Project description
Studying the effects of bipartite networks on different markets
Modern markets are bipartite, involving two different agents. The ERC-funded MARNET project will explore the bipartite network models for marriage and labour markets. Specifically, the project will focus on two economic applications. The first is marriage formation and intra-household resources allocation. The second is wage dynamics and job mobility. The overall aim of the project is to improve our empirical knowledge of markets structured as bipartite networks by providing better statistical models of network formation and of the effects of the network structure on outcomes.
Objective
Research proposal MARNET aims at improving our empirical knowledge of markets structured as bipartite networks (all connections involve two different categories of agents) by providing better statistical models of network formation and the effects of the network structure on outcomes.
The use of random graphs, in which an edge between two nodes is the realization of a random draw, to model networked social, technological and biological systems has been subject to a novel and vigorous effort over the last twenty years. I will contribute to the knowledge corpus on networked economic systems with two separate research lines: first, in studying the interaction between social norms and marriage (monogamous and heterosexual); second, in studying how to improve models for linked employer-employee data.
The first research line aims at developing empirical models of marriage formation and intra-household resource allocation in order to better understand why different marriage markets (regions, countries, time periods) look different. My aim is to disentangle and quantify the sources of differentiation that relate to standard socio-economic variables, such as education and wages, from those that relate to culture and social norms. Various extensions will be considered to improve the design and realism of the model (aging and fertility, lots of heterogeneity, unobserved heterogeneity, housing and asset accumulation).
In the second research line, I will use recent advances in dynamic random graphs to model individual wage dynamics and the mobility of workers across firms. The main empirical objective is to quantify the degree of assortative matching of workers and firms in the labour market, and the relative contributions of worker and firm heterogeneity in wages. Several extensions will be considered (time-varying types, subjecting the network structure to pre-determined firm sizes, opening firm nodes by modelling wage dynamics and occupational mobility within firms).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences knowledge engineering
- social sciences sociology demography fertility
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
- networks
- bipartite graphs
- dynamic random graphs
- stochastic block models
- marriage markets
- social norms
- cultural identity
- within household resource allocation
- comparative study
- unobserved heterogeneity
- finite mixtures
- discrete mixtures
- hidden Markov models
- wage dynamics
- employment dynamics
- firm size
- linked employer-employee data
- matching
- wage dispersion
- sorting
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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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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.
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
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.
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.
ERC-ADG - Advanced Grant
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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-2020-ADG
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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.
75341 PARIS CEDEX 07
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.