Evaluating Student Performance: Unveiling the Impact of School’s Economic, Social, and Cultural Status with Regression Discontinuity

Assessing students’ skills is crucial for policymakers and educational stakeholders, as it reveals territorial and social inequalities. This study explores the impact of school socioeconomic composition on Italian students’ mathematics scores in the INVALSI tests, using a Regression Discontinuity (RD) design approach. RD is a statistical method used to estimate the causal e!ect of an intervention or treatment comparing outcomes just above and below a certain threshold of a certain predictor variable named running variable. In the presented case study, the outcome variable is the student’s mathematics scores, and the running variable is an index that describes the economic, social, and cultural status of the school. The study aims to assess how the socioeconomic composition of schools influences the academic performance of students in mathematics. Furthermore, we focus on the discrete nature of the running variable, an aspect that can introduce methodological challenges in estimating the causal e!ect. Specifically, we propose a new method for estimating average treatment e!ects in the case of a discrete running variable.