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Land Allocation in the Presence of Estimation Risk

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  • Lence, Sergio H.
  • Hayes, Dermot J.

Abstract

Estimation risk occurs when parameters relevant for decision making are uncertain. Bayes' criterion is consistent with expected-utility maximization in the presence of estimation risk. This article examines optimal (Bayes') land allocations and land allocations obtained using the traditional plug-in approach and two alternative decision rules. Bayes' allocations are much better economically than the other allocations when there are few sample observations relative to activities. Calculation of certainty equivalent returns (CERs) with estimation risk is also discussed and illustrated. CERs are typically (and incorrectly) calculated with the plug-in approach. Plug-in CERs may be extremely misleading.
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Suggested Citation

  • Lence, Sergio H. & Hayes, Dermot J., 1995. "Land Allocation in the Presence of Estimation Risk," Staff General Research Papers Archive 995, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:995
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    Cited by:

    1. Pautsch, Gregory R. & Babcock, Bruce A. & Breidt, F. Jay, 1999. "Optimal Information Acquisition Under A Geostatistical Model," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 24(2), pages 1-25, December.
    2. Wang, Xuecai & Dorfman, Jeffrey H. & McKissick, John & Turner, Steven C., 2001. "Optimal Marketing Decisions for Feeder Cattle under Price and Production Risk," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 33(3), pages 431-443, December.
    3. Babcock, Bruce A. & Pautsch, Gregory R., 1998. "Moving From Uniform To Variable Fertilizer Rates On Iowa Corn: Effects On Rates And Returns," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 23(2), pages 1-16, December.
    4. Lien, Gudbrand & Hardaker, J. Brian & Asseldonk, Marcel A.P.M. van & Richardson, James W., 2009. "Risk programming and sparse data: how to get more reliable results," Agricultural Systems, Elsevier, vol. 101(1-2), pages 42-48, June.
    5. Gregory R. Pautsch & Bruce A. Babcock & F. Jay Breidt, 1998. "Optimal Sampling Under a Geostatistical Model," Center for Agricultural and Rural Development (CARD) Publications 98-wp200, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    6. Gudbrand Lien & J. Hardaker & Marcel Asseldonk & James Richardson, 2011. "Risk programming analysis with imperfect information," Annals of Operations Research, Springer, vol. 190(1), pages 311-323, October.

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