Revealed Decision Rules in Choices Under Risk∗
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摘要
The paper proposes the Maximum Rule Concentration Index (MRCI) to measure how parsimoniously menu-dependent decision rules explain repeated binary lottery choices, provides an MIQP and a scalable greedy heuristic to compute it, and applies a permutation test to show that average subject-level MRCI ≈ 0.545 (Neff ≈ 1.85) with 64.1% of subjects rejecting a menu‑independent random benchmark at 1% — modal-payoff focusing (MAP) and salience (SAL) account for most concentration gains [page::2].
