Nonparametric Analysis of Technology and Productivity under Non-Convexity
AbstractThis paper investigates the nonparametric analysis of technology under non-convexity. The analysis extends two approaches now commonly used in efficiency and productivity analysis: Data Envelopment Analysis (DEA) where convexity is imposed; and Free Disposal Hull (FDH) models. We argue that, while the FDH model allows for non-convexity, its representation of non-convexity is too extreme. We propose a new nonparametric model that relies on a neighborhood-based technology assessment which allows for less extreme forms of non-convexity. The distinctive feature of our approach is that it allows for non-convexity to arise in any part of the feasible set. We show how it can be implemented empirically by solving simple linear programming problems. And we illustrate the usefulness of the approach in an empirical application to the analysis of technical and scale efficiency on Korean farms.
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 Agricultural and Applied Economics Association in its series 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. with number 149684.
Date of creation: 2013
Date of revision:
Contact details of provider:
Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page: http://www.aaea.org
More information through EDIRC
technology; productivity; nonparametric; non-convexity; Farm Management; Production Economics; Productivity Analysis; Research Methods/ Statistical Methods;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-24 (All new papers)
- NEP-ECM-2013-06-24 (Econometrics)
- NEP-EFF-2013-06-24 (Efficiency & Productivity)
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.:
- Leopold Simar & Valentin Zelenyuk, 2008.
"Stochastic FDH/DEA estimators for Frontier Analysis,"
8, Kyiv School of Economics.
- Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
- Kristof Witte & Rui Marques, 2011.
"Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies,"
Journal of Productivity Analysis,
Springer, vol. 35(3), pages 213-226, June.
- Kristof De Witte & Rui C. Marcques, 2008. "Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies," Center for Economic Studies - Discussion papers ces0822, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
- Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
- Leleu, Herve, 2006. "A linear programming framework for free disposal hull technologies and cost functions: Primal and dual models," European Journal of Operational Research, Elsevier, vol. 168(2), pages 340-344, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search).
If references are entirely missing, you can add them using this form.