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A Small‐Sample Comparison of Estimators in the EU‐MGF Approach to Decision Making
Author(s) -
Gbur Edward E.,
Collins Robert A.
Publication year - 1989
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.2307/1241789
Subject(s) - estimator , moment (physics) , nonparametric statistics , econometrics , parametric statistics , sample (material) , mathematics , function (biology) , sample size determination , statistics , exponential function , parametric model , variety (cybernetics) , mathematical analysis , physics , classical mechanics , evolutionary biology , biology , thermodynamics
Estimation of the moment‐generating function lies at the core of the exponential utility—moment‐generating function approach to decision making. The small sample performances of the nonparametric empirical moment‐generating function and a parametric competitor have been examined under a variety of situations defined by the sample size, the level of risk aversion, and the degree to which the assumed parametric model approximates reality. Conditions under which each estimator would be preferred are obtained. Neither approach can be recommended unequivocally in all situations.