Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/227348
Authors: 
Becker, Christoph K.
Melkonyan, Tigran
Proto, Eugenio
Sofianos, Andis
Trautmann, Stefan T.
Year of Publication: 
2020
Series/Report no.: 
IZA Discussion Papers No. 13821
Abstract: 
Bayesian Updating is the dominant theory of learning in economics. The theory is silent about how individuals react to events that were previously unforeseeable or unforeseen. Recent theoretical literature has put forth axiomatic frameworks to analyze the unknown. In particular, we test if subjects update their beliefs in a way that is consistent "reverse Bayesian", which ensures that the old information is used correctly after an unforeseen event materializes. We find that participants do not systematically deviate from reverse Bayesianism, but they do not seem to expect an unknown event when this is reasonably unforeseeable, in two pre-registered experiments that entail unforeseen events. We argue that participants deviate less from the reverse Bayesian updating than from the usual Bayesian updating. We provide further evidence on the moderators of belief updating.
Subjects: 
reverse Bayesianism
unforeseen
unawareness
Bayesian Updating
JEL: 
C11
C91
D83
D84
Document Type: 
Working Paper

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