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

• 第一著者: Bijak, Jakub (auth)
• フォーマット: 電子媒体 図書の章
• 言語: 英語
• 出版事項: Bern Springer Nature 2022
• シリーズ: Methodos Series 17
• 主題: Population & demography; Social research & statistics; Migration, immigration & emigration; Open access; Agent-based modelling; Bayesian demography; Migration modelling; Model-based approaches; Uncertainty quantification; Forced migration; Computational experiments; Model calibration and sensitivity; Free access
• オンライン･アクセス: OAPEN Library: download the publication; OAPEN Library: description of the publication

要約

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.

物理的記述

1 electronic resource (263 p.)

ISBN

978-3-030-83039-7
9783030830397

アクセス

Open Access