Arbeitspapier

Optimal similarity judgments in intertemporal choice (and beyond)

We use a simple cost-benefit analysis to derive optimal similarity judgments - addressing the question: when should we expect a decision maker to distinguish between different time periods or different prizes? Our key premise is that cognitive resources are costly and are to be deployed only where they really matter. We show that this simple insight can explain a number of observed anomalies, such as: (i) time preference reversal, (ii) magnitude effects, (iii) interval length effects. For each of these phenomena, our approach allows to identify the direction of the bias relative to the benchmark case where cognitive resources are costless. Finally, we show that, when applied to choice under risk, the same insights predict anomalies such as the ratio and certainty effects, and rationalize Rabin's risk aversion paradox. This suggests that the theory may provide a parsimonious explanation of behavioral anomalies in different contexts.

Sprache
Englisch

Erschienen in
Series: CeDEx Discussion Paper Series ; No. 2019-06

Klassifikation
Wirtschaft
Microeconomic Behavior: Underlying Principles
Consumer Economics: Theory
Micro-Based Behavioral Economics: General‡
Thema
Similarity judgments
Intertemporal Choice
Rational Inattention
Choice Under Risk

Ereignis
Geistige Schöpfung
(wer)
Adriani, Fabrizio
Sonderegger, Silvia
Ereignis
Veröffentlichung
(wer)
The University of Nottingham, Centre for Decision Research and Experimental Economics (CeDEx)
(wo)
Nottingham
(wann)
2019

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Adriani, Fabrizio
  • Sonderegger, Silvia
  • The University of Nottingham, Centre for Decision Research and Experimental Economics (CeDEx)

Entstanden

  • 2019

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