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The reasons behind the progression in PISA scores: an education production function approach using semi-parametric techniques
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Resumo(s)
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.
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Palavras-chave
Education production function Efficiency Data envelopment analysis PISA