Exploring Italian students’ performances in the SNV test: a quantile regression perspective

Over the last decades, in educational studies, there is a growing interest in exploring the heterogeneous effects of educational predictors affecting students’ performances. For instance, the impact of gender gap, regional disparities and socio- economic background could be different for different levels of students’ ability, e.g. between low performing and high performing students. In this framework, quantile regression is an useful complement to standard analysis, as it offers a different per- spective to investigate educational data particularly interesting for researchers and policy makers. Through an analysis of data collected in the Italian annual survey on educational achievement carried out by INVALSI, this paper illustrates the added value of quantile regression to identify peculiar patterns of the relationship between predictors affecting performances at different level of students’ attainment.