How Does Prospect Theory Reflect Heuristics’ Probability Sensitivity in Risky Choice?

Abstract

Two prominent approaches to describing how people make decisions between risky options are algebraic models and heuristics. The two approaches are based on fundamentally different algorithms and are thus usually treated as antithetical, suggesting that they may be incommensurable. Using cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as an illustrative case of an algebraic model, we demonstrate how algebraic models and heuristics can mutually inform each other. Specifically, we highlight that CPT describes decisions in terms of psychophysical characteristics, such as diminishing sensitivity to probabilities, and we show that this holds even when the underlying process is heuristic in nature. Our results suggest that algebraic models and heuristics might offer complementary rather than rival modeling frameworks and highlight the potential role of heuristic principles in information processing for prominent descriptive constructs in risky choice.


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