Pseudolikelihood estimation of the stochastic frontier model
Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it has been applied using maximum likelihood estimation. An alternative approach, pseudolikelihood estimation, decouples estimation of the error component structure and the production frontier, has been adopted in both the nonparametric and panel data settings. To date, no formal comparison has yet to be conducted comparing these methods in a standard, parametric cross sectional framework. We produce a comparison of these two competing methods using Monte Carlo simulations. Our results indicate that pseudolikelihood estimation enjoys almost identical performance to maximum likelihood estimation across a range of scenarios and performance metrics, and for certain metrics outperforms maximum likelihood estimation when the distribution of inefficiency is incorrectly specied.
|Date of creation:||2017|
|Contact details of provider:|| Postal: Hohenzollernstraße 1-3, 45128 Essen|
Web page: http://www.rwi-essen.de/
More information through EDIRC
References listed on IDEAS
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.:
- Oleg Badunenko & Daniel J. Henderson & Subal C. Kumbhakar, 2012.
"When, where and how to perform efficiency estimation,"
Journal of the Royal Statistical Society Series A,
Royal Statistical Society, vol. 175(4), pages 863-892, October.
- Oleg Badunenko & Daniel J. Henderson & Subal C. Kumbhakar, 2011. "When, where and how to perform efficiency estimation," Cologne Graduate School Working Paper Series 02-06, Cologne Graduate School in Management, Economics and Social Sciences.
- Badunenko, Oleg & Henderson, Daniel J. & Kumbhakar, Subal C., 2011. "When, Where and How to Perform Efficiency Estimation," IZA Discussion Papers 5997, Institute for the Study of Labor (IZA).
- Badunenko, Oleg & Henderson, Daniel J. & Kumbhakar, Subal C., 2011. "When, where and how to perform efficiency estimation," MPRA Paper 33467, University Library of Munich, Germany.
- Henderson, Daniel J. & Kumbhakar, Subal C. & Li, Qi & Parmeter, Christopher F., 2015. "Smooth coefficient estimation of a seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 148-162.
- Olson, Jerome A. & Schmidt, Peter & Waldman, Donald M., 1980. "A Monte Carlo study of estimators of stochastic frontier production functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 67-82, May.
- Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
- Kumbhakar, Subal C. & Lien, Gudbrand D. & Hardaker, J. Brian, 2011. "Technical efficiency in competing panel data models: A study of Norwegian grain farming," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114673, European Association of Agricultural Economists.
- Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514.
- Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464.
- Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
- Christopher Parmeter & Kai Sun & Daniel Henderson & Subal Kumbhakar, 2014. "Estimation and inference under economic restrictions," Journal of Productivity Analysis, Springer, vol. 41(1), pages 111-129, February.
- Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:zbw:rwirep:693. 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: (ZBW - German National Library of Economics)
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.