Departments Forfattere "Rutström, Elisabet E."
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Andersen, Steffen; Harrison, Glenn W.; Lau, Morten Igel; Rutström, Elisabet E. (, 2009)[Flere oplysninger][Færre oplysninger]
Resume: We make the case that psychologists should make wider use of econometric methods for the estimation of structural models. These methods involve the development of maximum likelihood estimates of models, where the likelihood function is tailored to the structural model. In recent years these models have been developed for a wide range of behavioral models of choice under uncertainty. We explain the components of this methodology, and illustrate with applications to major models from psychology. The goal is to build, and traverse, a constructive bridge between the modeling insights of psychology and the statistical tools of economists. URI: http://hdl.handle.net/10398/7800 Filer i denne post: 1
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Andersen, Steffen; Harrison, Glenn W.; Lau, Morten Igel; Rutström, Elisabet E. (, 2009)[Flere oplysninger][Færre oplysninger]
Resume: The most popular models of decision making use a single criteria to evaluate projects or lotteries. However, decision makers may actually consider multiple criteria when evaluating projects. We consider a dual criteria model from psychology. This model integrates the familiar tradeoffs between risk and utility that economists traditionally assume, allowance for rankdependent decision weights, and consideration of income thresholds. We examine the issues involved in full maximum likelihood estimation of the model using observed choice data. We propose a general method for integrating the multiple criteria, using the logic of mixture models, which we believe is attractive from a decisiontheoretic and statistical perspective. The model is applied to observed choices from a major natural experiment involving intrinsically dynamic choices over highly skewed outcomes. The evidence points to the clear role that income thresholds play in such decision making, but does not rule out a role for tradeoffs between risk and utility or probability weighting. URI: http://hdl.handle.net/10398/7798 Filer i denne post: 1
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