Mood-driven choices and self-regulation
Mood-driven choices and self-regulation
We model a decision maker who can exert costly effort to regulate herself, thereby reducing internal conflicts between her normative objectives and mood-driven choices. We provide an axiomatic characterization of the model, and show how costs of self-regulation can be elicited and compared across individuals. In a consumption-saving problem we show that self-regulation can generate unintended income effects, which have important implications for public policies on saving behavior. We also provide several examples to illustrate how self-regulation can rationalize many well-known choice anomalies. These behavioral implications follow from a key feature of the model that self-regulation decisions can respond to changes in incentives.
727-760
Mihm, Max
3123d6b8-55e0-4cd4-ada5-542cd1f1f58f
Ozbek, Kemal
e7edfcf5-cb17-4e64-bfa4-30fb527d2e46
July 2018
Mihm, Max
3123d6b8-55e0-4cd4-ada5-542cd1f1f58f
Ozbek, Kemal
e7edfcf5-cb17-4e64-bfa4-30fb527d2e46
Abstract
We model a decision maker who can exert costly effort to regulate herself, thereby reducing internal conflicts between her normative objectives and mood-driven choices. We provide an axiomatic characterization of the model, and show how costs of self-regulation can be elicited and compared across individuals. In a consumption-saving problem we show that self-regulation can generate unintended income effects, which have important implications for public policies on saving behavior. We also provide several examples to illustrate how self-regulation can rationalize many well-known choice anomalies. These behavioral implications follow from a key feature of the model that self-regulation decisions can respond to changes in incentives.
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Accepted/In Press date: 7 May 2018
e-pub ahead of print date: 9 May 2018
Published date: July 2018
Identifiers
Local EPrints ID: 436134
URI: http://eprints.soton.ac.uk/id/eprint/436134
ISSN: 0022-0531
PURE UUID: 5633a430-dd54-46a4-9896-867176579a25
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Date deposited: 29 Nov 2019 17:30
Last modified: 17 Mar 2024 03:59
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Author:
Max Mihm
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