Project description
A geography of talent: Marriage, skills, and labour markets
Traditional studies often ignore how marriage and family responsibility influence where people choose to live and work. The ERC-funded SkiM2Lab project aims to redefine our understanding of how talent is distributed across the modern economy by examining the link between career paths and domestic life. To provide a more accurate picture, the study will shift from simple educational rankings to a multidimensional skill framework. By leveraging machine learning and large-scale data from online resumes, the project will map out how specific, granular abilities impact wage gaps and gender segregation. Ultimately, this work aims to identify emerging skills and their influence on productivity by building more sophisticated matching models.
Objective
The distribution of workers across jobs and across different geographic areas has major implications for growth, social welfare and inequality. It is complex but essential to understand the mechanisms behind the allocation of talents in the economy, that is, how skilled individuals choose their jobs and where they live.
However, the existing literature on the distribution of skills faces two major challenges. First, it has largely neglected the role of the marriage market and family constraints, although family formation and partner choice are intimately linked to career and location choices and these choices influence each other. Second, it must go beyond the standard one-dimensional classification of skills based on educational attainment alone. This hierarchy underestimates the inequalities that exist between multidimensional and non-hierarchical skill sets.
SkiM2Lab will address this challenge in developing state-of-the-art multidimensional matching models with two specific objectives.
In the first objective, I will analyze the interactions between the labor market and the marriage market using equilibrium models of matching where individuals and jobs are associated with multidimensional skill sets and are located in different places. Estimating these structural models on household data will reveal how family and labor markets affect wage disparities and occupational segregation by gender and region.
In the second objective, I will leverage big data such as online resumes and online job postings, as well as machine learning and natural language processing technologies, to extract skills at the most granular level, build new relevant combinations of skills and include them in a competitive matching model. This will make it possible to propose a new method to identify rapidly relevant emerging skills and their impact on wages and production.
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Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
91120 Palaiseau
France
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