Jakub Bijak – författare

This unique book provides a practical and interdisciplinary blueprint for determining quantitative scenarios of future international migration. Focusing on complexity and uncertainty as the defining challenges of migration, it explores how scenario building can be used to inform and underpin effective migration policy and practice.Through conceptual, theoretical and methodological analysis, From Uncertainty to Policy: A Guide to Migration Scenarios outlines the current state of the art in future-oriented migration studies. Highlighting key lessons and recommendations, expert contributors assess both the opportunities and limitations of scenario building as an analytical device. They combine demographic, statistical, sociological, economic, geographic and political science expertise to develop a new multi-step process for estimating, predicting and simulating migration flows and patterns. Ultimately, the book emphasises the importance of accounting for uncertainty and complexity in migration policy and presents practical tools for accurately measuring and managing migration now and in the future.Advancing the methodology of setting migration scenarios under uncertainty, this book is an essential resource for migration practitioners, advisors and policy-makers and a valuable read for students and scholars of migration studies, geography and population sciences.

This unique book provides a practical and interdisciplinary blueprint for determining quantitative scenarios of future international migration. Focusing on complexity and uncertainty as the defining challenges of migration, it explores how scenario building can be used to inform and underpin effective migration policy and practice.

Through conceptual, theoretical and methodological analysis, From Uncertainty to Policy: A Guide to Migration Scenarios outlines the current state of the art in future-oriented migration studies. Highlighting key lessons and recommendations, expert contributors assess both the opportunities and limitations of scenario building as an analytical device. They combine demographic, statistical, sociological, economic, geographic and political science expertise to develop a new multi-step process for estimating, predicting and simulating migration flows and patterns. Ultimately, the book emphasises the importance of accounting for uncertainty and complexity in migration policy and presents practical tools for accurately measuring and managing migration now and in the future.

Advancing the methodology of setting migration scenarios under uncertainty, this book is an essential resource for migration practitioners, advisors and policy-makers and a valuable read for students and scholars of migration studies, geography and population sciences.

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.

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.

International migration is becoming an increasingly important element of contemporary demographic dynamics and yet, due to its high volatility, it remains the most unpredictable element of population change. In Europe, population forecasting is especially difficult because good-quality data on migration are lacking. There is a clear need for reliable methods of predicting migration since population forecasts are indispensable for rational decision making in many areas, including labour markets, social security or spatial planning and organisation. In addressing these issues, this book adopts a Bayesian statistical perspective, which allows for a formal incorporation of expert judgement, while describing uncertainty in a coherent and explicit manner. No prior knowledge of Bayesian statistics is assumed. The outcomes are discussed from the point of view of forecast users (decision makers), with the aim to show the relevance and usefulness of the presented methods in practical applications.

International migration is becoming an increasingly important element of contemporary demographic dynamics and yet, due to its high volatility, it remains the most unpredictable element of population change. In Europe, population forecasting is especially difficult because good-quality data on migration are lacking. There is a clear need for reliable methods of predicting migration since population forecasts are indispensable for rational decision making in many areas, including labour markets, social security or spatial planning and organisation. In addressing these issues, this book adopts a Bayesian statistical perspective, which allows for a formal incorporation of expert judgement, while describing uncertainty in a coherent and explicit manner. No prior knowledge of Bayesian statistics is assumed. The outcomes are discussed from the point of view of forecast users (decision makers), with the aim to show the relevance and usefulness of the presented methods in practical applications.