(Sub) Optimality and (non) optimal satisficing in risky decision experiments

Arianna Galliera, Daniela Di Cagno, Werner Güth, Francesca Marzo, Noemi Pace

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

We implement a risky choice experiment based on one-dimensional choice variables and risk neutrality induced via binary lottery incentives. Each participant confronts many parameter constellations with varying optimal payoffs. We assess (sub)optimality, as well as (non) optimal satisficing by eliciting aspirations in addition to choices. Treatments differ in the probability that a binary random event, which are payoff-but not optimal choice-relevant is experimentally induced and whether participants choose portfolios directly or via satisficing, i.e., by forming aspirations and checking for satisficing before making their choice. By incentivizing aspiration formation, we can test satisficing, and in cases of satisficing, determine whether it is optimal.
Original languageEnglish
Pages (from-to)195-243
Number of pages49
JournalTheory and Decision
Volume83
DOIs
Publication statusPublished - 2017

Keywords

  • (un)Bounded rationality
  • Experiments
  • Risk
  • Satisficing
  • Uncertainty

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