Risky choice and Weber's Law

Area of Science:

• Behavioral Economics
• Cognitive Psychology
• Decision Science

Background:

• Existing models of risky choice often lack quantitative predictive power.
• Reboreda & Kacelnik's foraging model provided qualitative insights into risk sensitivity.
• Weber's Law in memory has not been extensively applied to models of choice under risk.

Purpose of the Study:

• To develop a family of process-based models for risky choice.
• To extend existing models by incorporating the effects of Weber's Law in memory.
• To achieve quantitative predictions of preferences and certainty equivalents in decision-making.

Main Methods:

• Generalizing and extending Reboreda & Kacelnik's risk-sensitive foraging model.
• Applying principles of Weber's Law in memory to behavioral choice.
• Developing models based on linear expected utility as a function of expected outcomes.

Main Results:

• The models quantitatively predict partial preferences between options with varying outcomes.
• The models accurately determine the certainty equivalent for probabilistic outcomes.
• The models predict risk aversion for desirable outcomes (gains) and risk seeking for undesirable outcomes (losses).

Conclusions:

• The proposed models offer a process-based approach to understanding risky choice.
• These models provide better descriptive performance with fewer parameters than existing functional models.
• The integration of memory effects (Weber's Law) enhances the prediction of risk sensitivity.