Evaluating the Importance of Multiple Imputations of Missing Data on Stochastic Frontier Analysis Efficiency Measures
AbstractThe robustness of the multiple imputation of missing data on parame- ter coefficients and efficiency measures is evaluated using stochastic frontier analysis in the panel Bayesian context. Second, the implications of multi- ple imputations on stochastic frontier analysis technical efficiency measures under alternative distributional assumptions−half-normal, truncation and exponential is evaluated. Empirical estimates indicate difference in the between-variance and within-variance of parameter coefficients estimated from stochastic frontier analysis and generalized linear models. Within stochastic frontier analysis, the between-variance and within-variance of technical efficiency are different across the three alternative distributional assumptions. Finally, results from this study indicate that even though the between- and within variance of multiple imputed data is close to zero, between- and within-variance of production function parameters, as well as, the technical efficiency measures are different.
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 150792.
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
Agricultural and Food Policy; Research Methods/ Statistical Methods;
This paper has been announced in the following NEP Reports:
- NEP-AGR-2013-07-05 (Agricultural Economics)
- NEP-ALL-2013-07-05 (All new papers)
- NEP-ECM-2013-07-05 (Econometrics)
- NEP-EFF-2013-07-05 (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.:
- 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.
- George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
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.