OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
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.
Please sign up for meetings using the below:
docs.google.com/spreadsheets/d/1eYzLT2DsbTivOvrVx3OGaE4alXvBO_ALCow3yV_fW8o/edit#gid=0
