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Essays in Revealed Preference Theory and Behavioral Economics


Imai, Taisuke (2016) Essays in Revealed Preference Theory and Behavioral Economics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9X63JT5.


Time, risk, and attention are all integral to economic decision making. The aim of this work is to understand those key components of decision making using a variety of approaches: providing axiomatic characterizations to investigate time discounting, generating measures of visual attention to infer consumers' intentions, and examining data from unique field settings.

Chapter 2, co-authored with Federico Echenique and Kota Saito, presents the first revealed-preference characterizations of exponentially-discounted utility model and its generalizations. My characterizations provide non-parametric revealed-preference tests. I apply the tests to data from a recent experiment, and find that the axiomatization delivers new insights on a dataset that had been analyzed by traditional parametric methods.

Chapter 3, co-authored with Min Jeong Kang and Colin Camerer, investigates whether "pre-choice" measures of visual attention improve in prediction of consumers' purchase intentions. We measure participants' visual attention using eyetracking or mousetracking while they make hypothetical as well as real purchase decisions. I find that different patterns of visual attention are associated with hypothetical and real decisions. I then demonstrate that including information on visual attention improves prediction of purchase decisions when attention is measured with mousetracking.

Chapter 4 investigates individuals' attitudes towards risk in a high-stakes environment using data from a TV game show, Jeopardy!. I first quantify players' subjective beliefs about answering questions correctly. Using those beliefs in estimation, I find that the representative player is risk averse. I then find that trailing players tend to wager more than "folk" strategies that are known among the community of contestants and fans, and this tendency is related to their confidence. I also find gender differences: male players take more risk than female players, and even more so when they are competing against two other male players.

Chapter 5, co-authored with Colin Camerer, investigates the dynamics of the favorite-longshot bias (FLB) using data on horse race betting from an online exchange that allows bettors to trade "in-play." I find that probabilistic forecasts implied by market prices before start of the races are well-calibrated, but the degree of FLB increases significantly as the events approach toward the end.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:time preference; risk preference; probability weighting; attention
Degree Grantor:California Institute of Technology
Division:Humanities and Social Sciences
Major Option:Social Science
Awards:John O. Ledyard Prize for Graduate Research in Social Science, 2012
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Camerer, Colin F.
Thesis Committee:
  • Camerer, Colin F. (chair)
  • Cvitanić, Jakša
  • Saito, Kota
  • Shum, Matthew S.
Defense Date:11 December 2015
Funding AgencyGrant Number
Nakajima FoundationUNSPECIFIED
Record Number:CaltechTHESIS:01072016-175429851
Persistent URL:
Imai, Taisuke0000-0002-0610-8093
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9363
Deposited By: Taisuke Imai
Deposited On:11 Jan 2016 23:18
Last Modified:28 Oct 2021 19:17

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