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Abstract

The Pratt-Arrow measure of absolute risk aversion, as defined by r(x)=-un(x)/u1(x), is well known to be invariant to linear transformations. However, this invariance property applies with respect to transformations of u and not with respect to arbitrary rescalings of the outcome variables, x. The effects of this misunderstanding has led to ambiguity in classifying attitudes by risk aversion coefficients. It is shown that inappropriate rescalings of the outcome variable can lead to inaccurate rankings produced by generalized stochastic dominance.

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