Published in:University of Arizona Working Paper 18-05
Extent:
1 Online-Ressource (47 p)
Language:
English
DOI:
10.2139/ssrn.3138936
Identifier:
Origination:
Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 30, 2019 erstellt
Description:
I show that persistent underconfidence and overconfidence each arise from the combination of Bayesian learning about one's own abilities and rationally choosing to exert more effort when more confident. If an agent believes that greater effort reliably improves outcomes, then the agent learns away overconfidence faster than he learns away underconfidence. The agent becomes underconfident on average. In contrast, the agent becomes overconfident on average if he believes that greater effort increases his exposure to chance. The results imply that a principal can extract more effort from an agent by conditioning the precision of feedback on performance, and the mechanism is consistent with modern understanding of depression