Abstract:
We consider a fundamental trade-off in search: when choosing between multiple unknown alternatives, is it better to learn a little about all of them (breadth) or a lot about a single one (depth)? In choice settings where a values are drawn from an exogenous distribution, we find that breadth is optimal for “small’‘ problems and that depth is optimal for “large’‘ ones. On the other hand, when distributions are endogenously chosen by firms, we find breadth to be always optimal. In a political setting where voters learn about candidates, we find a rational justification for a heretofore unexplained fact: voters tend to learn only about their preferred candidate. Finally, we consider extensions to fat-tails and correlation, and find that in these extensions, breadth is superior.

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