The name is absent

Examining the Functional Specification of Two-Parameter Model
Under Location and Scale Parameter Condition

Takahiro Nakashima

Abstract

The functional specification of mean-standard deviation approach is examined under
location and scale parameter condition. Firstly, the full set of restrictions imposed on the
mean-standard deviation function under the location and scale parameter condition are made
clear. Secondly, the examination based on the restrictions mentioned in the previous
sentence derives the new properties of the mean-standard deviation function on the
applicability of additive separability and the curvature of expansion path which links the
points that give the same slope of indifference curve. It reveals that attention has not been
sufficiently paid to the restrictions in interpreting the linear mean-standard deviation model
and the nonlinear mean-standard deviation model that have been used in previous research.
Thirdly, the interpretation of the nonlinear mean-standard deviation model is reconsidered in
detail and then an alternative nonlinear mean-standard deviation model is proposed. The
implication of the two nonlinear mean-standard deviation models to the empirical approach
“joint analysis of risk preference structure and technology” is discussed.

Keywords: mean-standard deviation approach, location and scale parameter condition,
functional specification, risk aversion, uncertainty

Acknowledgement

This manuscript was written when the author was a visiting researcher at Department of
Applied Economics and Management of Cornell University. This study was financially
supported by National Agriculture and Food Research Organization (NARO). English
language in this paper owes a great deal to Shoko Ishikawa.

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