How data on school absenteeism and school attendance are registered, recorded and published varies greatly between countries. This makes it difficult to compare the situation and the trends concerning absenteeism between countries. If a comparison were to be made between the levels of absenteeism and the trends concerning them in different countries, it would be difficult to rely solely on national statistics; it would instead be necessary to either collect specific data in international surveys designed to do this, or explore whether other international studies contain this information. One way of comparing students´ absenteeism between countries could be to use data from the PISA studies. This presentation will explore how PISA-data can be used to make such comparisons. The presentation compares student absenteeism between Germany, Japan, Sweden and United Kingdom using data from the PISA-studies. In the PISA-studies students were asked about whether they had skipped school in the student questionnaires in 2000, 2012, 2015 and 2018. As the wording was partly different in 2000 than in the other years the data from 2012, 2015 and 2018 are used for the comparison. PISA data can be used to see the proportion of students who have indicated in the student questionnaire that they in the last two full weeks of school prior to their completion of the PISA student questionnaire had skipped at least a whole school day at one time. The students who have reported that they have been absent are compared with all the students in the countries in relation to their results on the PISA test (reading comprehension, mathematics and science) and on some background variables (gender, socio-economic background and migration background). PISA data can be used to analyse and compare school attendance in different countries and explore how different factors are related to school attendance and how this may differ between countries. By comparing and analysing school attendance in different countries it is possible to identify and discuss factors that influence school attendance and issues that may be of importance to advance school attendance. However, we also can see limitations and possibilities to interpret the differences in results only on the basis of the survey data alone are limited. That is where we suggest qualitative case studies to gain a more holistic understanding and for critically discussing the dynamic relations between education and health and wellbeing of school youth.

Avvisati, F. & Keslair, F. (2014). REPEST: Stata module to run estimations with weighted replicate samples and plausible values. Statistical Software Components S457918, Boston College Department of Economics, revised 06 Jan 2020 Kreitz-Sandberg, S., Backlund, Å., Fredriksson, U., Isaksson, J., Rasmusson, M. & Gren Landell, M. (2022) Understanding School Attendance Problems through Attendance Statistics: International Comparative Views on the Situation in Sweden, Germany, the UK (England), and Japan. Manuscript submitted for publication. OECD (2014a) PISA 2012 Results: Ready to Learn. Students’ Engagement, Drive and Self-beliefs. (Volume III). Paris: OECD OECD (2014b) PISA 2012 Results: What Makes Schools Successful? Resources, Policies and Practices (Volume IV). Paris: OECD OECD (2016) PISA 2015 Results: Policies and Practices for Successful schools (Volume II) Paris: OECD OECD (2019a) PISA 2018 Results: What Students Know and Can Do. Volume I. Paris: OECD OECD (2019b) PISA 2018 Results: Where All Students Can Succeed. Volume II. Paris: OECD OECD (2019c) PISA 2018 Results: What School Life Means for Students’ Lives. Volume III. Paris: OECD