Risk programming and sparse data: how to get more reliable results

J. Brian Hardaker, Gudbrand D. Lien, Marcel A.P.M. Van Asseldonk, James Richardson () and Agnar Hegrenes

No 44051, 2008 International Congress, August 26-29, 2008, Ghent, Belgium from European Association of Agricultural Economists

Abstract: Because relevant historical data for farms are inevitably sparse, most risk programming studies rely on few observations. We discuss how to use available information to derive an appropriate multivariate distribution function that can be sampled for a more complete representation of the possible risks in riskbased models. For the particular example of a Norwegian mixed livestock and crop farm, the solution is shown to be unstable with few states, although the cost of picking a sub-optimal plan declines with increases in number of states by Latin Hypercube sampling.

Keywords: Risk; and; Uncertainty (search for similar items in EconPapers)
Pages: 5
Date: 2008
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Journal Article: Risk programming and sparse data: how to get more reliable results (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:eaae08:44051

DOI: 10.22004/ag.econ.44051

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