Objective Every individual is connected to a network of kin --- her/his family in the broad sense of that term --- that develops and changes as the individual ages. Family network affect demographic, economic, and health-related aspects of life and society. Despite its undeniable importance, remarkably little formal theory exists to show how kin dynamics are determined by mortality, fertility, and other variables. This project will develop a comprehensive mathematical model for kinship. It will be applicable to any kind of kin, in any population, based on any kind of age-classified or multistate structure. At the individual level, it will provide deterministic and stochastic properties of kin and kin characterstics, account for both dead and living kin, apply to age-, stage-, or multistate models, incorporate time variation, and include a general sensitivity analysis. At the cohort level, it will yield the means and variances of the lifetime experience of kin of any specified type. At the population level, the models will provide the distributions of kin characteristics, and the sources of their variance, as a function of population growth, and provide a link to population projections.The mathematical methods will be based on a novel development of coupled systems of subsidized matrix population models and their stochastic counterparts, on variance partitioning within and between ages, and on stochastic models with rewards. The use of matrix methods will provide results vastly exceeding any approximate or simulation procedures now in use, and be readily implemented in matrix-oriented stastical software. As a proof of concept and to search for patterns, exploratory analyses will be conducted using national and international life table and fertility data, model life tables, and detailed individual register data. A sequence of research workshops are planned to help communicate the results and develop new ideas and applications. Fields of science natural sciencescomputer and information sciencessoftwaresocial sciencessociologydemographymortalitysocial sciencessociologyfamily studiessocial sciencessociologydemographyfertilitynatural sciencesmathematicsapplied mathematicsmathematical model Keywords Formal demography population models mortality fertility multistate models Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2017-ADG - ERC Advanced Grant Call for proposal ERC-2017-ADG See other projects for this call Funding Scheme ERC-ADG - Advanced Grant Host institution UNIVERSITEIT VAN AMSTERDAM Net EU contribution € 1 232 861,00 Address SPUI 21 1012WX Amsterdam Netherlands See on map Region West-Nederland Noord-Holland Groot-Amsterdam Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 232 861,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all UNIVERSITEIT VAN AMSTERDAM Netherlands Net EU contribution € 1 232 861,00 Address SPUI 21 1012WX Amsterdam See on map Region West-Nederland Noord-Holland Groot-Amsterdam Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 1 232 861,00