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The Implications of Experimental Design for Choice Data

Caradonna, Pete (2020) The Implications of Experimental Design for Choice Data. In: D-TEA 2020 CONFERENCE: "PROSPECT THEORY", 16-19 June 2020, [Online]. (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20221027-210939113

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Abstract

Cycles in revealed preference data are often interpreted as fundamental units of choice-theoretic inconsistency. We fully characterize the manner in which the structure of a choice environment can lead to non-trivial dependence relations between cyclic choice patterns in data. We show that for any finite data set, while there may not be a unique maximal independent collection of choice cycles that explain the entirety of the inconsistency, the size of any such collection of cycles is well-defined. We utilize this to provide a means of controlling for the influence of experimental structure in the construction of inconsistency indices for choice data.


Item Type:Conference or Workshop Item (Paper)
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Record Number:CaltechAUTHORS:20221027-210939113
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20221027-210939113
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:117627
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:28 Oct 2022 15:05
Last Modified:28 Oct 2022 15:05

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