Fertility progression in Germany: An analysis using flexible nonparametric cure survival models

Vincent Bremhorst; Michaela Kreyenfeld; Philippe Lambert

doi:10.4054/DemRes.2016.35.18

Volume 35 - Article 18 | Pages 505–534

Fertility progression in Germany: An analysis using flexible nonparametric cure survival models

By Vincent Bremhorst, Michaela Kreyenfeld, Philippe Lambert

Date received:

5 Jan 2016

Date published:

26 Aug 2016

Word count:

9920

Keywords:

cure survival models, fertility, Germany, parity progression, quantum, timing

DOI:

10.4054/DemRes.2016.35.18

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Abstract

Objective: This paper uses data from the German Socio-Economic Panel (GSOEP) to study the transition to second and third births. In particular, we seek to distinguish the factors that determine the timing of fertility from the factors that influence ultimate parity progression.

Methods: We employ cure survival models, a technique commonly used in epidemiological studies and in the statistical literature but only rarely applied to fertility research.

Results: We find that education has a different impact on the timing and the ultimate probability of having a second and a third birth. Furthermore, we show that the shape of the fertility schedule for the total population differs from that of ‘susceptible women’ (i.e., those who have a second or a third child).

Conclusions: Standard event history models conflate timing and quantum effects. Our approach overcomes this shortcoming. It estimates separate parameters for the hazard rate of having a next child for the ‘susceptible population’ and the ultimate probability of having another child for the entire population at risk.

Contribution: We go beyond standard cure survival models, also known as split population models, used in fertility research by specifying a flexible non-parametric model using Bayesian P-splines for the latent distribution (related to the timing of an extra birth) instead of a parametric model. Our approach is, so far, limited to time-constant covariates, but can be extended to include time-varying covariates as well.