“The material collected by Jakub Bijak and his team constitutes a valuable resource for scholars interested in modelling individual decisions, not necessarily restricted to migration processes. … Researchers who already gained some experience in social simulation will receive many inspirations for improving their own research and rise to the next level. In this way, this book has the potential to advance the art of modelling in the social sciences.” (Thomas Fent, European Journal of Population, Vol. 38, 2022)

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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This open access book presents a ground-breaking approach to developing micro-foundations for demography and migration studies. 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.
Les mer
Part I: Preliminaries: Chapter 1. Introduction.- Chapter 2. Uncertainty and complexity: towards model-based demography.- Part II: Elements of the modelling process.- Chapter 3. Principles and state of the art of agent-based migration modelling.- Chapter 4. Building a knowledge base for the model.- Chapter 5. Uncertainty quantification, model calibration and sensitivity.- Chapter 6. The boundaries of cognition and decision making.- Chapter 7. Agent-based modelling and simulation with domain-specific languages.- Part III: Model results, applications, and reflections.- Chapter 8. Towards more realistic models.- Chapter 9. Bayesian model-based approach: impact on science and policy.- Chapter 10. Open science, replicability, and transparency in modelling.- Chapter 11. Conclusions: towards a Bayesian modelling process.
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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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Presents a ground-breaking agent-based simulation model of migration Connects behavioural and social theory with modelling and statistics This book is available open access and free to read online Discusses the building of a simulation model of migration
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Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
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Produktdetaljer

ISBN
9783030830380
Publisert
2021-12-10
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, UP, 06, 05
Språk
Product language
Engelsk
Format
Product format
Innbundet

Forfatter

Om bidragsyterne

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).