IDEAS home Printed from
   My bibliography  Save this article

Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers


  • K. Hadri
  • C. Guermat
  • J. Whittaker


In previous studies, measures of technical inefficiency effects derived from stochastic production frontiers have been estimated from residuals which are sensitive to specification errors. This study corrects for this inaccuracy by extending the doubly heteroscedastic stochastic cost frontier suggested by Hadri (1999) to the model for technical inefficiency effects. This model is a stochastic frontier production function for panel data as proposed by Battese and Coelli (1995). The study uses, for illustration of the techniques, data on 101 mainly cereal farms in England. We find that the correction for heteroscedasticity is supported by the data. Both point estimates and confidence intervals for technical efficiencies are provided. The confidence intervals are constructed by extending the “Battese-Coelli” method reported by Horrace and Schmidt (1996) by allowing the technical inefficiency to be time varying and the disturbance terms to be heteroscedastic. The confidence intervals reveal the precision of technical efficiency estimates and show the deficiencies of making inferences based exclusively on point estimates. Copyright Springer-Verlag Berlin Heidelberg 2003

Suggested Citation

  • K. Hadri & C. Guermat & J. Whittaker, 2003. "Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers," Empirical Economics, Springer, vol. 28(1), pages 203-222, January.
  • Handle: RePEc:spr:empeco:v:28:y:2003:i:1:p:203-222 DOI: 10.1007/s001810100127

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Lariviere, Eric & Larue, Bruno & Chalfant, Jim, 2000. "Modeling the demand for alcoholic beverages and advertising specifications," Agricultural Economics, Blackwell, vol. 22(2), pages 147-162, March.
    2. Alley, Andrew G & Ferguson, Donald G & Stewart, Kenneth G, 1992. "An Almost Ideal Demand System for Alcoholic Beverages in British Columbia," Empirical Economics, Springer, vol. 17(3), pages 401-418.
    3. Blundell, Richard, 1988. "Consumer Behaviour: Theory and Empirical Evidence--a Survey," Economic Journal, Royal Economic Society, vol. 98(389), pages 16-65, March.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
    5. R. Carew & W. J. Florkowski & S. He, 2004. "Demand for Domestic and Imported Table Wine in British Columbia: A Source-differentiated Almost Ideal Demand System Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 52(2), pages 183-199, July.
    6. S. Selvanathan & E.A. Selvanathan, 2005. "Empirical Regularities in Cross-Country Alcohol Consumption," The Economic Record, The Economic Society of Australia, vol. 81(s1), pages 128-142, August.
    7. Lariviere, Eric & Larue, Bruno & Chalfant, Jim, 2000. "Modeling the demand for alcoholic beverages and advertising specifications," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 22(2), March.
    8. Donald Freeman, 2001. "Beer and the business cycle," Applied Economics Letters, Taylor & Francis Journals, vol. 8(1), pages 51-54.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Boris Bravo-Ureta & Daniel Solís & Víctor Moreira López & José Maripani & Abdourahmane Thiam & Teodoro Rivas, 2007. "Technical efficiency in farming: a meta-regression analysis," Journal of Productivity Analysis, Springer, vol. 27(1), pages 57-72, February.
    2. Mark Andor & Frederik Hesse, 2014. "The StoNED age: the departure into a new era of efficiency analysis? A monte carlo comparison of StoNED and the “oldies” (SFA and DEA)," Journal of Productivity Analysis, Springer, vol. 41(1), pages 85-109, February.
    3. Tiziana Laureti, 2008. "Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 76-89, February.
    4. Maria L. Loureiro, 2009. "Farmers' health and agricultural productivity," Agricultural Economics, International Association of Agricultural Economists, vol. 40(4), pages 381-388, July.
    5. Stefan Meyer, 2015. "Payment schemes and cost efficiency: evidence from Swiss public hospitals," International Journal of Health Economics and Management, Springer, vol. 15(1), pages 73-97, March.
    6. Arazmuradov, Annageldy & Martini, Gianmaria & Scotti, Davide, 2014. "Determinants of total factor productivity in former Soviet Union economies: A stochastic frontier approach," Economic Systems, Elsevier, vol. 38(1), pages 115-135.
    7. Andrew J Tiffin, 2006. "Ukraine; The Cost of Weak Institutions," IMF Working Papers 06/167, International Monetary Fund.
    8. Stern, David I. & Jotzo, Frank, 2010. "How ambitious are China and India's emissions intensity targets?," Energy Policy, Elsevier, vol. 38(11), pages 6776-6783, November.
    9. Marta Zieba, 2011. "An Analysis of Technical Efficiency and Efficiency Factors for Austrian and Swiss Non-Profit Theatres," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(II), pages 233-274, June.
    10. repec:kap:iaecre:v:14:y:2008:i:1:p:76-89 is not listed on IDEAS
    11. Ogundari, K. & Brümmer, Bernhard, 2011. "Estimating Technical Efficiency, Input substitution and complementary effects using Output Distance Function: A study of Cassava production in Nigeria," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 12(2), June.
    12. Lowry, Mark Newton & Getachew, Lullit, 2009. "Statistical benchmarking in utility regulation: Role, standards and methods," Energy Policy, Elsevier, vol. 37(4), pages 1323-1330, April.
    13. Tchumtchoua, Sylvie, 2006. "Estimation and Inference in Parametric Stochastic Frontier Models: A SAS/IML Procedure for a Bootstrap Method," Research Reports 149177, University of Connecticut, Food Marketing Policy Center.
    14. Saastamoinen, Antti & Kuosmanen, Timo, 2016. "Quality frontier of electricity distribution: Supply security, best practices, and underground cabling in Finland," Energy Economics, Elsevier, vol. 53(C), pages 281-292.

    More about this item


    Key words: Stochastic frontier production; Heteroscedasticity; Technical efficiency; Elasticity; Panel data.; JEL classification: C23; C24; D24; Q12.;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity


    Access and download statistics


    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:spr:empeco:v:28:y:2003:i:1:p:203-222. 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: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.