Abstract

People often make choices with imperfect knowledge of how the variables in their decision problem are related. We study such choices when individuals face menus of conflicting and possibly misspecified models that link these variables. Do they discard inaccurate models, what types of inaccuracies do they detect, and how? Or do they instead follow models that sound appealing at face value, and what determines that appeal?

First, many individuals readily intuit the models' predicted correlations and reject models that contradict the data. Performance is high because the required inference is qualitative rather than quantitative. Second, when unable to identify the correct model, most choose cautiously by focusing on worst-case outcomes.

Materials

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