Causal Modelling in Fertility Research: A Review of the Literature and an Application to a Parental Leave Policy Reform

IF 1.5 Q2 DEMOGRAPHY
M. Kreyenfeld
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引用次数: 7

Abstract

This paper reviews empirical studies that have examined the causal determinants of fertility behaviour. In particular, we compare the approaches adopted in the different disciplines to improve our understanding of how birth dynamics are influenced by changes in female employment and changes in family policies. The wide array of panel data that have become available in recent years provide great potential for advanced causal modelling in this field. Event history modelling has been a dominant approach in sociology and demography. However, researchers are increasingly turning to other methods to unravel causal effects, such as fixed-effects modelling, the regression discontinuity approach, and statistical matching. We summarise selected studies, and discuss the advantages and the shortcomings of the different approaches. In an empirical section, we analyse the impact of the German 2007 policy reform on birth behaviour to illustrate the difficulties involved in isolating policy effects. The final chapter concludes by underscoring that even simple modelling strategies may be beneficial for improving our understanding of how policy effects shape demographic behaviour, and for laying the groundwork for more fine-grained causal investigations. * This article belongs to a special issue on “Identification of causal mechanisms in demographic research: The contribution of panel data”.
生育率研究中的因果模型:文献综述及其在育儿假政策改革中的应用
本文回顾了研究生育行为的因果决定因素的实证研究。特别是,我们比较了不同学科采用的方法,以提高我们对生育动态如何受到女性就业变化和家庭政策变化的影响的理解。近年来出现的大量面板数据为这一领域的高级因果模型提供了巨大的潜力。事件历史建模一直是社会学和人口学的主要方法。然而,研究人员越来越多地转向其他方法来揭示因果关系,如固定效应模型、回归不连续方法和统计匹配。我们总结了选定的研究,并讨论了不同方法的优点和缺点。在实证部分,我们分析了德国2007年政策改革对生育行为的影响,以说明孤立政策影响所涉及的困难。最后一章强调,即使是简单的建模策略,也可能有助于提高我们对政策影响如何塑造人口行为的理解,并为更细致的因果调查奠定基础。*本文属于“确定人口研究中的因果机制:面板数据的贡献”特刊。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.80
自引率
0.00%
发文量
15
审稿时长
26 weeks
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