The reasons behind the progression in PISA scores: An education production function approach using semi-parametric techniques

Research Masters

On December 2013, and for the fifth time since 2000, OECD published the results of the latest PISA survey, providing a view on how the students' performance has progressed during the last 12 years. Using PISA data we follow an education production function, which states that variables related to students, their family and the school explain the output, measured as the individual student achievement. Exploring the concept of efficiency we measure the ability that each student has to transform the given inputs into higher academic outcomes. Such analysis was performed through the estimation of an efficient frontier,derived by non-parametric techniques, namely Data Envelopment Analysis (DEA). Using this methodology we establish two vectors of analysis. The first one intends to disentangle the reasons behind the evolution in PISA scores across the years, concluding that the variation in inputs is on the core of the reasons to explain the evolution in PISA results. The second aims to evaluate what are the sources of student's efficiency. On this topic we particularly explore the role of the school inputs, concluding that students with a more favourable socio-economic background are more indifferent to variables such as class size and school size.