Toward an Appropriate Measure of Uncertainty in a Risk Programming Model
作者:
William T. McSweeny,
David E. Kenyon,
Randall A. Kramer,
期刊:
American Journal of Agricultural Economics
(WILEY Available online 1987)
卷期:
Volume 69,
issue 1
页码: 87-96
ISSN:0002-9092
年代: 1987
DOI:10.2307/1241309
出版商: Oxford University Press
数据来源: WILEY
摘要:
AbstractThe measure of uncertainty in a risk‐programming problem has long posed a dilemma. The use of the variance of realized returns assumes that the distribution of realized returns is the same as the distribution anticipated by the decision maker prior to the start of production. Rejection of this maintained hypothesis requires either direct elicitation of these distributions or construction of another measure from realized data. A mean‐squared forecast error is considered an appropriate measure. Optimal solutions to a quadratic risk‐programming problem are obtained using this measure and compared to those obtained using traditional measures.
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