Which error story is best?

Two recent papers, Harless and Camerer (1994) and Hey and Orme (1994) are both addressed to the same question: which is the 'best' theory of decision making under risk? As an essential part of their separate approaches to an answer to this question, both sets of authors had to make an assumption about the underlying stochastic nature of their data. In this context this implied an assumption about the 'errors' made by the subjects in the experiments generating the data under analysis. The two different sets of authors adopted different assumptions: the purpose of this current paper is to compare and contrast these two different error stories-in an attempt to discover which of the two is 'best'.