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Determinants and Consequences of Student Test Scores: Evidence from International, Big, and Text Data

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  • Pietro Sancassani

Abstract

Pietro Sancassani prepared this study while he was working at the Center for Economics of Education at the ifo Institut. The study was completed in March 2023 and accepted as a doctoral thesis by the Department of Economics at the LMU Munich. It consists of four distinct empirical essays and addresses various determinants and the consequences of student test scores. Chapter 2 investigates the impact of four teacher characteristics – whether teachers hold a Master' s degree, a subject-specific qualification, a major in education, or their level of experience – on student science test scores in ten different countries. Chapter 3 shows that teacher subject-specific qualifications positively affect student science test scores in thirty countries around the world. Chapter 4 shows the association between a measure of patience derived from social media data and student test scores at the regional level. Finally, Chapter 5 shows that the salience of the education topic induced by the "PISA-shock" in Germany led to an increase in the polarization of parliamentary debates about education.

Suggested Citation

  • Pietro Sancassani, 2023. "Determinants and Consequences of Student Test Scores: Evidence from International, Big, and Text Data," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 102, July.
    • Handle: RePEc:ces:ifobei:102
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    File URL: https://www.ifo.de/DocDL/BeitrWiFo_102_Sancassani.pdf
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    References listed on IDEAS

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    1. Woessmann Ludger, 2010. "Institutional Determinants of School Efficiency and Equity: German States as a Microcosm for OECD Countries," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(2), pages 234-270, April.
    2. Ludger Woessmann & Elke Luedemann & Gabriela Schuetz & Martin R. West, 2009. "School Accountability, Autonomy and Choice Around the World," Books, Edward Elgar Publishing, number 13540.
    3. Wo[ss]mann, Ludger & West, Martin, 2006. "Class-size effects in school systems around the world: Evidence from between-grade variation in TIMSS," European Economic Review, Elsevier, vol. 50(3), pages 695-736, April.
    4. Susan Athey & Guido Imbens, 2019. "Machine Learning Methods Economists Should Know About," Papers 1903.10075, arXiv.org.
    5. Bietenbeck, Jan, 2014. "Teaching practices and cognitive skills," Labour Economics, Elsevier, vol. 30(C), pages 143-153.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I29 - Health, Education, and Welfare - - Education - - - Other
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare

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