Stochastic models in experimental economics

 

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dc.contributor.advisor Harrison, Glenn W en_ZA
dc.contributor.advisor Ross, Don en_ZA
dc.contributor.author Monroe, Brian Albert en_ZA
dc.date.accessioned 2018-05-07T14:19:55Z
dc.date.available 2018-05-07T14:19:55Z
dc.date.issued 2018 en_ZA
dc.identifier.citation Monroe, B. 2018. Stochastic models in experimental economics. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/27979
dc.description.abstract Shortly after the introduction of Expected Utility Theory (EUT), economists and psychologists began publishing results that showed choices made by experimental subjects which apparently violate one or more of the EUT axioms. I discuss economists' responses to this evidence. These vary from developing new theoretical models, models that nest EUT as a special case, such as Rank Dependent Utility (RDU) and Regret Theory, as well as models that do not nest EUT, such as Cumulative Prospect Theory, to critiques of experimental methods and scope, to the promotion of stochastic models of choice. I discuss popular stochastic choice models in depth and evaluate their normative coherence. I find that the "Random Preferences" stochastic model fails to make normatively coherent statements, in contrast to the "Random Error" and "Tremble" models, which do so. I demonstrate a method to calculate the unconditional likelihood of choice errors for populations of EUT-compliant and RDU-compliant agents, and show how certain characteristics of the population relate to the likelihood of these choice errors and their costliness in terms of forgone welfare. I find that elements of the stochastic model that are not related to preference relations tend to have a greater influence on unconditional welfare estimates than the preference parameters themselves. Finally, I conduct a power analysis of the ability of a lottery battery instrument to correctly classify experimental subjects as employing either EUT or RDU, and the effect of this classification on the accuracy of the estimates of welfare surplus for the subjects. For large ranges of parameter values for these models, I find that the probability of type I and type II errors in the classification process are not trivial, and can be very costly in terms of welfare surplus. Additionally, I show that for a hypothetical population comprising subjects employing EUT or RDU, we can arrive at more accurate welfare surplus estimates on average by assuming that every subject employs the RDU functional, rather than by first trying to differentiate RDU subjects from EUT subjects. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Economics en_ZA
dc.title Stochastic models in experimental economics en_ZA
dc.type Doctoral Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Commerce en_ZA
dc.publisher.department School of Economics en_ZA
dc.type.qualificationlevel Doctoral
dc.type.qualificationname PhD en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Monroe, B. A. (2018). <i>Stochastic models in experimental economics</i>. (Thesis). University of Cape Town ,Faculty of Commerce ,School of Economics. Retrieved from http://hdl.handle.net/11427/27979 en_ZA
dc.identifier.chicagocitation Monroe, Brian Albert. <i>"Stochastic models in experimental economics."</i> Thesis., University of Cape Town ,Faculty of Commerce ,School of Economics, 2018. http://hdl.handle.net/11427/27979 en_ZA
dc.identifier.vancouvercitation Monroe BA. Stochastic models in experimental economics. [Thesis]. University of Cape Town ,Faculty of Commerce ,School of Economics, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/27979 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Monroe, Brian Albert AB - Shortly after the introduction of Expected Utility Theory (EUT), economists and psychologists began publishing results that showed choices made by experimental subjects which apparently violate one or more of the EUT axioms. I discuss economists' responses to this evidence. These vary from developing new theoretical models, models that nest EUT as a special case, such as Rank Dependent Utility (RDU) and Regret Theory, as well as models that do not nest EUT, such as Cumulative Prospect Theory, to critiques of experimental methods and scope, to the promotion of stochastic models of choice. I discuss popular stochastic choice models in depth and evaluate their normative coherence. I find that the "Random Preferences" stochastic model fails to make normatively coherent statements, in contrast to the "Random Error" and "Tremble" models, which do so. I demonstrate a method to calculate the unconditional likelihood of choice errors for populations of EUT-compliant and RDU-compliant agents, and show how certain characteristics of the population relate to the likelihood of these choice errors and their costliness in terms of forgone welfare. I find that elements of the stochastic model that are not related to preference relations tend to have a greater influence on unconditional welfare estimates than the preference parameters themselves. Finally, I conduct a power analysis of the ability of a lottery battery instrument to correctly classify experimental subjects as employing either EUT or RDU, and the effect of this classification on the accuracy of the estimates of welfare surplus for the subjects. For large ranges of parameter values for these models, I find that the probability of type I and type II errors in the classification process are not trivial, and can be very costly in terms of welfare surplus. Additionally, I show that for a hypothetical population comprising subjects employing EUT or RDU, we can arrive at more accurate welfare surplus estimates on average by assuming that every subject employs the RDU functional, rather than by first trying to differentiate RDU subjects from EUT subjects. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Stochastic models in experimental economics TI - Stochastic models in experimental economics UR - http://hdl.handle.net/11427/27979 ER - en_ZA


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