IDEAS home Printed from https://ideas.repec.org/p/hhs/hastef/0229.html
   My bibliography  Save this paper

A Monte Carlo Analysis of Technical Inefficiency Predictors

Author

Listed:
  • Kumbhakar, Subal C.

    (Department of Economics)

  • Löthgren, Mickael

    () (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

This paper studies performance of both point and interval predictors of technical inefficiency in the stochastic production frontier model using a Monte Carlo experiment. In point prediction we use the Jondrow et al. (1980) point predictor of technical inefficiency, while for interval prediction the Horrace and Schmidt (1996) and Hjalmarsson et al. (1996) results are used. When ML estimators are used we find negative bias in point predictions. MSEs are found to decline as the sample size increases. The mean empirical coverage accuracy of the confidence intervals are significantly below the theoretical confidence level for all values of the variance ratio.

Suggested Citation

  • Kumbhakar, Subal C. & Löthgren, Mickael, 1998. "A Monte Carlo Analysis of Technical Inefficiency Predictors," SSE/EFI Working Paper Series in Economics and Finance 229, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0229
    as

    Download full text from publisher

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.pdf.zip
    File Function: main text
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.pdf
    File Function: main text
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.ps.zip
    File Function: main text
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.ps
    File Function: main text
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.tabfig.pdf
    File Function: tables and figures
    Download Restriction: no

    File URL: http://swopec.hhs.se/hastef/papers/hastef0229.tabfig.pdf.zip
    File Function: tables and figures
    Download Restriction: no

    References listed on IDEAS

    as
    1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    2. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Konstantinos Giannakas & Kien Tran & Vangelis Tzouvelekas, 2003. "Predicting technical effciency in stochastic production frontier models in the presence of misspecification: a Monte-Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 35(2), pages 153-161.
    2. Rafaela Dios-Palomares & Jose Miguel Martínez Paz, 2004. "A spreading method to improve efficiency prediction," Economic Working Papers at Centro de Estudios Andaluces E2004/31, Centro de Estudios Andaluces.

    More about this item

    Keywords

    Bias; MSE; Point and Interval Estimators; Stochastic Production Frontier;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hhs:hastef:0229. 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: (Helena Lundin). General contact details of provider: http://edirc.repec.org/data/erhhsse.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.