Crowdsourcing Peer Information to Change Spending Behavior

70 Pages Posted: 22 Feb 2019 Last revised: 2 Jun 2020

See all articles by Francesco D'Acunto

Francesco D'Acunto

Boston College

Alberto G. Rossi

Georgetown University

Michael Weber

University of Chicago - Finance; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: May 2020


Consumers might overestimate optimal spending if forming beliefs based on others' spending, because others' conspicuous consumption is more visible than the rest of their consumption. If true, information about others' overall spending should change beliefs and choice. For a test, we provide crowdsourced information about anonymous “peer groups" to users of a FinTech app. Users converge to peers, especially when peer groups are more informative. For identification, we compare similar users matched to different peers based on sharp thresholds. A randomized control trial on a non-selected population supports external validity. Our results inform the design of robo-advisors for spending.

Keywords: FinTech, Learning, Beliefs and Expectations, Robo-advising, Visibility Bias, Social Transmission, Information Economics, Household Finance.

JEL Classification: D12, D14, D91, E22, G41

Suggested Citation

D'Acunto, Francesco and Rossi, Alberto G. and Weber, Michael, Crowdsourcing Peer Information to Change Spending Behavior (May 2020). Chicago Booth Research Paper No. 19-09, Fama-Miller Working Paper, Available at SSRN: or

Francesco D'Acunto

Boston College ( email )

140 Commonwealth Avenue
Chestnut Hill, MA 02467
United States

Alberto G. Rossi

Georgetown University ( email )

McDonough School of Business
Georgetown University
Washington, DC 20057
United States

Michael Weber (Contact Author)

University of Chicago - Finance ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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