Aggregation issues in the estimation of linear programming productivity measures
AbstractThis paper demonstrates the sensitivity of the linear programming approach in the estimation of productivity measures in the primal framework. Specifically, the sensitivity to the number of constraints (level of dis-aggregation) and imposition of returns to scale constraints is evaluated. Further, the shadow or dual values are recovered from the linear program and compared to the market prices used in the ideal Fisher index approach. Empirical application to U.S. state-level time series data from 1960-2004 reveal productivity change decreases with increases in the number of constraints. Divergence in productivity measures is observed due to the choice of method imposed, various levels of commodity/input aggregation, and technology assumptions. Due to the piecewise linear approximation of the nonparametric programming approach, the shadow share-weights are skewed leading to the difference in the productivity measures due to aggregation.
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.
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.
Bibliographic InfoArticle provided by Universidad del CEMA in its journal Journal of Applied Economics.
Volume (Year): XV (2012)
Issue (Month): (May)
Contact details of provider:
Postal: Av. Córdoba 374, (C1054AAP) Capital Federal
Phone: (5411) 6314-3000
Fax: (5411) 4314-1654
Web page: http://www.cema.edu.ar/publicaciones/jae.html
More information through EDIRC
aggregation; share-weights; single and multiple output and input; Malmquist productivity index; Malmquist total factor productivity index;
Other versions of this item:
- Shaik, Saleem & Mishra, Ashok K. & Atwood, Joseph A., 2011. "Aggregation Issues in the Estimation of Linear Programming Productivity Measures," Agribusiness & Applied Economics Report 101783, North Dakota State University, Department of Agribusiness and Applied Economics.
- O3 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
- Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
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.:
- Fare, Rolf & Zelenyuk, Valentin, 2003. "On aggregate Farrell efficiencies," European Journal of Operational Research, Elsevier, vol. 146(3), pages 615-620, May.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Valeria Dowding).
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.