Towards Bayesian model-based demography : agency, complexity and uncertainty in migration studies / Jakub Bijak ; with contributions by Philip A. Higham [and eight others].
Bijak, Jakub, author.
2022
HB849.4 .B55 2022
Available Online

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Open access
Document Delivery Supplied
Open access

Details

Title
Towards Bayesian model-based demography : agency, complexity and uncertainty in migration studies / Jakub Bijak ; with contributions by Philip A. Higham [and eight others].
Author
Bijak, Jakub, author.
ISBN
9783030830397 (electronic bk.)
303083039X (electronic bk.)
9783030830380
DOI
https://doi.org/10.1007/978-3-030-83039-7
Published
Cham : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource (xxv, 263 pages) : color illustrations
Item Number
10.1007/978-3-030-83039-7 doi
Call Number
HB849.4 .B55 2022
Dewey Decimal Classification
304.6
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Open access
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed December 20, 2021).
Series
Methodos series ; v. 17.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
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.

Browse Subjects

Show more subjects...

Statistics

from
to
Export