Noisy preferences in risky choice: A cautionary note

Area of Science:

• Cognitive Psychology
• Behavioral Economics
• Decision Science

Background:

• Risky decision-making models often assume perfect rationality.
• However, real-world choices are influenced by various sources of noise.
• Understanding these noise effects is crucial for accurate preference modeling.

Purpose of the Study:

• To investigate how noise in preference parameters and response processes impacts observed choices.
• To demonstrate that noise can create apparent risk aversion or seeking, and nonlinear probability weighting.
• To highlight the limitations of inferring preferences from modal choices without accounting for noise.

Main Methods:

• Simulated decision-making scenarios with varying noise levels.
• Analysis of choice proportions under different noise conditions.
• Comparison of model fits with and without accounting for dual noise sources.

Main Results:

• Noise in preference parameters can mimic systematic risk aversion or risk seeking.
• Combined noise can lead to apparent nonlinear probability weighting, deviating from expected utility theory.
• Modal choices are unreliable indicators of underlying preferences when noise is present.

Conclusions:

• Observed choices in risky decision-making are a complex interplay of true preferences and noise.
• Accurate quantitative models must incorporate both preference and response noise.
• Failure to account for noise can lead to erroneous inferences about decision-making behavior.