About the quality and sustainable education in European countries: a comparative econometric analysis

Abstract

This work examines the quality of education in European countries, analyzing its evolution towards the achievement of the Sustainable Development Goals (SDGs), in three different stages of efficiency: levels, patterns and determinants. The SDGs are a call to action for all countries to promote prosperity, while protecting the planet with determinant aspects in an equitable society, such as ensure inclusive and equitable quality education and promote lifelong learning opportunities for all (Goal 4), see [1]. The analysis is made under a non-parametric and deterministic model for measuring efficiency, based on DEA-CCR model, [2], in combination with other mathematical techniques important in the data analysis. In this context, two indicators are defined, one of them to calculate the accumulated effort of the decision units and the other one, to establish the most significant differences between groups with different levels of efficiency. The study is based on the EU's set of indicators to monitor progress towards the UN SDGs: basic education, tertiary education and adult learning. EU's set of indicators involves the participation in early childhood education; achievement in reading, mathematics or science; adult participation in learning; early leavers from education; tertiary education attainment and employment rates of recent graduates. With the aim of having a broader vision of the European educative performance, are considered two approaches. The approach (A1) considers five Eu set indicators, to examine 31 European countries during eleven years: 2006-2016. The approach (A2) considers the six Eu set indicators to examine 17 European countries during five non-consecutive years (2006, 2009, 2012, 2015, 2018). A comparative econometric analysis is carried out between approaches (A1) and (A2). This study aims to advance the analysis of strategies that allow us to identify the most efficient European countries in relation to performance factors; highlighting the improvements that could be applied to the less efficient ones, to increase their efficiency and achieve the objectives set for the year of 2030.