EconPapers    
Economics at your fingertips  
 

Learning and dropout in contests: an experimental approach

Francesco Fallucchi, Jan Niederreiter () and Massimo Riccaboni ()
Additional contact information
Jan Niederreiter: IMT Institute for Advanced studies
Massimo Riccaboni: IMT Institute for Advanced studies

Theory and Decision, 2021, vol. 90, issue 2, No 5, 245-278

Abstract: Abstract We design an experiment to study investment behavior in different repeated contest settings, varying the uncertainty of the outcomes and the number of participants in contests. We find decreasing over-expenditures and a higher rate of ‘dropout’ in contests with high uncertainty over outcomes (winner-take-all contests), while we detect a quick convergence toward equilibrium predictions and a near to full participation when this type of uncertainty vanishes (proportional-prize contests). These results are robust to changes in the number of contestants. A learning parameter estimation using the experience-weighted attraction (EWA) model suggests that subjects adopt different learning modes across different contest structures and helps to explain expenditure patterns deviating from theoretical predictions.

Keywords: Learning; Dropout; Experiment; Contest; Experience-weighted attraction (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11238-020-09783-z Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:theord:v:90:y:2021:i:2:d:10.1007_s11238-020-09783-z

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/11238/PS2

DOI: 10.1007/s11238-020-09783-z

Access Statistics for this article

Theory and Decision is currently edited by Mohammed Abdellaoui

More articles in Theory and Decision from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:kap:theord:v:90:y:2021:i:2:d:10.1007_s11238-020-09783-z