The central question we address in this paper is: what can an analyst infer from choice data about what a decision maker has learned? The key constraint we impose, which is shared across models of Bayesian learning, is that any learning must be rationalizable. To implement this constraint, we...

We introduce a simple method of recovering attention costs from choice data. Our method rests on a precise analogy with production theory. Costs of attention determine consumer demand and consumer welfare just as a competitive firm's technology determines its supply curve and profits. We...

Costs of attention, while central to choice behavior, have proven hard to measure. We introduce a simple method of recovering them from choice data. Our recovery method rests on the observation that costs of attention play precisely the same role in consumer choice as do a competitive firm's...