IDEAS home Printed from https://ideas.repec.org/p/qld/uqcepa/07.html
   My bibliography  Save this paper

Estimating State-Contingent Production Frontiers

Author

Abstract

Chambers and Quiggin (2000) advocate the use of state-contingent production technologies to represent risky production and establish important theoretical results concerning producer behaviour under uncertainty. Unfortunately, perceived problems in the estimation of state-contingent models have limited the usefulness of the approach in policy formulation. We show that fixed and random effects state-contingent production frontiers can be conveniently estimated in a finite mixtures framework. An empirical example is provided. Compared to standard estimation approaches, we find that estimating production frontiers in a state-contingent framework produces significantly different estimates of elasticities, firm technical efficiencies and other quantities of economic interest.

Suggested Citation

  • Chris O'Donnell & W.E. Griffiths, 2004. "Estimating State-Contingent Production Frontiers," CEPA Working Papers Series WP022004, School of Economics, University of Queensland, Australia.
    • Handle: RePEc:qld:uqcepa:07
    as

    Download full text from publisher

    File URL: https://economics.uq.edu.au/files/5346/WP022004.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chambers, R.G. & Quiggin, J., 1995. "Separation and Hedging Results with State-Contingent Production," Papers 293, Australian National University - Department of Economics.
    2. Robert G. Chambers & John Quiggin, 2002. "The State-Contingent Properties of Stochastic Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 513-526.
    3. Chambers, Robert G. & Quiggin, John C., 2004. "Technological and financial approaches to risk management in agriculture: an integrate approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 1-25.
    4. 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.
    5. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521785235, January.
    6. Koop, Gary & Steel, Mark F.J. & Osiewalski, Jacek, 1992. "Posterior analysis of stochastic frontier models using Gibbs sampling," DES - Working Papers. Statistics and Econometrics. WS 3677, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. 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.
    8. Newbery, David M, 1989. "The Theory of Food Price Stabilisation," Economic Journal, Royal Economic Society, vol. 99(398), pages 1065-1082, December.
    9. Robert G. James & John Quiggan, 1997. "Separation and Hedging Results with State‐Contingent Production," Economica, London School of Economics and Political Science, vol. 64(254), pages 187-209, May.
    10. 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.
    11. Rasmussen, Svend, 2004. "Optimizing Production under Uncertainty: Generalisation of the State-Contingent Approach and Comparison of Methods for Empirical Application," Unit of Economics Working Papers 24184, Royal Veterinary and Agricultural University, Food and Resource Economic Institute.
    12. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
    13. 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.
    14. 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.
    15. Yangseon Kim & Peter Schmidt, 2000. "A Review and Empirical Comparison of Bayesian and Classical Approaches to Inference on Efficiency Levels in Stochastic Frontier Models with Panel Data," Journal of Productivity Analysis, Springer, vol. 14(2), pages 91-118, September.
    16. Chambers, Robert G. & Quiggin, John, 1996. "Non-point-source pollution regulation as a multi-task principal-agent problem," Journal of Public Economics, Elsevier, vol. 59(1), pages 95-116, January.
    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. Supawat Rungsuriyawiboon & Chris O'Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia.
    2. 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.
    3. 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.
    4. Farsi, Mehdi & Filippini, Massimo, 2009. "An analysis of cost efficiency in Swiss multi-utilities," Energy Economics, Elsevier, vol. 31(2), pages 306-315, March.
    5. William Horrace & Seth Richards-Shubik & Ian Wright, 2015. "Expected efficiency ranks from parametric stochastic frontier models," Empirical Economics, Springer, vol. 48(2), pages 829-848, March.
    6. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    7. Idaira Cabrera‐Suárez & Jorge V. Pérez‐Rodríguez, 2021. "Bank branch performance and cost efficiency: A stochastic frontier panel data approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5850-5863, October.
    8. Martini, Gianmaria & Scotti, Davide & Viola, Domenico & Vittadini, Giorgio, 2020. "Persistent and temporary inefficiency in airport cost function: An application to Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 999-1019.
    9. Belotti, Federico & Ilardi, Giuseppe, 2018. "Consistent inference in fixed-effects stochastic frontier models," Journal of Econometrics, Elsevier, vol. 202(2), pages 161-177.
    10. Varabyova, Yauheniya & Schreyögg, Jonas, 2013. "International comparisons of the technical efficiency of the hospital sector: Panel data analysis of OECD countries using parametric and non-parametric approaches," Health Policy, Elsevier, vol. 112(1), pages 70-79.
    11. Roberto Colombi & Gianmaria Martini & Giorgio Vittadini, 2017. "Determinants of transient and persistent hospital efficiency: The case of Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 5-22, September.
    12. Quang Nguyen & Sean Pascoe & Louisa Coglan & Son Nghiem, 2021. "The sensitivity of efficiency scores to input and other choices in stochastic frontier analysis: an empirical investigation," Journal of Productivity Analysis, Springer, vol. 55(1), pages 31-40, February.
    13. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    14. Jyotsna Rosario & K.R. Shanmugam, 2024. "Elementary Education Outcome Efficiency of Indian States: A Ray Frontier Approach," Working Papers 2024-264, Madras School of Economics,Chennai,India.
    15. Vanesa D’Elia & Gustavo Ferro, 2019. "Empirical Efficiency Measurement in Higher Education: An Overview," CEMA Working Papers: Serie Documentos de Trabajo. 708, Universidad del CEMA.
    16. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    17. 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.
    18. Liang Zhang & Wei Bao & Liang Sun, 2016. "Resources and Research Production in Higher Education: A Longitudinal Analysis of Chinese Universities, 2000–2010," Research in Higher Education, Springer;Association for Institutional Research, vol. 57(7), pages 869-891, November.
    19. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    20. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:qld:uqcepa:07. 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: SOE IT (email available below). General contact details of provider: https://edirc.repec.org/data/decuqau.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.