Causal analysis in population studies: concepts, methods, applications

Causal analysis in population studies: concepts, methods, applications

Engelhardt, H.
Kohler, H.
Fürnkranz-Prskawetz, A.

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The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the ‘causes ofeffects’ by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the ‘effects of causes’ in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible. In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships—i.e. relationships that can ultimately inform policies or interventions—is a complex undertaking. Estimation of causal relationships based on non-experimental data in population studies Comprehensive discussion of available techniques Contributions by the leading scholars in the field INDICE: From the contents 1: Causal analysis in population studies: H. Engelhardt, H.P. Kohler, A. Prskawetz.- 2: Issues in the estimation of causal effects in population research, with an application to the effects of teenage childbearing: R.A. Moffitt.- 3: Sequential potential outcome models to analyze the effects of fertility on labor market outcomes: M. Lechner.- 4: Structural modelling, exogeneity, and causality: M. Mouchart, F. Russo, G. Wunsch.- 5: Causation as a generative process. The elaboration of an idea for the social sciences and an application to an analysis of an interdependent dynamic social system: H.-P. Blossfeld.- 6: Instrumental variable estimation for duration date: G.E. Bijwaard.- 7: Female labour participation with concurrent demographic processes: an estimation for italy: G. De Santis, A. Di Pino.

  • ISBN: 978-1-4020-9966-3
  • Editorial: Springer
  • Encuadernacion: Cartoné
  • Páginas: 250
  • Fecha Publicación: 01/05/2009
  • Nº Volúmenes: 1
  • Idioma: Inglés