Bayesian Estimation of Technical Efficiency of a Single Input
The authors propose estimation of a stochastic production frontier model within a Bayesian framework to obtain the posterior distribution of single-input-oriented technical efficiency at the firm level. This method can be used to estimate the environmental efficiency of agricultural production when the technology interaction with the environment is modeled via public inputs such as soil quality and environmental conditions. All computations are carried out using Markov chain Monte Carlo methods. The approach is illustrated through its application to production data from Ukrainian collective farms.
|Date of creation:||Nov 2000|
|Date of revision:|
|Contact details of provider:|| Postal: 578 Heady Hall, Ames, IA 50011-1070|
Web page: http://www.fapri.iastate.edu/
More information through EDIRC
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.:
- Broeck, Julien Van den & Steel, Mark F.J. & Osiewalski, Jacek & Koop, Gary, 1992.
"Stochastic frontier models: a bayesian perspective,"
UC3M Working papers. Economics
2823, Universidad Carlos III de Madrid. Departamento de Economía.
- van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
When requesting a correction, please mention this item's handle: RePEc:ias:fpaper:00-wp254. 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: ()
If references are entirely missing, you can add them using this form.