In the second half of the 20th century, scientific study of population changed its paradigm from the macro to the micro, so that attention focused mainly on individuals as the agents of demographic action. However, for accurate handling of all the complexities of human behaviours, the interactions between individuals and the context they belong to cannot be ignored. Therefore, in order to explain (or, at least, to understand) contemporary fertility and family dynamics, the gap between the micro and the macro should be bridged. In this contribution, we highlight two possible directions for bridging the gap: (1) integrating life-course analyses with the study of contextual characteristics, which is made possible by the emergence of the theory and tools of multi-level modelling; and (2) bringing the micro-level findings back to macro outcomes via meta-analytic techniques and agent-based computational models.
Methods for Reconciling the Micro and the Macro in Family Demography Research: A Systematisation / Anna Matysiak; Daniele Vignoli. - STAMPA. - (2012), pp. 475-484. [10.1007/978-3-642-21037-2]
Methods for Reconciling the Micro and the Macro in Family Demography Research: A Systematisation
VIGNOLI, DANIELE
2012
Abstract
In the second half of the 20th century, scientific study of population changed its paradigm from the macro to the micro, so that attention focused mainly on individuals as the agents of demographic action. However, for accurate handling of all the complexities of human behaviours, the interactions between individuals and the context they belong to cannot be ignored. Therefore, in order to explain (or, at least, to understand) contemporary fertility and family dynamics, the gap between the micro and the macro should be bridged. In this contribution, we highlight two possible directions for bridging the gap: (1) integrating life-course analyses with the study of contextual characteristics, which is made possible by the emergence of the theory and tools of multi-level modelling; and (2) bringing the micro-level findings back to macro outcomes via meta-analytic techniques and agent-based computational models.File | Dimensione | Formato | |
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