The Influence of Gender on Individuals’ Ability to Predict Their Own Risk Tolerance: Evidence from a European Country

Júlio Lobão ()
Additional contact information
Júlio Lobão: School of Economics and Management, University of Porto, Rua Dr. Roberto Frias, 4200-464 Porto, Portugal

Administrative Sciences, 2024, vol. 14, issue 3, 1-16

Abstract: The literature on individuals’ ability to predict their own level of risk tolerance is scarce and presents divergent results. Utilizing both differential prediction models and logit models on a sample of 391 individuals in Portugal, this study demonstrates that respondents’ gender play a crucial role in this predictive ability. Men tend to overestimate their level of risk tolerance, while women tend to believe they are less risk-tolerant than they actually are. Furthermore, the results reveal that men’s ability to correctly predict their level of risk tolerance is significantly higher. Being a man implies a 20% higher probability of being consistent in this prediction compared to being a woman, even after controlling for a set of sociodemographic factors. The finding of a systematic inconsistency between measures of subjective and objective risk tolerance suggests that the choice between the two measures of risk propensity is not indifferent. Our findings have relevant implications in the fields of corporate finance, financial investment, and various other spheres of economic life.

Keywords: risk tolerance; subjective risk tolerance; objective risk tolerance; survey; gender; Portugal; psychometric tests (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2076-3387/14/3/56/pdf (application/pdf)
https://www.mdpi.com/2076-3387/14/3/56/ (text/html)

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:gam:jadmsc:v:14:y:2024:i:3:p:56-:d:1357525

Access Statistics for this article

Administrative Sciences is currently edited by Ms. Nancy Ma

More articles in Administrative Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().