The relative age effect (RAE) concerns the fact that in most countries, school entry is defined by an age criterion whereby the oldest student entering the school is typically one year older than the youngest student. It is well known from the literature that the relatively older students performs better than the younger (e.g. Luyten, 2006; Martin, Mullis, & Foy, 2011; Ponzo & Scoppa, 2014; Sprietsma, 2008), but the degree to which the effect is modified throughout the course of primary and secondary school has not been extensively studied. Ponzo and Scoppa (2014) using data from PIRLS-2006, TIMSS-2007 and PISA 2009 is one example of a study showing that the effect declines as the pupils grow older. The degree to which this initial difference persists into later life is not entirely clear. On the one hand, Bedard and Dhuey (2006) find that relatively fewer individuals which at the start of their schooling were the youngest in their class, enter into tertiary education. Kawaguchi confirms this finding in a Japanese context, but on the other hand he also found that future income is not affected (2006). The same effect has been shown to exist in many sports, where the older individuals in each cohort appear to excel and have more success than the younger ones (Helsen et al., 2012; Helsen, van Winckel, & Williams, 2005; Mujika et al., 2009). Furthermore, RAE has also been studied for non-academic outcomes. Recent research for instance indicates that the relatively youngest adolescents have more emotional and peer problems than the oldest in the cohort (Patalay et al., 2015) but that the effect dissipates with age. However, the effects on emotional and mental health are more controversial (Lien, Tambs, Oppedal, Heyerdahl, & Bjertnes, 2005). 

The purpose of this study is to use the data from 20 years of international large-scale studies (ILSA) to replicate and add further details to these findings. Firstly, ILSA now represent a large number of studies across different subjects enabling us to study the robustness of the RAE within a system over studies, cycles and subjects. Furthermore, when seen together, the international studies represent different age groups, which make it possible to replicate and extend the study by Ponso and Scoppa (2014). And finally, internationally comparative data represent systems with a diversity of procedures for school entry and further tracking and streaming mechanisms which potentially could be a source for reducing or increasing RAE. However, these differences are also a source of confounding which needs to be explicitly addressed by careful selection of systems and studies to be included in the analysis (Cliffordson, 2010). Obviously, TIMSS & PIRLS have grade-based populations, making it hard to compare RAE over systems given that the age-distribution in a particular grade varies between countries, while PISA have age-based population where the observed RAE also will be confounded with number of years of schooling.

The following hypotheses guided the analyses:

H1: The RAE is expected to be reasonably robust over cycles for the same grades/subjects. The results are also expected to be reasonably robust across subjects for the same grade/study

H2: When comparing performance among students in adjacent grades, the variation in performance is related to both number of years in the school and to RAE.

H3: In a system were student cohorts are kept more or less unchanged over time RAE is gradually reduced as students are older, while in a system with substantial tracking/streaming such a reduction will not be observed

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