The timing of abortions, births, and union dissolutions in Finland

Heini Vaisanen

doi:10.4054/DemRes.2017.37.28

Volume 37 - Article 28 | Pages 889–916

The timing of abortions, births, and union dissolutions in Finland

By Heini Vaisanen

Date received:

8 Mar 2017

Date published:

5 Oct 2017

Word count:

7054

Keywords:

fertility behavior, Finland, induced abortion, multiprocess model, registry data, union dissolution

DOI:

10.4054/DemRes.2017.37.28

Replicable Material:

demographic-research.37-28 (zip file, 2 kB)
readme.37-28 (text file, 936 Byte)

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Abstract

Background: People make fertility decisions within the wider context of their lives. Previous studies have shown that there are factors that drive both relationship transitions and childbearing decisions. However, there is a lack of research on whether these factors also drive abortion decisions and decisions to end a romantic relationship, and whether their effect depends on being in a cohabitating or marital union.

Objective: To study whether the factors that influence relationship transitions and childbearing decisions are also associated with abortion decision-making.

Methods: I analysed nationally representative register data of Finnish women born in 1965–1969 (N=17,666) using multi-level multi-process event history models.

Results: Women’s unobserved characteristics affected union dissolution, abortion, and childbearing decisions: Women with a tendency towards unstable relationships were more likely to have an abortion and less likely to give birth. The observed likelihood of abortion was lower for married than cohabiting women in the early years of a relationship, but became similar over time.

Conclusions: Characteristics such as personality and religiosity may partly explain these results. In line with previous research on other union characteristics, the likelihood of abortion in long-term cohabitation becomes similar to marriage over time.

Contribution: This study is the first to jointly estimate these three decision-making processes using reliable longitudinal data.