IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v41y2014i2p321-337.html
   My bibliography  Save this article

Technical efficiency in competing panel data models: a study of Norwegian grain farming

Author

Listed:
  • Subal Kumbhakar

    ()

  • Gudbrand Lien
  • J. Hardaker

Abstract

Estimation of technical efficiency is widely used in empirical research using both cross-sectional and panel data. Although several stochastic frontier models for panel data are available, only a few of them are normally applied in empirical research. In this article we chose a broad selection of such models based on different assumptions and specifications of heterogeneity, heteroskedasticity and technical inefficiency. We applied these models to a single dataset from Norwegian grain farmers for the period 2004–2008. We also introduced a new model that disentangles firm effects from persistent (time-invariant) and residual (time-varying) technical inefficiency. We found that efficiency results are quite sensitive to how inefficiency is modeled and interpreted. Consequently, we recommend that future empirical research should pay more attention to modeling and interpreting inefficiency as well as to the assumptions underlying each model when using panel data. Copyright Springer Science+Business Media, LLC 2014

Suggested Citation

  • 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.
  • Handle: RePEc:kap:jproda:v:41:y:2014:i:2:p:321-337
    DOI: 10.1007/s11123-012-0303-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11123-012-0303-1
    Download Restriction: Access to full text is restricted to subscribers.

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kumbhakar, Subal C., 1991. "Estimation of technical inefficiency in panel data models with firm- and time-specific effects," Economics Letters, Elsevier, vol. 36(1), pages 43-48, May.
    2. Jean-Paul Chavas & Ragan Petrie & Michael Roth, 2005. "Farm Household Production Efficiency: Evidence from The Gambia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(1), pages 160-179.
    3. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
    4. Caudill, Steven B. & Ford, Jon M., 1993. "Biases in frontier estimation due to heteroscedasticity," Economics Letters, Elsevier, vol. 41(1), pages 17-20.
    5. Wilson, Paul & Hadley, David & Asby, Carol, 2001. "The influence of management characteristics on the technical efficiency of wheat farmers in eastern England," Agricultural Economics, Blackwell, vol. 24(3), pages 329-338, March.
    6. Subal C. Kumbhakar & Almas Heshmati, 1995. "Efficiency Measurement in Swedish Dairy Farms: An Application of Rotating Panel Data, 1976–88," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 660-674.
    7. Konstantinos Giannakas & Richard Schoney & Vangelis Tzouvelekas, 2001. "Technical Efficiency, Technological Change and Output Growth of Wheat Farms in Saskatchewan," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 49(2), pages 135-152, July.
    8. Hadri, Kaddour, 1999. "Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 359-363, July.
    9. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    10. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2011. "A Stochastic Frontier Model with short-run and long-run inefficiency random effects," Working Papers 1101, Department of Economics and Technology Management, University of Bergamo.
    11. Guohua Feng & Apostolos Serletis, 2009. "Efficiency and productivity of the US banking industry, 1998-2005: evidence from the Fourier cost function satisfying global regularity conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 105-138.
    12. 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.
    13. Kaddour Hadri & Cherif Guermat & Julie Whittaker, 2003. "Estimating Farm Efficiency in the Presence of Double Heteroscedasticity Using Panel Data," Journal of Applied Economics, Universidad del CEMA, vol. 6, pages 255-268, November.
    14. Wang, Hung-Jen & Ho, Chia-Wen, 2010. "Estimating fixed-effect panel stochastic frontier models by model transformation," Journal of Econometrics, Elsevier, vol. 157(2), pages 286-296, August.
    15. Kumbhakar, Subal C. & Wang, Hung-Jen, 2005. "Estimation of growth convergence using a stochastic production frontier approach," Economics Letters, Elsevier, vol. 88(3), pages 300-305, September.
    16. Kumbhakar, Subal C & Hjalmarsson, Lennart, 1995. "Labour-Use Efficiency in Swedish Social Insurance Offices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 33-47, Jan.-Marc.
    17. Giannis Karagiannis & Alexander Sarris, 2005. "Measuring and explaining scale efficiency with the parametric approach: the case of Greek tobacco growers," Agricultural Economics, International Association of Agricultural Economists, vol. 33(s3), pages 441-451, November.
    18. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    19. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    20. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    21. Kumbhakar, Subal C., 1987. "The specification of technical and allocative inefficiency in stochastic production and profit frontiers," Journal of Econometrics, Elsevier, vol. 34(3), pages 335-348, March.
    22. Caudill, Steven B & Ford, Jon M & Gropper, Daniel M, 1995. "Frontier Estimation and Firm-Specific Inefficiency Measures in the Presence of Heteroscedasticity," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 105-111, January.
    23. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    24. Barry K. Goodwin & Ashok K. Mishra, 2004. "Farming Efficiency and the Determinants of Multiple Job Holding by Farm Operators," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(3), pages 722-729.
    25. Wang, Hung-Jen, 2006. "Stochastic frontier models," MPRA Paper 31079, University Library of Munich, Germany.
    26. repec:ags:jaecon:43994 is not listed on IDEAS
    27. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    28. 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.
    29. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Stochastic frontier models; Panel data; Heteroskedasticity; Heterogeneity; Persistent and residual technical inefficiency; C23; D24; O30; Q12;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

    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:kap:jproda:v:41:y:2014:i:2:p:321-337. 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: http://www.springer.com .

    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.