IDEAS home Printed from https://ideas.repec.org/a/kap/jproda/v8y1997i3p269-280.html
   My bibliography  Save this article

A Stochastic Frontier Production Function with Flexible Risk Properties

Author

Listed:
  • G. Battese
  • A. Rambaldi
  • G. Wan

Abstract

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures. An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • G. Battese & A. Rambaldi & G. Wan, 1997. "A Stochastic Frontier Production Function with Flexible Risk Properties," Journal of Productivity Analysis, Springer, vol. 8(3), pages 269-280, August.
  • Handle: RePEc:kap:jproda:v:8:y:1997:i:3:p:269-280
    DOI: 10.1023/A:1007755604744
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1007755604744
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1023/A:1007755604744?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
    ---><---

    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. 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.
    2. John M. Antle, 1983. "Incorporating Risk in Production Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 65(5), pages 1099-1106.
    3. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    4. Asmcrom Kidane & David G. Abler, 1994. "Production technologies in Ethiopian agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 10(2), pages 179-191, April.
    5. Coelli, T. J., 1992. "A computer program for frontier production function estimation : Frontier version 2.0," Economics Letters, Elsevier, vol. 39(1), pages 29-32, May.
    6. 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.
    7. 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.
    8. 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.
    9. Wan, G.H. & Griffiths, William E. & Anderson, Jock R., 1989. "Estimation of Marginal Risks with Seemingly Unrelated Regression and Panel Data," 1989 Conference (33rd), February 7-9, 1989, Christchurch, New Zealand 144886, Australian Agricultural and Resource Economics Society.
    10. Gourieroux, Christian & Holly, Alberto & Monfort, Alain, 1982. "Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters," Econometrica, Econometric Society, vol. 50(1), pages 63-80, January.
    11. Antle, John M., 1983. "Incorporating Risk In Production Analysis," 1983 Annual Meeting, July 31-August 3, West Lafayette, Indiana 279106, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. 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. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    2. Villano, Renato A. & O'Donnell, Christopher J. & Battese, George E., 2005. "An Investigation of Production Risk, Risk Preferences and Technical Efficiency: Evidence From Rainfed Lowland Rice Farms in the Philippines," Working Papers 12953, University of New England, School of Economics.
    3. Villano, Renato A. & Fleming, Euan M., 2004. "Analysis of Technical Efficiency in a Rainfed Lowland Rice Environment in Central Luzon Philippines Using a Stochastic Frontier Production Function with a Heteroskedastic Error Structure," Working Papers 12906, University of New England, School of Economics.
    4. Renato Villano & Euan Fleming, 2006. "Technical Inefficiency and Production Risk in Rice Farming: Evidence from Central Luzon Philippines," Asian Economic Journal, East Asian Economic Association, vol. 20(1), pages 29-46, March.
    5. Althaler, Karl S. & Slavova, Tatjana, 2000. "DEA Problems under Geometrical or Probability Uncertainties of Sample Data," Economics Series 89, Institute for Advanced Studies.
    6. Reddy, Mahendra, 2002. "Implication of Tenancy Status on Productivity and Efficiency: Evidence from Fiji," Sri Lankan Journal of Agricultural Economics, Sri Lanka Agricultural Economics Association (SAEA), vol. 4, pages 1-20.
    7. Coelli, Tim J., 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 1-27, December.
    8. Lothgren, Mickael, 1997. "Generalized stochastic frontier production models," Economics Letters, Elsevier, vol. 57(3), pages 255-259, December.
    9. Muktar Geleto & Mohammed Essa, 2022. "Analysis of Red Pepper Production Risk Adjusted Technical Efficiency: The Case Of Lanfuro District In Siltie Zone, Southern Ethiopia," International Journal of Business and Management, International Institute of Social and Economic Sciences, vol. 10(1), pages 30-58, May.
    10. George E. Battese & Sohail J. Malik & Manzoor A. Gill, 1996. "An Investigation Of Technical Inefficiencies Of Production Of Wheat Farmers In Four Districts Of Pakistan," Journal of Agricultural Economics, Wiley Blackwell, vol. 47(1‐4), pages 37-49, January.
    11. B. E. Bravo‐Ureta & L. Rieger, 1990. "Alternative Production Frontier Methodologies And Dairy Farm Efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(2), pages 215-226, May.
    12. Pantzios, Christos J. & Rozakis, Stelios & Tzouvelekas, Vangelis, 2006. "Evading Farm Support Reduction via Efficient Input Use: The Case of Greek Cotton Growers," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(3), pages 555-574, December.
    13. Muhamad Zahid Muhamad & Mad Nasir Shamsudin & Nitty Hirawaty Kamarulzaman & Nolila Mohd Nawi & Jamaliah Laham, 2022. "Investigating Yield Variability and Technical Efficiency of Smallholders Pineapple Production in Johor," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    14. 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.
    15. Zhihai Yang & Amin W. Mugera & Fan Zhang, 2016. "Investigating Yield Variability and Inefficiency in Rice Production: A Case Study in Central China," Sustainability, MDPI, vol. 8(8), pages 1-11, August.
    16. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    17. Ali D. Cagdas & Scott R. Jeffrey & Elwin G. Smith & Peter C. Boxall, 2016. "Environmental Stewardship and Technical Efficiency in Canadian Prairie Canola Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 455-477, September.
    18. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    19. Tim J. Coelli & George E. Battese, 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 103-128, August.
    20. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.

    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:8:y:1997:i:3:p:269-280. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.