Beyond the two-state setting: Do individuals generally underinfer from high-weight information?

180 Pages Posted: 13 Jul 2020 Last revised: 24 Feb 2022

See all articles by Maren Baars

Maren Baars

University of Muenster - Finance Center

Thomas Langer

University of Muenster - Finance Center

Hannes Mohrschladt

University of Muenster - Finance Center

Date Written: June 19, 2020

Abstract

Individuals have been shown to systematically deviate from Bayes' law when updating probabilistic beliefs. Experimental studies indicate that individuals' underinference with respect to new signal sets is more pronounced if the weight or reliability of the signal set is high. We challenge the generality of this prominent finding and argue that the two-state setting, which dominates experimental research, is an extreme and peculiar case with respect to the normative importance of signal set characteristics. Thus, previously identified judgment biases might not extend to settings with more than two states. Our experimental analyses support this conjecture as they show that individuals' weight-dependent underinference is no general phenomenon but specific to the two-state setting. Given that many real-world information environments do not resemble such a simplified setting, our results caution against an indiscriminate transfer of popular biases in belief updating to a broad set of real-world applications.

Keywords: Information Weight, Over- and Underinference, Judgment Biases

JEL Classification: C91, D91

Suggested Citation

Baars, Maren and Langer, Thomas and Mohrschladt, Hannes, Beyond the two-state setting: Do individuals generally underinfer from high-weight information? (June 19, 2020). Available at SSRN: https://ssrn.com/abstract=3631011 or http://dx.doi.org/10.2139/ssrn.3631011

Maren Baars

University of Muenster - Finance Center ( email )

Universitätsstraße 14-16
Münster, 48143
Germany

Thomas Langer

University of Muenster - Finance Center ( email )

Universitatsstr. 14-16
Muenster, 48143
Germany
+49 251 83 22033 (Phone)

Hannes Mohrschladt (Contact Author)

University of Muenster - Finance Center ( email )

Universitätsstr. 14-16
Muenster, 48143
Germany

HOME PAGE: http://www.wiwi.uni-muenster.de/fcm/en/the-fcm/lsf/team/hannes-mohrschladt

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
167
Abstract Views
922
Rank
284,461
PlumX Metrics