Semiparametric Estimation of Stochastic Frontiers A Bayesian Penalized Approach
Almost all previous approaches to estimating semiparametric frontier models, where the functional form for the production (cost) function is unknown, have been local nonparametric (ie. kernel) approaches. In this paper we use a penalized (ie. spline) approach. We show how this approach can be applied to a variety of frontier models, including panel models with fixed and random effects, within a Bayesian framework. We also apply our approach to different multivariate settings, including additive and additive with interaction models. The latter is a promising model because it is very flexible and does not suffer the severe curse of dimensionality problem common with fully nonparametric functions. We illustrate our method using a simulated example.
|Date of creation:||Aug 2003|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +61 7 3365 6570
Fax: +61 7 3365 7299
Web page: http://www.uq.edu.au/economics/
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.:
- Smith, M. & Kohn, R., .
"Nonparametric Regression using Bayesian Variable Selection,"
Statistics Working Paper
_009, Australian Graduate School of Management.
- Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
- Park, B.U. & Simar, L., 1992.
"Efficient Semiparametric Estimation in Stochastic Frontier Model,"
9201, Catholique de Louvain - Institut de statistique.
- PARK, Byeong & SIMAR, Léopold, 1992. "Efficient semiparametric estimation in stochastic frontier model," CORE Discussion Papers 1992013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Park, B. U. & Simar, L., . "Efficient semiparametric estimation in a stochastic frontier model," CORE Discussion Papers RP -1113, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Adams, Robert M & Berger, Allen N & Sickles, Robin C, 1999. "Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 349-58, July.
- 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.
When requesting a correction, please mention this item's handle: RePEc:qld:uqcepa:04. 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: (SOE IT)
If references are entirely missing, you can add them using this form.