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Towards Bayesian Model-Based Demography Agency, Complexity and Uncertainty in Migration Studies /

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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 an...

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Bibliographic Details
Main Author: Bijak, Jakub (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2022.
Edition:1st ed. 2022.
Series:Methodos Series, Methodological Prospects in the Social Sciences, 17
Subjects:
Demography.
Population.
Social sciences > Statistical methods.
Emigration and immigration.
Population and Demography.
Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
Human Migration.
Online Access:Link to Metadata
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Table of Contents:
  • 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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