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oapen-20.500.12657-51962
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oapen-20.500.12657-519622022-01-12T11:09:26Z Towards Bayesian Model-Based Demography Bijak, Jakub Open access Agent-based modelling Bayesian demography Migration modelling Model-based approaches Uncertainty quantification Forced migration Computational experiments Model calibration and sensitivity Free access bic Book Industry Communication::J Society & social sciences::JH Sociology & anthropology::JHB Sociology::JHBD Population & demography bic Book Industry Communication::J Society & social sciences::JH Sociology & anthropology::JHB Sociology::JHBC Social research & statistics bic Book Industry Communication::J Society & social sciences::JF Society & culture: general::JFF Social issues & processes::JFFN Migration, immigration & emigration This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration – one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly. 2021-12-13T18:55:53Z 2021-12-13T18:55:53Z 2022 book ONIX_20211213_9783030830397_36 9783030830397 https://library.oapen.org/handle/20.500.12657/51962 eng Methodos Series application/pdf n/a 978-3-030-83039-7.pdf https://link.springer.com/978-3-030-83039-7 Springer Nature Springer International Publishing 10.1007/978-3-030-83039-7 10.1007/978-3-030-83039-7 6c6992af-b843-4f46-859c-f6e9998e40d5 H2020 European Research Council 9783030830397 Springer International Publishing 17 263 Bern 725232 open access
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| institution |
OAPEN
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DSpace
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| language |
English
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| description |
This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. It offers a unique and novel methodology for creating empirically grounded agent-based models of international migration – one of the most uncertain population processes and a top-priority policy area. The book discusses in detail the process of building a simulation model of migration, based on a population of intelligent, cognitive agents, their networks and institutions, all interacting with one another. The proposed model-based approach integrates behavioural and social theory with formal modelling, by embedding the interdisciplinary modelling process within a wider inductive framework based on the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise innovative computer-based simulations, and to learn about modelling the simulated individuals and the way they make decisions. The identified knowledge gaps are subsequently filled with information from dedicated laboratory experiments on cognitive aspects of human decision-making under uncertainty. In this way, the models are built iteratively, from the bottom up, filling an important epistemological gap in migration studies, and social sciences more broadly.
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| title |
978-3-030-83039-7.pdf
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| spellingShingle |
978-3-030-83039-7.pdf
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| title_short |
978-3-030-83039-7.pdf
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| title_full |
978-3-030-83039-7.pdf
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| title_fullStr |
978-3-030-83039-7.pdf
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| title_full_unstemmed |
978-3-030-83039-7.pdf
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| title_sort |
978-3-030-83039-7.pdf
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| publisher |
Springer Nature
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| publishDate |
2021
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| url |
https://link.springer.com/978-3-030-83039-7
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| _version_ |
1771297389877919744
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