z-logo
open-access-imgOpen Access
Causal Modelling in Fertility Research: A Review of the Literature and an Application to a Parental Leave Policy Reform
Author(s) -
Michaela Kreyenfeld
Publication year - 2021
Publication title -
comparative population studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.419
H-Index - 15
eISSN - 1869-8999
pISSN - 1869-8980
DOI - 10.12765/cpos-2021-10
Subject(s) - identification (biology) , fertility , matching (statistics) , german , causal chain , regression discontinuity design , field (mathematics) , causality (physics) , life course approach , causal inference , empirical research , causal model , panel data , econometrics , positive economics , psychology , economics , population , sociology , developmental psychology , geography , demography , medicine , philosophy , mathematics , archaeology , pathology , biology , epistemology , quantum mechanics , botany , physics , pure mathematics
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”.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here