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Sample selectivity and the validity of international student achievement tests in economic research

Author

Listed:
  • Hanushek, Eric A.
  • Wößmann, Ludger

Abstract

Larger rates of exclusion, non-response, and age-specific enrollment are related to better country average scores on international student achievement tests. But accounting for sample selectivity does not alter existing evidence that academic achievement enters importantly in economic growth regressions. ; Sample selection International student achievement tests Economic growth

Suggested Citation

  • Hanushek, Eric A. & Wößmann, Ludger, 2011. "Sample selectivity and the validity of international student achievement tests in economic research," Munich Reprints in Economics 20401, University of Munich, Department of Economics.
    • Handle: RePEc:lmu:muenar:20401
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    Citations

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    Cited by:

    1. Ludger Woessmann, 2016. "The Importance of School Systems: Evidence from International Differences in Student Achievement," Journal of Economic Perspectives, American Economic Association, vol. 30(3), pages 3-32, Summer.
    2. Lyubov Babich & Aleksandra Shabunova & Galina Belekhova, 2017. "Economic Modernization, Human Capital and Smart-Learning Technology," MIC 2017: Managing the Global Economy; Proceedings of the Joint International Conference, Monastier di Treviso, Italy, 24–27 May 2017,, University of Primorska Press.
    3. Onil Boussim, 2023. "Correcting Sample Selection Bias in PISA Rankings," Papers 2309.10642, arXiv.org, revised Oct 2025.
    4. Hanushek, Eric A. & Woessmann, Ludger, 2011. "Sample selectivity and the validity of international student achievement tests in economic research," Economics Letters, Elsevier, vol. 110(2), pages 79-82, February.
    5. Jakubowski, Maciej & Pokropek, Artur, 2015. "Reading achievement progress across countries," International Journal of Educational Development, Elsevier, vol. 45(C), pages 77-88.
    6. Hendrik van Broekhuizen & Dieter von Fintel, 2010. "Who Responds to Voluntary Cognitive Tests in Household Surveys? The Role of Labour Market Status, Respondent Confidence, Motivation and a Culture of Learning in South Africa," Working Papers 27/2010, Stellenbosch University, Department of Economics.
    7. Muñoz, Juan Sebastián, 2018. "The economics behind the math gender gap: Colombian evidence on the role of sample selection," Journal of Development Economics, Elsevier, vol. 135(C), pages 368-391.
    8. Hanushek, Eric A. & Woessmann, Ludger, 2012. "Schooling, educational achievement, and the Latin American growth puzzle," Journal of Development Economics, Elsevier, vol. 99(2), pages 497-512.
    9. Kaarsen, Nicolai, 2014. "Cross-country differences in the quality of schooling," Journal of Development Economics, Elsevier, vol. 107(C), pages 215-224.
    10. Haizheng Li & Junzi He & Qinyi Liu & Barbara M. Fraumeni & Xiang Zheng, 2016. "Regional Distribution and Dynamics of Human Capital in China 1985-2014: Education, Urbanization, and Aging of the Population," NBER Working Papers 22906, National Bureau of Economic Research, Inc.
    11. Eric Hanushek & Ludger Woessmann, 2012. "Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation," Journal of Economic Growth, Springer, vol. 17(4), pages 267-321, December.
    12. Veruska Oppedisano & Gilberto Turati, 2015. "What are the causes of educational inequality and of its evolution over time in Europe? Evidence from PISA," Education Economics, Taylor & Francis Journals, vol. 23(1), pages 3-24, February.
    13. Jabrane Amaghouss & Aomar Ibourk, 2019. "Higher Education and Economic Growth: A Comparative Analysis of World Regions Trajectories," Economia Internazionale / International Economics, Camera di Commercio Industria Artigianato Agricoltura di Genova, vol. 72(3), pages 321-350.
    14. Balart, Pau & Oosterveen, Matthijs & Webbink, Dinand, 2018. "Test scores, noncognitive skills and economic growth," Economics of Education Review, Elsevier, vol. 63(C), pages 134-153.

    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • I20 - Health, Education, and Welfare - - Education - - - General
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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