How to Counteract Biased Self-Assessments? An Experimental Investigation of Reactions to Social Information

43 Pages Posted: 28 Sep 2021 Last revised: 16 Apr 2023

See all articles by Gerlinde Fellner-Röhling

Gerlinde Fellner-Röhling

Ulm University - Department of Mathematics and Economics

Kristijan Hromek

Independent

Janina Kleinknecht

affiliation not provided to SSRN; Ulm University - Department of Mathematics and Economics

Sandra Ludwig

Ulm University

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Abstract

In a lab experiment, we investigate whether social information can improve the accuracy of self-assessments of relative performance. In particular, we compare the effectiveness of di erent types of social information: subjects either learn their close peers' (i) average absolute performance, (ii) average self-assessment or (iii) average bias of self-assessments. Additionally, we explore the demand for the different types of social information. Our results suggest that social information can help debiasing subjects' self-assessments, but not all types of information are equally effective. Only learning about the average bias of peers improves own self-assessments. Subjects are, in general, willing to pay for social information but mostly prefer information about their peers' absolute performance, which is the least helpful type of social information. Consequently, endogenous choice of social information does not further improve self-assessments.

Keywords: social information, feedback, overcondence, experiment, debiasing strategies

Suggested Citation

Fellner-Röhling, Gerlinde and Hromek, Kristijan and Kleinknecht, Janina and Kleinknecht, Janina and Ludwig, Sandra, How to Counteract Biased Self-Assessments? An Experimental Investigation of Reactions to Social Information. Available at SSRN: https://ssrn.com/abstract=3932106 or http://dx.doi.org/10.2139/ssrn.3932106

Gerlinde Fellner-Röhling

Ulm University - Department of Mathematics and Economics ( email )

Helmholzstrasse
Ulm, D-89081
Germany

Kristijan Hromek

Independent ( email )

Janina Kleinknecht (Contact Author)

Ulm University - Department of Mathematics and Economics ( email )

Helmholtzstrasse 18
Ulm, D-89081
Germany

affiliation not provided to SSRN

No Address Available

Sandra Ludwig

Ulm University ( email )

Ulm University
Helmholtzstrasse 18
Ulm, Baden-Württemberg 89081
Germany

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