Using simulated reproductive history data to re-think the relationship between 
education and fertility

Ciganda, Daniel; Lorenti, Angelo

doi:10.1007/978-3-030-34971-4_15

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Book Chapter

Using simulated reproductive history data to re-think the relationship between education and fertility

MPS-Authors

There are no MPG-Authors in the publication available

External Resource

Link
(Any fulltext)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Ciganda, D., & Lorenti, A. (2019). Using simulated reproductive history data to re-think the relationship between education and fertility. In I. Weber, K. M. Darwish, C. Wagner, E. Zagheni, L. Nelson, S. Aref, et al. (Eds.), Social Informatics 11th International Conference, SocInfo 2019, Doha, Qatar, November 18–21, 2019, