 Jan 1994
Date of revision:
Contact details of provider:
Postal: Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium)
Fax: +32 10474304
Web page: http://www.uclouvain.be/core
More information through EDIRC
Exploratory data analysis; ordinary least squares; normal-gamma composed errors; maximum likelihood;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Behr, Andreas & Tente, Sebastian, 2008. "Stochastic frontier analysis by means of maximum likelihood and the method of moments," Discussion Paper Series 2: Banking and Financial Studies 2008,19, Deutsche Bundesbank, Research Centre.
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.