Recency, Records and Recaps: The effect of feedback on behavior in a simple decision problem*

Suboptimal behavior can persist in simple stochastic decision problems. This has motivated the development of solution concepts such as cursed equilibrium (Eyster & Rabin 2005) and behavioral equilibrium (Esponda 2008). We experimentally study a simple adverse selection (or “lemons”) problem and find that learning models that heavily discount past information (i.e. display recency bias) explain patterns of behavior better than Nash, cursed or behavioral equilibrium. Providing counterfactual information or a record of past outcomes does little to aid convergence to optimal strategies, but providing sample averages (“recaps”) gets individuals most of the way to optimality. Thus recency effects are not solely due to limited memory but stem from some other form of cognitive constraints.

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