000			02023nam a22002177a 4500
999			_c38068 _d38068
020			_a9783030830410
041			_aeng.
082			_a304.6 _bBIJ-T
100			_aBijak, Jakub _eauthor.
245			_aTowards Bayesian model-based demography : _bagency, complexity and uncertainty in migration studies / _cJakub Bijak ; with contributions by Philip A. Higham [and eight others].
260			_aCham : _bSpringer, _c2022.
300			_a263p.
504			_aIncludes bibliographical references and index.
520			_aThis 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.
546			_aEnglish.
650			_aDemography _xMethodology.
650			_aPopulation.
650			_aSocial sciences _xStatistical methods.
650			_aEmigration and immigration.
942			_2ddc _cBK