Matching information

Artikel

We analyze the optimal allocation of experts to teams, where experts differ in the precision of their information, and study the assortative matching properties of the resulting assignment. The main insight is that in general it is optimal to diversify the composition of the teams, ruling out positive assortative matching. This diversification leads to negative assortative matching when teams consist of pairs of experts. And when experts' signals are conditionally independent, all teams have similar precision. We also show that if we allow experts to join multiple teams, then it is optimal to allocate them equally across all teams. Finally, we analyze how to endogenize the size of the teams, and we extend the model by introducing heterogeneous firms in which the teams operate.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Theoretical Economics ; ISSN: 1555-7561 ; Volume: 13 ; Year: 2018 ; Issue: 1 ; Pages: 377-414 ; New Haven, CT: The Econometric Society

Classification and Topics

• Classification: Wirtschaft ; Bargaining Theory; Matching Theory ; Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
• Subject: Assortative matching ; teams ; diversification ; correlation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Chade, Hector ; Eeckhout, Jan
• Event: Veröffentlichung
• (who): The Econometric Society
• (where): New Haven, CT
• (when): 2018

Further information

• DOI: doi:10.3982/TE1820
• Handle: http://hdl.handle.net/10419/197150
• Last update: 10.03.2025, 11:43 AM CET