MS2016029.pdf (435.83 kB)
Download file

Social Information “Nudges”: An Experiment with Multiple Group References

Download (435.83 kB)
journal contribution
posted on 31.03.2017, 15:37 by Shaun Hargreaves Heap, Abhijit Ramanlingam, David Rojo Arjona
Social information “nudges” concerning how others perform typically boost individual performances in experiments with one group reference point. However, in many natural settings, sometimes due to policy, there are several such group reference points. We address the complications that such multiple group social information might introduce through an experiment. The boost to average performance is significant and comparable to the one group case. Between-group inequality does not change. Individual inequality falls, however, because the boost is largest among the pre-“nudge” very poor performers. Finally, the boost to average performance is highest when individuals freely choose their group affiliations.

Funding

Hargreaves Heap’s work was supported by the Economic and Social Science Research Council through the Network for Integrated Behavioural Science (Grant reference ES/K002201/1). Funding from the School of Economics, University of East Anglia and the Department of Political Economy, King’s College London is gratefully acknowledged.

History

Citation

Southern Economic Journal, 2017

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/Department of Economics

Version

AM (Accepted Manuscript)

Published in

Southern Economic Journal

Publisher

Wiley, Southern Economic Association

issn

0038-4038

eissn

2325-8012

Acceptance date

24/02/2017

Copyright date

2017

Available date

17/03/2019

Publisher version

http://onlinelibrary.wiley.com/doi/10.1002/soej.12210/abstract

Notes

JEL classifications: C91, D03, D60;The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

Usage metrics

Categories

Keywords

Exports