IDEAS home Printed from https://ideas.repec.org/a/bes/jnlbes/v12y1994i3p339-46.html
   My bibliography  Save this article

Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function

Author

Listed:
  • Koop, Gary
  • Osiewalski, Jacek
  • Steel, Mark F J

Abstract

In this article, the authors describe the use of Gibbs sampling methods for drawing posterior inferences in a cost frontier model with an asymptotically ideal price aggregator, nonconstant returns to scale, and composed error. An empirical example illustrates the sensitivity of efficiency measures to assumptions made about the functional form of the frontier. The authors also examine the consequences of imposing regularity through parametric restrictions alone.

Suggested Citation

  • Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-346, July.
  • Handle: RePEc:bes:jnlbes:v:12:y:1994:i:3:p:339-46
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    2. William A. Barnett & Michael Wolfe, 2004. "Semi-nonparametric Bayesian Estimation of the Asymptotically Ideal Production Model1," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 303-349, Emerald Group Publishing Limited.
    3. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    4. Caves, Douglas W & Christensen, Laurits R, 1980. "Global Properties of Flexible Functional Forms," American Economic Review, American Economic Association, vol. 70(3), pages 422-432, June.
    5. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    6. W. E. Diewert & T. J. Wales, 1993. "Linear and Quadratic Spline Models for Consumer Demand Functions," Canadian Journal of Economics, Canadian Economics Association, vol. 26(1), pages 77-106, February.
    7. Gallant, A. Ronald & Golub, Gene H., 1984. "Imposing curvature restrictions on flexible functional forms," Journal of Econometrics, Elsevier, vol. 26(3), pages 295-321, December.
    8. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    9. 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.
    10. 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)

    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. Dashti, Imad, 2003. "Inference from concave stochastic frontiers and the covariance of firm efficiency measures across firms," Energy Economics, Elsevier, vol. 25(6), pages 585-601, November.
    2. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    3. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.
    4. Efthymios G. Tsionas, 2006. "Inference in dynamic stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 669-676, July.
    5. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    6. William C. Horrace & Yulong Wang, 2022. "Nonparametric tests of tail behavior in stochastic frontier models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 537-562, April.
    7. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
    8. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2014. "Estimation and efficiency measurement in stochastic production frontiers with ordinal outcomes," Journal of Productivity Analysis, Springer, vol. 42(1), pages 67-84, August.
    9. Altunbas, Y. & Gardener, E. P. M. & Molyneux, P. & Moore, B., 2001. "Efficiency in European banking," European Economic Review, Elsevier, vol. 45(10), pages 1931-1955, December.
    10. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    11. Tsionas, Efthymios G., 2003. "Combining DEA and stochastic frontier models: An empirical Bayes approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 499-510, June.
    12. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    13. Adnan Kasman, 2002. "Cost Efficiency, Scale Economies, and Technological Progress in Turkish Banking," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 2(1), pages 1-20.
    14. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.
    15. Maira Caño- Guiral, 1995. "Competitividad y eficiencia técnica. Un modelo de datos panel para la industria láctea uruguaya," Documentos de Trabajo (working papers) 0795, Department of Economics - dECON.
    16. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    17. Charnes, Abraham & Gallegos, Armando & Li, Hongyu, 1996. "Robustly efficient parametric frontiers via Multiplicative DEA for domestic and international operations of the Latin American airline industry," European Journal of Operational Research, Elsevier, vol. 88(3), pages 525-536, February.
    18. Najma Sharif & Atul Dar, 1996. "An empirical study of the patterns and sources of technical inefficiency in traditional and HYV rice cultivation in Bangladesh," Journal of Development Studies, Taylor & Francis Journals, vol. 32(4), pages 612-629.
    19. Jin Yang & Hui Wang & Songqing Jin & Kevin Chen & Jeffrey Riedinger & Chao Peng, 2016. "Migration, local off-farm employment, and agricultural production efficiency: evidence from China," Journal of Productivity Analysis, Springer, vol. 45(3), pages 247-259, June.
    20. 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.

    More about this item

    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:bes:jnlbes:v:12:y:1994:i:3:p:339-46. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main .

    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.