IDEAS home Printed from https://ideas.repec.org/p/rsm/riskun/r10_3.html
   My bibliography  Save this paper

Production Under Uncertainty: A Simulation Study

Author

Listed:
  • Sriram Shankar

    (School of Economics, University of Queensland)

  • Chris O'Donnell

    (School of Economics, University of Queensland)

  • John Quiggin

    (School of Economics, University of Queensland)

Abstract

In this article we model production technology in a state-contingent framework. Our model analyzes production under uncertainty without being explicit about the nature of producer risk preferences. In our model producers’ risk preferences are captured by the risk-neutral probabilities they assign to the different states of nature. Using a state-general state-contingent specification of technology we show that rational producers who encounter the same stochastic technology can make significantly different production choices. Further, we develop an econometric methodology to estimate the risk-neutral probabilities and the parameters of stochastic technology when there are two states of nature and only one of which is observed. Finally, we simulate data based on our state-general state-contingent specification of technology. Biased estimates of the technology parameters are obtained when we apply conventional ordinary least squares (OLS) estimator on the simulated data.

Suggested Citation

  • Sriram Shankar & Chris O'Donnell & John Quiggin, 2010. "Production Under Uncertainty: A Simulation Study," Risk & Uncertainty Working Papers WPR10_3, Risk and Sustainable Management Group, University of Queensland.
  • Handle: RePEc:rsm:riskun:r10_3
    as

    Download full text from publisher

    File URL: http://www.uq.edu.au/rsmg/WP/WPR10_03.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Powell, Alan A. & Gruen, Fred H.G., 1967. "The Estimation Of Production Frontiers: The Australian Livestock/Cereals Complex," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 11(1), pages 1-19, June.
    2. O'Donnell, Christopher J. & Shankar, Sriram, 2009. "Estimating State-Allocable Production Technologies When There are Two States of Nature and State Allocations of Inputs are Unobserved," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 50898, Australian Agricultural and Resource Economics Society.
    3. Rasmussen, Svend, 2003. "Criteria for optimal production under uncertainty. The state-contingent approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 47(4), pages 1-30.
    4. C. J. O'Donnell & W. E. Griffiths, 2006. "Estimating State-Contingent Production Frontiers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 249-266.
    5. Jean-Paul Chavas, 2008. "On the economics of agricultural production ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(4), pages 365-380, December.
    6. Jean-Paul Chavas, 2008. "A Cost Approach to Economic Analysis Under State-Contingent Production Uncertainty," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 435-466.
    7. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521785235, January.
    8. Christopher O’Donnell & Robert Chambers & John Quiggin, 2010. "Efficiency analysis in the presence of uncertainty," Journal of Productivity Analysis, Springer, vol. 33(1), pages 1-17, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shankar, Sriram, 2015. "Efficiency analysis under uncertainty: a simulation study," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(2), April.
    2. Robert Chambers & Teresa Serra & Spiro Stefanou, 2015. "Using ex ante output elicitation to model state-contingent technologies," Journal of Productivity Analysis, Springer, vol. 43(1), pages 75-83, February.
    3. Taylan G. Topcu & Konstantinos Triantis, 2022. "An ex-ante DEA method for representing contextual uncertainties and stakeholder risk preferences," Annals of Operations Research, Springer, vol. 309(1), pages 395-423, February.
    4. Kota Minegishi, 2016. "Comparison of production risks in the state-contingent framework: application to balanced panel data," Journal of Productivity Analysis, Springer, vol. 46(2), pages 121-138, December.
    5. Raushan Bokusheva & Lajos Baráth, 2024. "State‐contingent production technology formulation: Identifying states of nature using reduced‐form econometric models of crop yield," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 805-827, March.

