Project description
Investigating the education driven inequality
Through an interdisciplinary study, the EU-funded UNEQUALED project, seeks answers to insistent questions over learning and future life opportunity inequalities. The project mainly focuses on identifying and analyzing educational constraints, such as financial, technological, school organization and students’ socio-emotional barriers, in order to propose ways to leapfrog inequality. Starting from constraints’ quantification, the researcher team will then use big datasets to investigate the role of each identified barrier to determine its impact on student choices and educational attainments. UNEQUALED scope is set at national level in France, utilizing data from representative samples.
Objective
Project UNEQUALED aims to study educational constraints faced by individuals at a stage when they are planning their future investments in human capital. Despite its importance, understanding the determinants of educational choices has been a longstanding challenge for two important reasons. First, it requires broad, representative, data. Secondly, because the environment in which individuals’ educational plans are formed, and adjust, is typically endogenous to their characteristics. I will tackle these issues using large interventions on nationally representative samples of individuals.
Different parts of project UNEQUALED target specific questions that will help construct an overall picture. The project will seek to understand, and quantify, the role of the different barriers in leading to unequal learning and opportunities and the effects of easing the constraints. Specifically asking: Can the easing of technological constraints reduce learning inequality? What role does ICT access and training play for distance learning? Does differential social exposure within the classroom impact student outcomes? Can role models help an individual reach their goal? How important are psychological (or socio-emotional) barriers for achievement?
I will address each part using detailed micro longitudinal data, but at a macro level (large scale, nationally representative samples). I plan to combine economic concepts with field interventions, experiments and rich econometric and computer sciences tools to analyse big datasets and to causally estimate the impact of the components that drive the adjustment in educational plans, and, ultimately, how these factors into later educational outcomes. All projects will aim to capture the short and long-run impacts. To carry off this ambitious research project, I will work with a large and interdisciplinary network of researchers specializing in economics, statistics, computer science, management science, and public policy.
Fields of science
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
75341 Paris
France