Session Information
05 SES 08 A, Metrics and Equity
Paper Session
Contribution
Educational systems have effects on the intergenerational transmission of education (Breen and Jonsson 2005; van de Werfhorst and Mijs 2010). In particular, previous research has identified one central institutional factor as influencing the intergenerational transmission of educational advantage: between-school tracking, which increases educational inequalities (e.g., Canaan 2020). The extent to which tracking impacts educational inequalities depends on the age at between-school tracking (Brunello and Checchi 2007; Hanushek and Wößmann 2006; Pfeffer 2008). A later age at tracking in an education system reduces educational inequalities and increases intergenerational educational mobility (van de Werfhorst and Mijs 2010).
The most convincing empirical evidence in favor of causal effects of age at (first) tracking on intergenerational educational mobility comes from research estimating the effects of educational reforms in the age at tracking (e.g., van de Werfhorst 2018, 2019). This literature has implicitly assumed that the effects of such reforms do not vary across contexts. However, there are theoretical reasons to expect heterogeneity in the effects of reforms in the age at tracking on the intergenerational transmission of education by context.
In this study, we develop two expectations of such variation. First, the effects of the reforms may vary with the size of the change in the age at tracking. There may be reforms in the age at tracking, which are too incremental, to increase educational mobility. Contrary to this expectation, previous research has treated all countries which track students at an age younger than 15 as early tracking countries (e.g., Hanushek and Wößmann 2006; Scheeren 2022), and thereby ignored the considerable variation in terms of the size in the change of the age at educational selection within this group. It seems, however, at least theoretically possible that reforms in the age at tracking could increase educational mobility more if they shift the age at tracking by more than by less years.
Second, the effects of reforms in the age at tracking on educational mobility may be stronger in countries with stronger egalitarian values. In a climate of more egalitarian societal values there might be more possibilities for reforms to translate into actual outcomes for students and the intended equalizing effects of the reforms might more easily materialize in positive outcomes for students, especially for those from parents with lower levels of education. This hypothesis has been expressed by earlier research (van de Werfhorst 2018:32) but it has not been empirically tested.
The present study tests whether the effects of reforms in the age at tracking on educational mobility vary across countries. There are two kinds of previous studies on the consequences of tracking, neither of them allows us to answer this question. On the one hand, previous research has investigated the effects of reforms in tracking age in single country studies (e.g., Canaan 2020 on France and Dronkers 1993 on the Netherlands). These studies point towards positive implications of increasing the age at tracking and educational attainment (Canaan 2002; Dronkers 1993; Wielemans 1991). Variation in results across different studies can, however, be based on differences in the research design and the operationalization of variables. Yet, it is plausible that these differences are due to contextual differences. On the other hand, previous comparative research has analyzed multiple countries in difference-in-difference designs and therefore, by design, excluded the possibility of cross-country variation in the effects of reforms on educational mobility (Brunello and Checchi 2007; Hanushek and Wößmann 2006; van de Werfhorst 2018, 2019; Scheeren 2022).
In addition, we analyze gender differences in these effects. The investigation of gender differences is motivated by the inconclusive findings from previous studies.
Method
We use data from the European Social Survey (ESS) and the Survey of Health, Ageing and Retirement in Europe (SHARE). We use both data sources to increase the sample sizes. This is needed to improve the precision of our estimates. Whilst the ESS provides a sample which is representative for the adult population in each country, SHARE is representative of the population aged 50 years and older as well as their partners. Both data sets cover the countries with reforms included in our analysis and the cohorts that have been affected by the reforms. We use data from all waves of the survey data sets, which were available at the time of writing. This means we used waves 1 to 10 (2002–2020) from the ESS data and waves 1 to 8 (2004–2017) from SHARE. SHARE is a panel data set. However, on each respondent we only use the information once, and we always use the most recent information to measure educational attainment. We analyze the effects of reforms in age at tracking on educational mobility using a regression discontinuity design (RDD). We estimate OLS and linear probability regression models (LPMs).
