IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Analyzing Inefficiency Using a Frontier Search Approach

Efficiency measurement naturally requires the definition of a frontier as a benchmark indicating efficiency. Usually a measure reflecting the distance of a data point to the frontier indicates the level of efficiency. One of the crucial characteristics to distinguish efficiency measurement tools is the way in which they construct the frontier. The class of deterministic and non parametric tools of constructing the frontier mainly comprises of tools associated with Data Envelopment Analysis. Coming in various flavors all DEA frontiers suffer of their piecewise construction giving rise to numerous vertices. Those vertices do not allow convenient analysis of the frontier properties such as computing elasticities and the like. In this paper we want to contribute to the class of deterministic and non parametric tools of constructing the frontier in an one output and n input setting. We suggest a new empirical approach drawing on functional search in the fashion of Koza's (1992) genetic programming. The frontier search algorithm employed evolves the functional form of the frontier and the parameters simultaneously. The frontier exhibits the neat property that it is smooth and differentiable enabling the computation of elasticities,for example. In particular we introduce both the idea and the algorithm of the frontier search procedure. We discuss the advantages and shortcomings with respect to empirical problems. The arguments brought forth in the preceding sections are illustrated by the investigation of an artificial example.

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.

File URL: http://www.wiwi.uni-augsburg.de/vwl/institut/paper/199.pdf
Download Restriction: no

Paper provided by Universitaet Augsburg, Institute for Economics in its series Discussion Paper Series with number 199.

as
in new window

Length: pages
Date of creation: Dec 2000
Date of revision:
Handle: RePEc:aug:augsbe:0199
Contact details of provider: Postal: Universitaetsstrasse 16, D-86159 Augsburg, Germany
Phone: +49 821 598 4060
Fax: +49 821 598 4217
Web page: http://www.wiwi.uni-augsburg.de/vwl/institut
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Schmertmann, Carl P, 1996. "Functional Search in Economics Using Genetic Programming," Computational Economics, Society for Computational Economics, vol. 9(4), pages 275-98, November.
  2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
  3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:aug:augsbe:0199. 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: (Dr. Albrecht Bossert)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.