Piermont, Evan
(2017)
Learning about Preference.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
Abstract
This dissertation includes three essays, each investigating the formation and evolution of preference, with particular attention paid to epistemological concerns, dynamics, and learning. Loosely speaking, each chapter provides a different approach to modeling how a Decision Maker (DM) might learn about her own preference. The work as a whole adheres to the classical notions of revealed preference and utility maximization and the chapters are ordered by their level of abstraction. The first chapter considers DM who learns by observing the environment in which decisions must be made. The second chapter, written jointly with Roee Teper, considers a DM who learns by observing the consequences of her prior choices. Finally, the third chapter considers a DM who learns novel of which she previously had not conception.
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Details
Item Type: |
University of Pittsburgh ETD
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Status: |
Unpublished |
Creators/Authors: |
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ETD Committee: |
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Date: |
1 July 2017 |
Date Type: |
Publication |
Defense Date: |
31 March 2017 |
Approval Date: |
1 July 2017 |
Submission Date: |
8 March 2017 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
139 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Dietrich School of Arts and Sciences > Economics |
Degree: |
PhD - Doctor of Philosophy |
Thesis Type: |
Doctoral Dissertation |
Refereed: |
Yes |
Uncontrolled Keywords: |
responsive learning, menu-dependent choice, unawareness, epistemic preference, preference formation |
Related URLs: |
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Date Deposited: |
01 Jul 2017 22:38 |
Last Modified: |
01 Jul 2017 22:38 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/31068 |
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Learning about Preference. (deposited 01 Jul 2017 22:38)
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