March 28th: Martin Meier (IHS, Vienna)
Perfect Quasi-Perfect Equilibrium (with L. Blume)
Leonardo Pejsachowicz (Princeton U.),
Breadth versus Depth (with M. Richet and S. Geng)
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)? Generally, we find that breadth is optimal for “small” problems and that depth is optimal for “large” ones. We find that in a political setting where voters learn about candidates and find a rational justification for the stylized fact that voters tend to learn only about their preferred candidate. Finally, we consider extensions to fat-tails, correlation, and a strategic IO setting and find that in all extensions, breadth is superior.
Chantal Marlats (LEMMA, U. Paris II),
Reputation effects in stochastic games with two long-lived players.