Towards Bayesian Model-Based Demography: Agency, Complexity and Uncertainty in Migration Studies: 17 (Methodos Series) - Tapa blanda

Bijak, Jakub

 
9783030830410: Towards Bayesian Model-Based Demography: Agency, Complexity and Uncertainty in Migration Studies: 17 (Methodos Series)
Tapa blanda
ISBN 10: 3030830411 ISBN 13: 9783030830410
Editorial: Springer, 2021

Sinopsis

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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Acerca del autor

Jakub Bijak is Professor of Statistical Demography at the University of Southampton. He has background in economics (PhD 2008, Warsaw School of Economics) and over 20 years’ work experience in academia and international civil service. His research focuses on demographic uncertainty, population and migration models and forecasts, and the demography of armed conflict. He has been awarded the Allianz European Demographer Award (2015) and the Jerzy Z Holzer Medal (2007) for work on migration modelling. Leader of a European Research Council project “Bayesian agent-based population studies” (www.baps-project.eu), and a Horizon 2020 project “QuantMig: Quantifying Migration Scenarios for Better Policy” (www.quantmig.eu).

De la contraportada

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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Editorial
Springer
Año de publicación
2021
Idioma
Inglés
ISBN 10 
3030830411
ISBN 13 
9783030830410
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
292
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Otras ediciones populares con el mismo título

9783030830380: Towards Bayesian Model-Based Demography: Agency, Complexity and Uncertainty in Migration Studies: 17 (Methodos Series, 17)

Edición Destacada

ISBN 10:  3030830381 ISBN 13:  9783030830380
Editorial: Springer, 2022
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