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Influences on the Link Between Fertility Intentions and Behavioural Outcomes

Lessons from a European Comparative Study
  • Zsolt Spéder
  • Balázs Kapitány
Chapter

Abstract

This chapter aims to provide an insight into fertility decision making, concentrating in particular on links between fertility intentions and actual behaviour. Both the discussion of theoretical approaches and the empirical analysis enable us to gain a more accurate insight into the intention–behaviour link. After surveying the relevant literature, the chapter gives a broad overview of different kinds of factors that may contribute to the success or failure of the realisation of fertility intentions. The empirical section investigates the realisation of time-related positive fertility intentions using a comparative approach and exploiting the unique advantages of a longitudinal panel design. Four medium-sized European countries are compared, all with rather different fertility regimes, namely the Netherlands and Switzerland (Western), and Hungary and Bulgaria (post-Communist). Using four harmonised longitudinal panel surveys, a typology of fertility intentions and outcomes is constructed, and common patterns and country-specific factors are studied. By employing multinominal logistical regression models, factors influencing postponement, abandonment and realisation of childbearing intentions are uncovered. Our results indicate that in all four countries age, partnership status and education influence the realisation of fertility intentions in comparable ways; however, the specific effects of some of these factors differ. Our theoretical considerations and empirical results reveal aspects of the intention–behaviour link that could – to some extent – be easily accommodated to the TPB approach, but which also pose challenges to this theoretical framework.

Keywords

Ideational Factor Fertility Behaviour Fertility Intention Intention Realisation Partnership Status 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We are very thankful to the researchers of the REPRO project for providing useful feedback about an earlier draft of our paper.

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Hungarian Demographic Research InstituteBudapestHungary

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