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Can problem-solving attitudes explain the gender gap in financial literacy? Evidence from Italian students’ data

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  • Sergio Longobardi

    (University of Naples “Parthenope”)

  • Margherita Maria Pagliuca

    (University of Naples “Parthenope”)

  • Andrea Regoli

    (University of Naples “Parthenope”)

Abstract

Recent results from the OECD PISA (Financial literacy assessment framework. Australian Council for Educational Research. ACER, Australia, 2012) highlight that Italy is the only surveyed country where, among 15-year-old students, boys perform significantly better than girls in terms of financial literacy. This gap is relevant because financially literacy is crucial to make sound financial decisions and, consequently, it is likely to impact strongly on well-being of women. The main findings reveal that students’ performance in financial literacy is most strongly influenced by some personality traits, such as perseverance and openness to solving complex problems, and, at same time, by the school career and the type of school attended. Their effects are larger among low-performing students than in the upper tail of the score distribution. A decomposition exercise of the gender gap in financial literacy confirms the role played by motivational and attitudinal factors and, at the same time, highlights that putting males and females on an even footing with respect to personal characteristics does not suffice to close the gap.

Suggested Citation

  • Sergio Longobardi & Margherita Maria Pagliuca & Andrea Regoli, 2018. "Can problem-solving attitudes explain the gender gap in financial literacy? Evidence from Italian students’ data," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1677-1705, July.
    • Handle: RePEc:spr:qualqt:v:52:y:2018:i:4:d:10.1007_s11135-017-0545-0
    DOI: 10.1007/s11135-017-0545-0
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    3. Giovanna Di Castro & Valentina Ferri, 2022. "Why do boys perform worse than girls in reading literacy? Evidences from PISA survey 2018," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 76(1), pages 144-156, January-M.
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    5. Falco J. Bargagli Stoffi & Kenneth De Beckker & Joana E. Maldonado & Kristof De Witte, 2021. "Assessing Sensitivity of Machine Learning Predictions.A Novel Toolbox with an Application to Financial Literacy," Papers 2102.04382, arXiv.org.

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