Two recent papers, Harless and Camerer(1994) and Hey and Orme(1994) were both addressed to the same question: which is the 'best' theory of decision making under risk? The two papers shared a common concern: the appropriate trade-off between the descriptive accuracy of a theory and the predictive parsimony of that theory. In other respects, however, the two papers differed markedly: first in their treatment of the stochastic specification underlying the data generating process; second, and more importantly, in their interpretation of the question posed. This current paper tackles these two issues; first, trying to resolve the issue of the correct stochastic specification; second, by clarifying what economists might mean by a `best' theory. The paper provides a general framework for answering such questions, and illustrates the application of this framework through two experiments aimed at answering the question: `which is the best theory of decision making under risk?'.
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Paper provided by Department of Economics, University of York in its series Discussion Papers with number
99/18.
Length: Date of creation: Date of revision: Handle: RePEc:yor:yorken:99/18
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