The term socioeconomic status (SES) is a widely used variable to demonstrate the economic and social level of an individual or a group in society. SES is often defined by combining several components such as educational level, occupations, and family income (American Psychological Association, 2020). In addition to those components, The Organization for Economic Co-operation and Development (OECD, 2019) also includes the availability and number of essential home appliances for estimating SES. As SES levels of families start to differentiate in a society, the conditions that parents can create for the education and welfare of their children also become to vary.

In many countries, high-quality education standards are not affordable by all members of the population due to disparities in SES and several other variables. However, SES is probably one of the most important variables that explains such differences. Consequently, it leads to diversity in the outcome variables such as achievement levels of students all over the world. 

In one of the first studies about the SES, Coleman et al. (1966) found out that academic achievement had a stronger association with the social and ethnic composition of the students attending the school rather than with its resources and facilities provided. Jehangir et al. (2015) and Perry & McConney (2013) reported similar findings, too.

SES levels of the schools that students are enrolled to can also be considered as reliable predictors of the achievement. The school SES is defined based on the overall socioeconomic composition of a school and is estimated as an aggregated average of the students' individual SES attending the same school (Perry & McConney, 2010a). Research also shows that in many countries, students’ academic achievement is even more strongly associated with their schools’ SES than their family’s SES (Perry & McConney, 2010b; Sirin, 2005)

While research strongly indicates the presence of a relationship between school SES and academic achievement, much less is known about the interaction between students’ SES levels and achievement when school SES level is considered. Although studies focusing on school or student SES are present in the literature, the interaction between student and school-related SES has not been examined sufficiently. The potential interaction between these two variables needs further investigation. Differences between student and school SES levels may create a common effect that might explain students' educational achievements.

While examining school and student SES, a cross-cultural approach may help to get a clearer picture of the interaction. The interaction patterns between school and student SES may vary or stay constant across the countries, both of which can provide important findings. Additionally, identification of these insights can be helpful for countries to adapt their educational systems according to modern educational standards.

The purpose of this study is to investigate the possible interactions among school SES, individual SES and their effect on achievement in three different countries using PISA 2018 dataset. The analyses were conducted for reading, science, and mathematics literacy levels of students in a comparative manner across the countries. The analyzed data includes Estonia, Belarus, and Azerbaijan from PISA 2018 dataset. For Azerbaijan, the data was collected from the capital city, Baku only. The countries were selected based on their performance levels in PISA 2018 cycle.

Estonia, Belarus, and Azerbaijan were selected according to performance rankings in PISA 2018. These countries also shared a similar historical and educational background, which they were parts of Soviet Union until 1991. Some economical and educational characteristics of the selected countries are described in the following paragraphs below. Estonia was selected as a level 3 country for all domains of PISA, while Belarus was selected as level 2, and Azerbaijan was a level 1 country. Participants of this study included 5,316 Estonian, 5,803 Belarusian, and 6,827 Azerbaijani students from 230, 234, and 197 schools, respectively. For this study, performance scores of the literacy tests and variables derived from student questionnaires such as ESCS were used. Individual SES is already estimated by the ESCS index of PISA. Some of the students were removed from the initial data for missing ESCS values in the PISA dataset. School SES values were calculated as an aggregated average of students' SES values studying in particular schools. Schools represented by less than 5 students in the PISA dataset were removed from the sample for more reliable results. After calculating both individual and institutional SES scores, students were divided into quartiles for both SES variables, forming 16 comparison groups, for each domain and country separately, and cross-reference tables were formed accordingly. Students’ literacy variables were defined by plausible variables defined for each domain. Due to sampling technique used in PISA, use of single plausible variable or averaging them is not suggested. Instead, these plausible variables should be weighted. IDB Analyzer was used to weight the variables. For each country, a separate factorial ANOVAs were conducted to see differences between student and school SES groups in terms of mathematics, reading, and science literacy of students. Factorial ANOVA also provided information about interaction between student and school SES groups.

For Azerbaijan and Estonia largest point differences for all three domains were observed at the highest ESCS quartiles. However, for Belarus, the largest point differences for reading and science domains were observed at the 2nd ESCS quartile, while for mathematics, the largest difference belonged to the 1st ESCS quartile. Based on the comparisons among countries, it can be observed that the largest point differences were observed for Belarus (from 70 to 86 points), while the smallest gaps between literacy scores seemed to belong to the Azerbaijani sample (from 16 to 42 points). Since the Azerbaijan data was taken from the capital city, Baku only the smallest differences of literacy scores for Azerbaijan data could be explained. The overall performances of students in each country as well. It seems that Estonian students still can achieve level 3 performances for all PISA domains regardless of their individual SES levels. However, their Belarusian peers could only achieve level 3 performance if both their individual and school SES was high enough. In contrast, Azerbaijani students could achieve level 2 performance at maximum for all domains. Both individual and school SES levels played a more critical role related to literacy scores in Belarus rather than Estonia and Azerbaijan. Since the Estonian students could still achieve higher performance scores regardless of their individual SES levels, it seemed that the Estonian education system was creating more equal opportunities for students regardless of their socio-economic backgrounds. Lastly, Azerbaijani students could only achieve level 2 performance at maximum despite the increase at both SES quartiles. Although the differences in performance scores indicated that both individual and school SES plays important role in the performances of Azerbaijani students as well, the maximum level performance that Azerbaijani students can achieve shows that they are considerably behind their Belarusian and Estonian peers regardless of their individual SES levels.

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