This technical brief analyses the relationship between immigrant status and educational expectations in PISA. Migration flows from outside and within the EU have increased in recent years, and this has raised the attention of policy makers and the general public, with special interests on the implications that those flows can have on, among other, the education system and the labour markets. At the same time, the EU has set the Europe 2020 headline target of reducing the share of early school leavers to 10 % within the EU.
Early school leavers become generally disadvantaged socially and economically in later stages in life, so that it is important to better understand the motivations for leaving school and provide adequate policy solutions. The European Commission (2016, p. 3) indicates that early school leavers are more likely to come from immigrant student groups, as their “early school leaving rates are nearly twice as high as for the native population”. Yet it also emphasises that there is still a lack of evidence pointing to the underlying reasons. In particular, it is not clear whether, among early school leavers, immigrants students are more frequent due to specific reasons related to the status of immigrants or whether they are more frequent because immigrant students are more likely to possess the set of characteristics that are normally associated to early school leaving behaviour (such as belonging to low socio economic status).
This study analyses the factors that are most strongly related to the probability to leave school early, putting special attention to immigrant status (by differentiating among first and second generation immigrants and, where possible, among EU and non-EU immigrants). To this end, we use OECD’s PISA data, which are the most widely employed data on international student assessment. Since early school leavers cannot directly be considered with these data, we focus on educational expectations, including the expectation to dropout early from school. As the related literature emphasises, these expectations are very closely linked to actually realised educational career patterns. Therefore, we can use expectations to gain insights on the factors influencing early school leaving. In addition, we also employ data from Eurostat to complement the picture on early school leavers and immigrants. First, we provide a range of descriptive data on immigrants and expected early school leavers. Second, we run a number of two-level logit regression models, including a range of student- and school-level variables. In particular, we consider all (available) EU Member States together, before providing results for each MS individually. Finally, we also distinguish more specifically between EU and non-EU immigrants in our regression models.
The results show that, when controlling for individual and school characteristics, immigrant students do not structurally differ in their expected early dropout probability from natives across Europe. In other words, the reasons why students expect to leave school early are the same for both immigrant students and natives. This finding implies that it is more important to focus on the common factors that are associated with expected early school leaving. In particular, our results suggest that these are, at the students’ level, the socio-economic background of students, their epistemological beliefs and grade repetition, while, at the school level, the most consistent factor is the school’s mean expected early school leavers rate. The school-environment thus appears to play a key role in shaping educational expectations. Among the student-related factors, grade repetition is the most amenable by policy, so that grade repetition practices may be reconsidered by national policy makers.