IDEAS home Printed from https://ideas.repec.org/p/ags/uconnr/149177.html

Estimation and Inference in Parametric Stochastic Frontier Models: A SAS/IML Procedure for a Bootstrap Method

Author

Listed:
  • Tchumtchoua, Sylvie

Abstract

Parametric Stochastic Frontier Models are widely used in productivity analysis and are commonly estimated using FRONTIER, STATA or LIMDEP packages, which only provide point estimates for firm-specific technical efficiency. Confidence intervals for technical efficiencies with superior coverage properties than those offered by the Horrace and Schmidt (1996) method may be computed using the Bootstrap method introduced by Simar and Wilson (2005). To facilitate these calculations, we propose a SAS/IML procedure, which computes these confidence intervals for stochastic frontier models with or without inefficiency effects. We apply the program to estimating supermarket-specific technical efficiency in the U.S. Results indicates that the program works very well and produce narrower confidence intervals than those obtain using Horrace and Schmidt (1996) method.

Suggested Citation

  • 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.
    • Handle: RePEc:ags:uconnr:149177
    DOI: 10.22004/ag.econ.149177
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/149177/files/rr95.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.149177?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    2. 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.
    3. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    2. Mark Andor & Frederik Hesse, "undated". "The StoNED age: The Departure Into a New Era of Efficiency Analysis? An MC study Comparing StoNED and the "Oldies" (SFA and DEA)," Working Papers 201285, Institute of Spatial and Housing Economics, Munster Universitary.
    3. 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.
    4. Mäkinen, Mikko, 2007. "Do Stock Opiton Schemes Affect Technical Inefficiency? Evidence from Finland," Discussion Papers 1085, The Research Institute of the Finnish Economy.
    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. 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.
    7. Mehdi Farsi & Aurelio Fetz & Massimo Filippini, 2007. "Benchmarking and Regulation in the Electricity Distribution Sector," CEPE Working paper series 07-54, CEPE Center for Energy Policy and Economics, ETH Zurich.
    8. Helvoigt, Ted L. & Adams, Darius M., 2009. "A stochastic frontier analysis of technical progress, efficiency change and productivity growth in the Pacific Northwest sawmill industry," Forest Policy and Economics, Elsevier, vol. 11(4), pages 280-287, July.
    9. Castiglione, Concetta & Infante, Davide & Zieba, Marta, 2023. "Public support for performing arts. Efficiency and productivity gains in eleven European countries," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    10. Adetutu, Morakinyo & Glass, Anthony & Weyman-Jones, Thomas, 2015. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," MPRA Paper 65409, University Library of Munich, Germany.
    11. Federico Belotti & Silvio Daidone & Giuseppe Ilardi & Vincenzo Atella, 2013. "Stochastic frontier analysis using Stata," Stata Journal, StataCorp LLC, vol. 13(4), pages 718-758, December.
    12. Olli-Pekka Kuusela & Maria S. Bowman & Gregory S. Amacher & Richard B. Howarth & Nadine T. Laporte, 2020. "Does infrastructure and resource access matter for technical efficiency? An empirical analysis of fishing and fuelwood collection in Mozambique," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(3), pages 1811-1837, March.
    13. Getu Hailu & B. James Deaton, 2016. "Agglomeration Effects in Ontario’s Dairy Farming," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(4), pages 1055-1073.
    14. Cristian Barra & Nazzareno Ruggiero, 2022. "How do dimensions of institutional quality improve Italian regional innovation system efficiency? The Knowledge production function using SFA," Journal of Evolutionary Economics, Springer, vol. 32(2), pages 591-642, April.
    15. Raimundo Soto & Rosalía Vásquez, 2011. "The Efficiency Cost of the Kafala in Dubai: A Stochastic Frontier Analysis," Documentos de Trabajo 399, Instituto de Economia. Pontificia Universidad Católica de Chile..
    16. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
    17. Fabio Pieri & Enrico Zaninotto, 2010. "The Impact of Vertical Integration and Outsourcing on Firm Efficiency: Evidence from the Italian Machine Tool Industry," DISA Working Papers 1001, Department of Computer and Management Sciences, University of Trento, Italy, revised 11 Mar 2010.
    18. J. Griffin, 2011. "Bayesian clustering of distributions in stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(3), pages 275-283, December.
    19. Lang, Gunter & Welzel, Peter, 1999. "Mergers among German Cooperative Banks: A Panel-Based Stochastic Frontier Analysis," Small Business Economics, Springer, vol. 13(4), pages 273-286, December.
    20. Paul, Satya & Shankar, Sriram, 2018. "Modelling Efficiency Effects in a True Fixed Effects Stochastic Frontier," MPRA Paper 87437, University Library of Munich, Germany.

    More about this item

    Keywords

    ;
    ;

    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:ags:uconnr:149177. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/fmuctus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.