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Estimating causal effects of extended school closures on non-cognitive factors: evidence from TIMSS and PISA

Author

Listed:
  • Marzena Binkiewicz

    (Faculty of Economic Sciences, University of Warsaw)

  • Artur Pokropek

    (Institute of Philosophy and Sociology, Polish Academy of Sciences)

Abstract

This study investigates the causal impact of prolonged school closures during the COVID-19 pandemic on non-cognitive predictors of mathematics achievement and the strength of their association with student performance. Drawing on data from TIMSS (2015, 2019, 2023) and PISA (2022), we apply difference-in-differences (DiD) models across two research designs: successive cross-sections of 4th-grade cohorts and a pseudo-panel following a cohort from primary to secondary school. Our findings indicate that, although school closures did not significantly affect the level of students’ self-beliefs, they did reduce the strength of the association between negative attitudes and achievement—particularly among girls and in OECD countries. The results highlight the nuanced effects of distance learning on mathematics outcomes, contributing to the literature on the role of affective-motivational factors in education.

Suggested Citation

  • Marzena Binkiewicz & Artur Pokropek, 2025. "Estimating causal effects of extended school closures on non-cognitive factors: evidence from TIMSS and PISA," Working Papers 2025-16, Faculty of Economic Sciences, University of Warsaw.
    • Handle: RePEc:war:wpaper:2025-16
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    File URL: https://www.wne.uw.edu.pl/download_file/5750/0
    File Function: First version, 2025
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    More about this item

    Keywords

    Mathematics achievement; non-cognitive factors; distance learning; school closures; TIMSS; PISA; gender differences; math anxiety; self-efficacy;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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