Expected Outcomes
There are good theoretical reasons to believe that the effects of the reforms may vary across contexts. Yet, our results are in line with the implicit expectation of prior studies, which assume no cross-country variation in the effects of reforms in the age at tracking on educational mobility than with both our hypotheses. Neither the size of the increase in the age at tracking (hypothesis 1), nor the extent to which there are egalitarian values are prevailing in a society (hypothesis 2) impact the effect of an age increase in tracking on educational mobility. In fact, it is quite astonishing how robust the positive effects of reforms in the age at tracking are for fostering educational mobility. In all five countries, the reforms have clearly improved the educational attainment of children with low educated parents more than for children with medium and highly educated parents. Hence, the reforms have contributed to reducing educational inequalities. There are heterogeneities in the results across the three outcome variables. With respect to years of education there is an overall reduction in educational inequalities. The results for the other two dependent variables, upper-secondary education completion, and even more so higher education completion reveal fewer impacts of the reforms. This shows that the effects of the reforms are found rather at the lower than at the higher end of educational attainment, which are also the levels of education directly affected by the reforms. Finally, in most countries quite clearly the reforms in age at tracking have only affected the completion of upper secondary but not the completion of post-secondary education. This implies that there are no positive spillover effects of changing the age at tracking for tertiary education. In addition, our results with respect to gender are not in line with our theoretical expectations.
References
Allmendinger, Jutta. 1989. “Educational Systems and Labor Market Outcomes.” European Sociological Review 5:231–50. Bol, Thijs, and Herman G. van de Werfhorst. 2013. “Educational Systems and the Trade-Off between Labor Market Allocation and Equality of Educational Opportunity.” Comparative Education Review 57:285–308. Cunha, Flavio, and Heckman, James. 2007. “The Technology of Skill Formation.” American Economic Review 97:31–47. Brunello, Giorgio, and Daniele Checchi. 2007. “Does School Tracking Affect Equality of Opportunity? New International Evidence.” Economic Policy 22:781–861. d’Hombres, Beatrice, Francesca Borgonovi, and Bryony Hoskins. 2010. “Voter Turnout, Information Acquisition and Education: Evidence from 15 European Countries.” The BE Journal of Economic Analysis & Policy 10:1–34. DiPrete, Thomas A. and Buchmann, Claudia. 2013. The Rise of Women: The Growing Gender Gap in Education and What It Means for American Schools. New York: Russell Sage Foundation. Grätz, Michael. 2021. “Does Increasing the Minimum School-Leaving Age Affect the Intergenerational Transmission of Education? Evidence from Four European Countries.” European Sociological Review, DOI: 10.1093/esr/jcab065. Meghir, Costas, and Mårten Palme. 2005. “Educational Reform, Ability, and Family Background.” American Economic Review 95:414–24. Sammons, Pamela. 1995. “Gender, Ethnic and Socio‐Economic Differences in Attainment and Progress: A Longitudinal Analysis of Student Achievement over 9 years.” British Educational Research Journal 21:465–85. Scheeren, Lotte. 2022. “The Differential Impact of Educational Tracking on SES Gaps in Educational Achievement for Boys and Girls.” European Sociological Review, DOI:10.1093/esr/jcac012. Shavit, Yossi and Westerbeek, Karin. 1998. “Reforms, Expansion, and Equality of Opportunity.” European Sociological Review 14:33–47. Sørensen, Aage B. 1970. “Organizational Differentiation of Students and Educational Opportunity.” Sociology of Education 43:355–76. Österman, Marcus. 2021. “Can We Trust Education for Fostering Trust? Quasi-Experimental Evidence on the Effect of Education and Tracking on Social Trust.” Social Indicators Research 154:211–33. van de Werfhorst, Herman G. 2018. “Early Tracking and Socioeconomic Inequality in Academic Achievement: Studying Reforms in Nine Countries.” Research in Social Stratification and Mobility 58:22–32. van de Werfhorst, Herman G. 2019. “Early Tracking and Educational Social Inequality in Educational Attainment: Educational Reforms in 21 Countries.” American Journal of Education 126:65–99. van de Werfhorst, Herman G., and Jonathan J. B. Mijs. 2010. “Achievement Inequality and the Institutional Structure of Educational Systems: A Comparative Perspective.” Annual Review of Sociology 36:407–28.
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