书目名称 | Causal Analysis in Population Studies |
副标题 | Concepts, Methods, A |
编辑 | Henriette Engelhardt,Hans-Peter Kohler,Alexia Fürn |
视频video | |
概述 | 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 |
丛书名称 | The Springer Series on Demographic Methods and Population Analysis |
图书封面 |  |
描述 | .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 of effects’ 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. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had rece |
出版日期 | Book 2009 |
关键词 | Causal Analysis; Causal effects; Counterfactual Approach; Demographic Processes; Demography; Econometrics |
版次 | 1 |
doi | https://doi.org/10.1007/978-1-4020-9967-0 |
isbn_softcover | 978-90-481-8232-9 |
isbn_ebook | 978-1-4020-9967-0Series ISSN 1877-2560 Series E-ISSN 2215-1990 |
issn_series | 1877-2560 |
copyright | Springer Science+Business Media B.V. 2009 |