SubsidieMeestersAdd in choice: optimizing students' dynamic and interdependent decisions
This project aims to develop a methodology using dynamic discrete choice models to analyze optimal educational choice provision, considering externalities and internalities across all education levels.
Projectdetails
Introduction
The diversity of educational opportunities has the potential to improve the situation of everyone by providing an environment adapted to the needs and goals of all. Letting parents or students choose their trajectory can improve welfare as it allows them to sort into the right program, using their private information on comparative advantages and preferences.
Externalities and Challenges
However, personal choices are not necessarily in line with society's objectives because of externalities. Apart from financial externalities that are inevitable in subsidized educational systems, peer effects are crucial in this context as the student composition of an educational program affects its quality.
Furthermore, from an individual perspective, the right choice is difficult to make, and behavioral biases (or internalities) are common. As a result, such choices are often restricted.
Restrictions on Choices
Targeted vouchers open up spots for some groups of children at the cost of others. Grading standards prevent students from attending certain tracks or courses in high school, and college admissions prevent completely free access. However, there is little guidance for policymakers in knowing and realizing the optimal size and composition of different options.
Key Questions
- What is the right balance between choice, ability, and diversity requirements in school choice and tracking?
- Are seats in college programs optimally provided according to society's needs?
- How to incentivize students to align their choices with a societal optimum?
Project Objective
This project aims to develop a methodology to empirically analyze the optimal provision of choice using novel dynamic discrete choice models that take into account externalities and internalities. The objective is to apply this methodology to rich micro-data from the three main levels of education:
- School competition in primary education
- Tracking in secondary education
- Admission and graduation in college
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 1.447.000 |
| Totale projectbegroting | € 1.447.000 |
Tijdlijn
| Startdatum | 1-3-2025 |
| Einddatum | 28-2-2030 |
| Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- FONDATION JEAN JACQUES LAFFONT,TOULOUSE SCIENCES ECONOMIQUESpenvoerder
- ECOLE D'ECONOMIE ET DE SCIENCES SOCIALES QUANTITATIVES DE TOULOUSE - TSE
Land(en)
Vergelijkbare projecten binnen European Research Council
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|---|---|---|---|---|
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Inequalities in decision-making at critical junctions in life: The role of ability signals for sorting and selection
The OPPORTUNITY project investigates how ability signals influence high-stakes decision-making and perpetuate socio-economic inequalities, aiming to inform policies that enhance equality of opportunity.
Market Design and Participation: Comprehensive Design for Matching Markets
The MADPART project aims to enhance assignment markets by analyzing the impact of outside options on participation and developing innovative designs using advanced theoretical and empirical methods.
UNEQUAL EDucation: The Role of Educational Constraints in Shaping Inequalities
Project UNEQUALED investigates educational constraints affecting human capital investment decisions using large-scale interventions to identify and quantify barriers to learning and opportunities.
Education policies that work: A context-sensitive ‘big data’ approach
EDUPOL conducts a comprehensive analysis of neoliberal and democratic educational policies' interplay to identify effective policy combinations for improving quality and equality in education.
Proportional Algorithms for Democratic Decisions
The project aims to develop algorithms ensuring proportionality in collective decision-making, enhancing fairness in various public scenarios through formal models and computational methods.