Funding

Our research lab is supported by multiple funding sources. Below is an overview of our key funded projects:

Add in choice: optimizing students’ dynamic and interdependent decisions (EDDYNCHOICE)

#

• Source: ERC
• Principal Investigator: Olivier De Groote
• Involved Members: Ana Maria Gazmuri, Maximilian Müller, Anaïs Fabre, Arnaud Maurel
• Funding Amount: €1,447,000
• Duration: 2025 - 2030

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. 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. 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. 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?

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, and admission and graduation in college.

Improving Early Horizontal Tracking: An RCT on Boosting Cooperative Decision-Making Between Parents and Children

#

• Source: UniCredit Foundation
• Principal Investigator: Lea Cassar, Christina Felfe de Ormeno and Maximilian Müller
• Funding Amount: €200,000
• Duration: 2024 - 2027

Announcement

Returns to Education: New Challenges for Models of Human Capital Investment (RECHC)

#

• Source: ANR
• Principal Investigator: François Poinas
• Involved Members: Olivier De Groote, Thierry Magnac, Gyung-Mo Kim
• Funding Amount: €273,888
• Duration: March 2021 – March 2025

In most advanced societies, improving skill supply to the labor market is on the policy agenda. This is justified both by the fact that skill accumulation fosters innovation, and by the fact that the adoption of new technologies modifies the set of skills needed in the labor market. One powerful way to affect skill supply is through education, as education is an essential input in the production of labor market productive skills. Understanding how individuals make their schooling decisions and how such decisions affect labor market outcomes (earnings, job mobility) is essential not only for the economist, but also for the policy maker who has to decide which policy gives the right incentives to invest in education.

The objective of this project is to improve the state-of-the art modeling strategies of educational and labor market decisions and adapt them to features that are particularly important in today’s context, in which different educational programs prepare for a diverse set of occupations and in which desired policies aim to improve the match between individual skills and interests. To this end, we will estimate dynamic structural human capital investment models in three different institutional contexts. This will allow us to learn about individual behavior and simulate policies that aim to improve the transitions within education, from education to the labor market, and between jobs.

A usual assumption made in standard human capital accumulation models is that individual unobserved characteristics (ability or preferences) are stable over time. This assumption does not capture well the possibility that preferences might evolve as the individual progresses into the educational system by acquiring more or less specialized skills. In a first project, we relax this assumption in the French context, where individuals specialize at different stages of their educational progression. Our model also introduces a way to deal with endogenous sample attrition, a feature widely encountered in longitudinal survey data and that can cause sample selection biases.

Another usual assumption is that individuals have perfect information about their own skills when they make their schooling decisions. In a second project, we relax this assumption and allow individuals to be overconfident about their (labor market) prospects in the South Korean context, characterized by a high college enrollment rate and a high unemployment rate among the educated.

In a third project, we extend the standard model by allowing for a large diversity of both educational options and job opportunities to study how the type of post-secondary education affects occupational choices and wages. This project is conducted in the German context, characterized by a large variety of post-secondary educational programs, including vocational-oriented programs tailored to specific occupations.

The Unequal Impact of Matching Students with Schools (MATCHINEQ)

#

• Source: ANR
• Principal Investigator: Olivier De Groote
• Involved Members: Ana Maria Gazmuri, Arnaud Maurel, Lisa Botbol, Anaïs Fabre, Juan Martin Pal, Guillem Foucault-i-Llopart
• Funding Amount: €249,225
• Duration: September 2022 – February 2025

School choice programs allow students (and their parents) to select a school of their preference in an attempt to improve access to high-quality education. As school capacities are limited, it is not possible to assign every student to their most preferred choice. Therefore, it is important to define a mechanism for student assignments. There is little evidence on the impact that these mechanisms have on equal access to quality education. The way in which they are implemented could hurt socially disadvantaged groups for several reasons. For example, it could reduce the options available for disadvantaged students if schools are able to select students. Moreover, misinformation about the rules, or limited resources to apply and hold out for the best options, could disproportionally harm students from low socioeconomic backgrounds. These are featured frequently across many different school choice settings without a clear understanding of the consequences in terms of educational outcomes and inequality.

Our team proposes a project in which we will analyze education programs that aim to improve outcomes among the socially disadvantaged. We will study how the characteristics of the allocation system impact educational outcomes for different socioeconomic groups both in compulsory and higher education. We will use and extend structural econometric models to study student behavior, which will allow us to study some of the determinants of social inequality and to simulate outcomes under alternative matching policies.