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

✍ Scribed by Jakub Bijak

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 277
• Series: Methodos Series, 17
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Foreword
Bayesian Epistemic Probability
Agent-Based or Model-Based Demography?
Conclusion
References
About the Authors
Lead Author
Contributors
Acknowledgements
Contents
List of Boxes
List of Figures
List of Tables
Part I: Preliminaries
Chapter 1: Introduction
1.1 Why Bayesian Model-Based Approaches for Studying Migration?
1.2 Aims and Scope of the Book
1.3 Structure of the Book
1.4 Intended Audience and Different Paths Through the Book
Chapter 2: Uncertainty and Complexity: Towards Model-Based Demography
2.1 Uncertainty and Complexity in Demography and Migration
2.2 High Uncertainty and Impact: Why Model Asylum Migration?
2.3 Shifting Paradigm: Description, Prediction, Explanation
2.4 Towards Micro-foundations in Migration Modelling
2.5 Philosophical Foundations: Inductive, Deductive and Abductive Approaches
2.6 Model-Based Demography as a Research Programme
Part II: Elements of the Modelling Process
Chapter 3: Principles and State of the Art of Agent-Based Migration Modelling
3.1 The Role of Models in Studying Complex Systems
3.1.1 What Can a Model Do?
3.1.2 Not ‘the Model of’, but ‘a Model to’
3.1.3 Complications
3.2 Complex Social Phenomena and Agent-Based Models
3.2.1 Modelling Migration
3.2.2 Uncertainty
3.3 Agent-Based Models of Migration: Introducing the Routes and Rumours Model
3.3.1 Research Questions
3.3.2 Space and Topology
3.3.3 Decision-Making Mechanisms
3.3.4 Social Interactions and Information Exchange
3.4 A Note on Model Implementation
3.5 Knowledge Gaps in Existing Migration Models
Chapter 4: Building a Knowledge Base for the Model
4.1 Key Conceptual Challenges of Measuring Asylum Migration and Its Drivers
4.2 Case Study: Syrian Asylum Migration to Europe 2011–19
4.3 Data Overview: Process and Context
4.3.1 Key Dimensions of Migration Data
4.3.2 Process-Related Data
4.3.3 Contextual Data
4.4 Quality Assessment Framework for Migration Data
4.4.1 Existing Frameworks
4.4.2 Proposed Dimensions of Data Assessment: Example of Syrian Asylum Migration
4.5 The Uses of Data in Simulation Modelling
4.6 Towards Better Migration Data: A General Reflection
Chapter 5: Uncertainty Quantification, Model Calibration and Sensitivity
5.1 Bayesian Uncertainty Quantification: Key Principles
5.2 Preliminaries of Statistical Experimental Design
5.3 Analysis of Experiments: Response Surfaces and Meta-Modelling
5.4 Uncertainty and Sensitivity Analysis
5.5 Bayesian Methods for Model Calibration
Chapter 6: The Boundaries of Cognition and Decision Making
6.1 The Role of Individual-Level Empirical Evidence in Agent-Based Models
6.2 Prospect Theory and Discrete Choice
6.3 Eliciting Subjective Probabilities
6.4 Conjoint Analysis of Migration Drivers
6.5 Design, Implementation, and Limitations of Psychological Experiments for Agent-Based Models
6.6 Immersive Decision Making in the Experimental Context
Chapter 7: Agent-Based Modelling and Simulation with Domain-Specific Languages
7.1 Introduction
7.2 Domain-Specific Languages for Modelling
7.2.1 Requirements
7.2.2 The Modelling Language for Linked Lives (ML3)
7.2.3 Discussion
7.3 Model Execution
7.3.1 Execution of ML3 Models
7.3.2 Discussion
7.4 Domain-Specific Languages for Simulation Experiments
7.4.1 Basics
7.4.2 Complex Experiments
7.4.3 Reproducibility
7.4.4 Related Work
7.4.5 Discussion
7.5 Managing the Model’s Context
7.6 Conclusion
Part III: Model Results, Applications, and Reflections
Chapter 8: Towards More Realistic Models
8.1 Integrating the Five Building Blocks of the Modelling Process
8.2 Risk and Rumours: Motivation and Model Description
8.3 Uncertainty, Sensitivity, and Areas for Data Collection
8.4 Risk and Rumours with Reality: Adding Empirical Calibration
8.5 Reflections on the Model Building and Implementation
Chapter 9: Bayesian Model-Based Approach: Impact on Science and Policy
9.1 Bayesian Model-Based Migration Studies: Evaluation and Perspectives
9.2 Advancing the Model-Based Agenda Across Scientific Disciplines
9.3 Policy Impact: Scenario Analysis, Foresight, Stress Testing, and Planning
9.3.1 Early Warnings and Stress Testing
9.3.2 Forecasting and Scenarios
9.3.3 Assessing Policy Interventions
9.4 Towards a Blueprint for Model-Based Policy and Decision Support
Chapter 10: Open Science, Replicability, and Transparency in Modelling
10.1 The Replication Crisis and Questionable Research Practices
10.2 Open Science and Improving Research Practices
10.3 Implications for Modellers
Chapter 11: Conclusions: Towards a Bayesian Modelling Process
11.1 Bayesian Model-Based Population Studies: Moving the Boundaries
11.2 Limitations and Lessons Learned: Barriers and Trade-Offs
11.3 Towards Model-Based Social Enquiries: The Way Forward
Appendices: Supporting Information
Appendix A. Architecture of the Migrant Route Formation Models
A1. Model Description
A2. Processes
A3. Illustration
Appendix B. Meta-Information on Data Sources on Syrian Migration into Europe
B1. Selected Key Sources of Data on Syrian Migration into Europe
B2. Supplementary General Sources on Migration Processes, Drivers or Features
Appendix C. Uncertainty and Sensitivity Analysis: Sample Output
Appendix D. Experiments: Design, Protocols, and Ethical Aspects
D.1. Prospect Theory and Discrete Choice Experiment
D.2. Eliciting Subjective Probabilities
D.3. Conjoint Analysis of Migration Drivers
Appendix E. Provenance Description of the Route Formation Models
Glossary
References
Index