Promoting equity in education has become a continuous challenge during the past few decades. Beginning with the Coleman Report (1968) on equality of educational opportunities, ample work has shown that children's educational success is not only determined by individual ability and effort but by a myriad of factors outside of a student’s control. This includes factors such as socioeconomic status (SES), ethnicity, the school students attend, institutional and economic circumstances of the education system, among others (Chmielewski, 2019; European Commission/EACEA/Eurydice, 2020; Pfeffer, 2008). This is particularly concerning, as the purpose of education is to act as one of the key democratizing factors in society (European Commission/EACEA/Eurydice, 2020; Leuven et al., 2007).

Many education systems have implemented at least one major policy initiative to enhance equity in education (European Commission/EACEA/Eurydice, 2020). Despite consistent efforts from policy makers and researchers, social inequality persists in every education system in the world (Chmielewski, 2019). There are, however, striking differences between education systems in the degrees of educational inequity – especially in secondary education (European Commission/EACEA/Eurydice, 2020). As such, it is relevant to examine why some countries succeed in improving equity and others do not.

Students and schools are part of wider education systems (European Commission/EACEA/Eurydice, 2020), which have their own institutional features. These features (such as the governance, curriculum structure, standard practices, implemented policies, or traditions) impact in turn the degree of equity in an education system (Burger, 2016; European Commission/EACEA/Eurydice, 2020; Schlicht et al., 2010). While the importance of family background and school composition effects on performance is widely demonstrated and continues to exist, a pivotal question remains which systemic characteristics can moderate the effects of family background and school composition on achievement. Two of the most powerful dimensions, stratification and standardization, are acknowledged as important but have – to our knowledge – not been investigated at both school and student levels simultaneously, while also considering the interplay between them (Allmendinger, 1989).

Intrigued by the strong variation in equity levels between countries, combined with the abovementioned gaps in the literature, the aim of this paper is to gain a better insight into which systemic factors are associated with the socioeconomic student and school inequity in secondary education. A greater understanding of which system-level variables are correlated with the socioeconomic student or school inequity can help policy makers and researchers devise strategies for improving educational equity in different national contexts.

We specify three-level hierarchical linear models (standardized and non-standardized) to examine how system-level variables are correlated with the SES student and school inequity. Multicollinearity is checked upon with the tolerance and variance inflation factor values before running the analysis and does not constitute a problem in our model. We follow a stepwise procedure beginning with the null model (Model A) and variance components. Next, we build upon the model in an iterative fashion. In Model B, we add all control variables. The random slopes of student and school SES are specified in Model C. All system-level factors are added in Model D, after which cross-level interactions between our system-level variables and the SES student and school inequity are allowed (Model E). This study uses data from the 2018 PISA (Programme for International Student Assessment) study. Variables used in the analyses are created from the student or school questionnaire (by means of aggregating) or are borrowed from external sources (such as World Bank, Eurydice, UNDP and OECD). In general, we had 8 groups systemic variables in our analyses: (1-6) stratification variables (early tracking, between-school segregation, private schooling, school choice policies, grade repetition, admission policies), (7-8) standardization (central exams, autonomy). Our dependent variable is mathematics performance. Although students are also assessed on other areas, mathematics is considered as a suitable subject for cross-country comparisons (Burger, 2019). All plausible values are used in our models. We have two measures of equity: (1) socioeconomic student equity (measured by the correlation between students’ SES and mathematics performance), and (2) socioeconomic school equity (measured by the correlation between school SES and mathematics performance). To deal with the missing values, we imputed our data (only independent variables) before aggregating the variables three times for each country separately by ‘multiple imputation by chained equations’ (MICE). After the data imputation, we ended up with 237 datasets (79 countries*3 imputations), which we vertically merged to 3 datasets by imputation 1, 2, 3. In the final models, listwise deletion was used to exclude education system that had missing values on the systemic variables. Consequently, the sample of our analyses consists of 378,339 students, nested within 13,947 schools, nested within 49 education systems. The final analyses are run in Mplus 8.4. Senate weights on both student and school level are included.

In general, we can conclude that the effect-sizes of the correlations between student/school inequity and the system-level variables are relatively small, but the cumulative effect-size of several systemic factors can be substantial. Based on the descriptive evidence (the study provides associational, not experimental evidence) of this study we can highlight three key findings: (1) School SES is more strongly correlated with mathematics performance than student SES, indicating that it is a strong determinant of inequities between students and schools. Based on the fact that school SES has a stronger relationship with mathematics performance than school SES, policies aimed at reducing socioeconomic school inequity might be more effective tools to reduce, in general, inequity within an education system. (2) Education systems that are more stratified, are also characterized by higher degrees of socioeconomic inequity. On the one hand, we saw that the socioeconomic school inequity is higher in more stratified education systems, in which students are sorted in more homogeneous settings. We observe that the socioeconomic inequity is substantially smaller in education systems that track students at a later age, that have a high share of schools using area-based admission policies, and in education systems with little or private independent schools. The relationship between stratification variables and the socioeconomic student inequity is less clear. (3) Although based on our results central exams seem not to diminish inequity substantially, we did not control for possible moderating effect of central exams. It might be the case that central exams, ceteris paribus, do not considerable impact socioeconomic inequity, but that it does indirectly, by reducing the ‘impact’ of other stratification variables, is of great importance. This information is valuable towards policymakers, as it can be used as a tool to more efficiently develop, implement, or adapt educational policies.

Allmendinger, J. (1989). Career mobility dynamics: A comparative analysis of the United States, Norway, and West Germany. Max-Planck-Institut für Bildungsforschung. Burger, K. (2016). Intergenerational transmission of education in Europe: Do more comprehensive education systems reduce social gradients in student achievement? Research in Social Stratification and Mobility, 44, 54-67. Burger, K. (2019). The socio-spatial dimension of educational inequality: A comparative European analysis. Studies in Educational Evaluation, 62, 171-186. Chmielewski, A. K. (2019). The global increase in the socioeconomic achievement gap, 1964 to 2015. American Sociological Review, 84(3), 517-544. Coleman, J. (1968). The concept of equality of educational opportunity. Harvard educational review, 38(1), 7-22. European Commission/EACEA/Eurydice. (2020). Equity in school education in Europe: Structures, policies and student performance (Eurydice report, Issue. P. Office & o. t. E. Union. Leuven, E., Lindahl, M., Oosterbeek, H., & Webbink, D. (2007). The effect of extra funding for disadvantaged pupils on achievement. The Review of Economics and Statistics, 89(4), 721-736. Pfeffer, F. T. (2008). Persistent inequality in educational attainment and its institutional context. European sociological review, 24(5), 543-565. Schlicht, R., Stadelmann-Steffen, I., & Freitag, M. (2010). Educational inequality in the EU the effectiveness of the national education policy. European Union Politics, 11(1), 29–60. https://doi.org/10.1 177/1465116509346387.