Laboratory

Fertility and Well-Being

At a Glance Projects Publications Team

Project

Causal Inference Approaches to Fertility Over the Life Course

Jessica Nisén, Mathias Lerch, Maarten Jacob Bijlsma; in Collaboration with Ben Wilson (Stockholm University, Sweden), Johanna Tassot (Maastricht University, Netherlands)

Counterfactual causal inference, a subdiscipline of statistics that involves inferring causal effects from observational data, has made great conceptual and methodological progress in recent years. In this project, we apply the concepts and methods of counterfactual causal inference to the study of fertility.  Detailed Description

Publications

Nisén, J.; Bijlsma, M. J.; Martikainen, P.; Wilson, B.; Myrskylä, M.:

The gendered impacts of delayed parenthood: a dynamic analysis of young adulthood

Advances in Life Course Research 53:100496, 1–16. (2022)    

Bijlsma, M. J.; Wilson, B.:

Modelling the socio-economic determinants of fertility: a mediation analysis using the parametric g-formula

Journal of the Royal Statistical Society/A 183:2, 493–513. (2020)    

Nisén, J.; Bijlsma, M. J.; Martikainen, P.; Wilson, B.; Myrskylä, M.:

The gendered impacts of delayed parenthood on educational and labor market outcomes: a dynamic analysis of population-level effects over young adulthood

MPIDR Working Paper WP-2019-017. (2019)    

Bijlsma, M. J.; Wilson, B.:

Modelling the socio-economic determinants of fertility: a mediation analysis using the parametric g-formula

MPIDR Working Paper WP-2017-013. (2017)