Discriminating between Preference Functionals: A Monte Carlo Study

Enrica Carbone ()

Journal of Risk and Uncertainty, 1997, vol. 15, issue 1, 29-54

Abstract: This paper reports on the results of a Monte Carlo investigation into the power of commonly employed procedures for identifying the 'correct' preference functional of individuals, and hence for discriminating between the large number of preference functionals now advocated in the theoretical literature. The paper also asks which of two commonly employed experimental procedures might be the most efficient in this respect. The results show that several of the 'newer' preference functionals are difficult to distinguish empirically--at least on the basis of conventional experimental tests--and that the Complete ranking experimental design might be better than the Pairwise Choice design. The conclusion of the paper is that more thought should therefore be given to the question of the experimental design. Copyright 1997 by Kluwer Academic Publishers

Date: 1997
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