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Towards Bayesian Model-Based Demography

Agency, Complexity and Uncertainty in Migration Studies

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  • Open Access
  • © 2022

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Overview

  • 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

Part of the book series: Methodos Series (METH, volume 17)

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About this book

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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Keywords

Table of contents (11 chapters)

  1. Preliminaries

  2. Elements of the Modelling Process

  3. Model Results, Applications, and Reflections

Reviews

“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)

Authors and Affiliations

  • Social Statistics & Demography, University of Southampton, Southampton, UK

    Jakub Bijak

About the author

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).

Bibliographic Information

  • Book Title: Towards Bayesian Model-Based Demography

  • Book Subtitle: Agency, Complexity and Uncertainty in Migration Studies

  • Authors: Jakub Bijak

  • Series Title: Methodos Series

  • DOI: https://doi.org/10.1007/978-3-030-83039-7

  • Publisher: Springer Cham

  • eBook Packages: Social Sciences, Social Sciences (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s) 2022

  • Hardcover ISBN: 978-3-030-83038-0Published: 10 December 2021

  • Softcover ISBN: 978-3-030-83041-0Published: 10 December 2021

  • eBook ISBN: 978-3-030-83039-7Published: 09 December 2021

  • Series ISSN: 1572-7750

  • Series E-ISSN: 2542-9892

  • Edition Number: 1

  • Number of Pages: XXV, 263

  • Number of Illustrations: 46 illustrations in colour

  • Topics: Demography, Statistics for Social Sciences, Humanities, Law, Migration

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