Herding with and Without Payoff Externalities - an Internet Experiment

24 Pages Posted: 22 Aug 2004

See all articles by Mathias Drehmann

Mathias Drehmann

Bank for International Settlements (BIS)

Joerg Oechssler

University of Heidelberg - Alfred Weber Institute for Economics

Andreas Roider

University of Regensburg - Department of Economics and Econometrics; IZA Institute of Labor Economics

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Date Written: August 2004

Abstract

Most real world situations which are susceptible to herding are also characterized by direct payoff externalities. Yet, the bulk of the theoretical and experimental literature focuses on pure informational externalities. In this paper we study several different forms of payoff externalities that interact with a standard herding model. More than 6000 subjects, including a subsample of 267 consultants from an international consulting firm, participated in an internet experiment. We also replicate and review earlier cascade experiments. Finally, we study reputation effects in the context of herding.

Keywords: Information cascades, herding, network effects, reputation, experiment, internet

JEL Classification: C92, D8

Suggested Citation

Drehmann, Mathias and Oechssler, Joerg and Roider, Andreas, Herding with and Without Payoff Externalities - an Internet Experiment (August 2004). Available at SSRN: https://ssrn.com/abstract=579904 or http://dx.doi.org/10.2139/ssrn.579904

Mathias Drehmann

Bank for International Settlements (BIS) ( email )

Centralbahnplatz 2
CH-4002 Basel
Switzerland

Joerg Oechssler (Contact Author)

University of Heidelberg - Alfred Weber Institute for Economics ( email )

Grabengasse 14
Heidelberg, D-69117
Germany
+49 6221 54 3548 (Phone)
+49 6221 54 3630 (Fax)

HOME PAGE: http://www.awi.uni-heidelberg.de/with2/theorie2/Team/Oechssler/Oechssler_main.html

Andreas Roider

University of Regensburg - Department of Economics and Econometrics ( email )

Universitaetsstrasse 31
D-93040 Regensburg
Germany

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

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