Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/102670
Authors: 
Gorelkina, Olga
Year of Publication: 
2014
Series/Report no.: 
Preprints of the Max Planck Institute for Research on Collective Goods 2014/11
Abstract: 
This paper introduces a virtually efficient mechanism in a setting with sequentially arriving agents who hold informative signals about future types. To reveal the information the principal organises betting on future type reports. An agent´s betting reward depends on how accurately the prior updated on his report predicts the type reports observed in the following period. The mechanism satisfies participation constraints and generates no deficit after any reported history.
Subjects: 
dynamic mechanisms
scoring rule
Bayesian learning
conjugate priors
JEL: 
D71
D82
D84
D61
Document Type: 
Working Paper

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