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PublicationArticle (with peer review)

Gender differences in financial literacy: The role of stereotype threat

Abstract

Understanding why women display less financial literacy than men is crucial for developing policies to reduce gender inequalities and improve women’s financial behavior. In a series of studies, we investigate whether the observed gender gap in financial literacy can be identified in nonnumerical contexts, if it can be related to confidence in financial matters, and if it can be attributed to stereotype threat, which posits that inbuilt prejudices about gender and finance undermine performance among women in tasks involving finance. We utilized data from the Swedish Standardized Scholastic Aptitude Test (n = 40,662) to investigate if there is a greater difference in reading comprehension between men and women when reading about topics related to finance. Furthermore, we conducted large-scale online data collection (n = 1989), including a survey on financial vocabulary and an experiment that manipulated the salience of the financial content across conditions when assessing financial literacy. The results show that the observed gender gap in financial literacy is robust also in a nonnumerical financial contexts and that it can not be attributed to a difference in (displayed) confidence. Finally, mediation analysis showed a significant indirect effect of gender on financial literacy through financial anxiety suggesting that a stereotype threat for women in the financial domain contributes to the observed gender gap.

Tinghög, G., Ahmed, A., Barrafrem, K., Lind, T., Skagerlund, K., & Västfjäll, D. (2021). Gender differences in financial literacy: The role of stereotype threat. Journal of Economic Behavior & Organization, 192, 405-416.

Details

Author
Tinghög, G., Ahmed, A., Barrafrem, K., Lind, T., Skagerlund, K., & Västfjäll, D.
Publication year
2021
Published in

Journal of Economic Behavior & Organization, 192, 405-416.


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Article (with peer review)

Artificial Intelligence for Public Use

Lodefalk, M.; Engberg, E.; Lidskog, R.; Skargren, F.; Tang, A.
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Publication year

2026

Published in

Digital Society

Abstract

The public sector faces rising expectations, demographic change and persistent efficiency challenges. This article examines both the potential and limitations of AI in public services. Using an interdisciplinary conceptual framework, it analyses organisational, regulatory, technical and ethical barriers. It also simulates AI’s possible long-term effects on labour demand and productivity in Sweden using administrative data and occupational AI-exposure measures. The scenarios suggest that AI could help ease labour shortages and raise productivity, although effects vary substantially across subsectors and types of organisation. The results are scenarios, not forecasts.

Working paper

Ratio Working Paper No. 393: What is an AI Worker? Evidence from Matched Vacancy-Hires

Hellsten, M.
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Publication year

2026

Published in

Ratio Working Paper Series.

Abstract

Despite growing policy interest in AI workforce development, surprisingly little is known about what defines these workers, or indeed if they differ from their occupational peers. Using a novel matched vacancy-hire dataset linking Swedish job postings to the individuals hired to fill them, drawn from register data on the entire Swedish population, I study the characteristics of workers who develop and apply AI. Observable traits including high cognitive ability, a tertiary degree in STEM subjects, and a recent migrant background largely explain occupational sorting. Of these, only higher education, prior AI experience, and a science degree set them apart within occupation. I then use earnings as a window onto unobservable differences: AI workers earn approximately 5% more than their peers, entirely explained by firm-level wages. However, AI workers with a doctorate degree stand out sharply in both traits and earnings, indicating that AI workers split into segments that differ by the complexity of their skills and tasks. Taken together, these results point to two distinct policy levers: the supply of average AI workers, termed AI integrators, can be expanded via STEM education participation, while the elite AI developers are supplied by researchers moving to the private sector.

Reports

Effects of School Leadership in Sweden: An Evaluation of the National Principal Training Programme 2009–2021

R. Persson, E. Demir & K. Wennberg

Publication year

2026

Published in

IFAU Report 2026:19

Abstract

This report evaluates Sweden’s National Principal Training Programme using data on 3,783 participants from 2009 to 2021. The results indicate no noticeable improvement in student outcomes or teachers’ assessments of principals’ pedagogical leadership. The analyses also suggest that principals have limited influence on variation in grades compared with other factors.

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