    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. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    2. Serra, Teresa & Chambers, Robert G. & Oude Lansink, Alfons, 2014. "Measuring technical and environmental efficiency in a state-contingent technology," European Journal of Operational Research, Elsevier, vol. 236(2), pages 706-717.
    3. Céline Nauges & Christopher J. O'Donnell & John Quiggin, 2011. "Uncertainty and technical efficiency in Finnish agriculture: a state-contingent approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(4), pages 449-467, October.
    4. Pedro Macedo & Elvira Silva & Manuel Scotto, 2014. "Technical efficiency with state-contingent production frontiers using maximum entropy estimators," Journal of Productivity Analysis, Springer, vol. 41(1), pages 131-140, February.
    5. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    6. Adamson, David & Mallawaarachchi, Thilak & Quiggin, John C., 2007. "Water use and salinity in the Murray–Darling Basin: A state-contingent model," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 51(3), pages 1-19.
    7. Shankar, Sriram, 2012. "Production economics in the presence of risk," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(4), pages 1-24, December.
    8. Huettel, Silke & Narayana, Rashmi & Odening, Martin, 2011. "Measuring dynamic efficiency under uncertainty," Structural Change in Agriculture/Strukturwandel im Agrarsektor (SiAg) Working Papers 129062, Humboldt University Berlin, Department of Agricultural Economics.
    9. John Quiggin & Robert G. Chambers, 2006. "The state-contingent approach to production under uncertainty ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 50(2), pages 153-169, June.
    10. Theodoros Skevas & Teresa Serra, 2016. "The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 139-153, December.
    11. Hardaker, J. Brian & Lien, Gudbrand, 2010. "Probabilities for decision analysis in agriculture and rural resource economics: The need for a paradigm change," Agricultural Systems, Elsevier, vol. 103(6), pages 345-350, July.
    12. Adamson, David, 2010. "Climate change, Irrigation and Pests: Examining Heliothis in the Murray Darling Basin," Risk and Sustainable Management Group Working Papers 149879, University of Queensland, School of Economics.
    13. Just, Richard E. & Just, David R., 2011. "Global identification of risk preferences with revealed preference data," Journal of Econometrics, Elsevier, vol. 162(1), pages 6-17, May.
    14. Bouali Guesmi & Ahmed Yangui & Ibtissem Taghouti & José Maria Gil, 2022. "Trade-Off between Land Use Pattern and Technical Efficiency Performance: Evidence from Arable Crop Farming in Tunisia," Land, MDPI, vol. 12(1), pages 1-13, December.
    15. Nauges, Celine & O'Donnell, Christopher J. & Quiggin, John C., 2009. "Uncertainty and technical efficiency in Finnish Agriculture," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 48062, Australian Agricultural and Resource Economics Society.
    16. Robert Chambers & Teresa Serra & Spiro Stefanou, 2015. "Using ex ante output elicitation to model state-contingent technologies," Journal of Productivity Analysis, Springer, vol. 43(1), pages 75-83, February.
    17. Macedo, Pedro & Scotto, Manuel, 2014. "Cross-entropy estimation in technical efficiency analysis," Journal of Mathematical Economics, Elsevier, vol. 54(C), pages 124-130.
    18. Sansi Yang & C Richard Shumway, 2018. "Asset fixity under state-contingent production uncertainty," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(5), pages 831-856.
    19. Adamson, David & Mallawaarachchi, Thilak & Quiggin, John, 2004. "Modelling basin level allocation of water in the Murray Darling Basin in a world of uncertainty," Risk and Sustainable Management Group Working Papers 149844, University of Queensland, School of Economics.
    20. Eldon V. Ball & Ricardo Cavazos & Jeffrey T. LaFrance & Rulon Pope & Jesse Tack, 2010. "Aggregation and Arbitrage in Joint Production," Monash Economics Working Papers archive-22, Monash University, Department of Economics.

    More about this item

    Keywords

    CES; Cobb-Douglas; OLS; output-cubical; risk-neutral; state-allocable; state-contingent;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

    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:rsm:riskun:r10_3. 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: David Adamson (email available below). General contact details of provider: https://edirc.repec.org/data/rsmuqau.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.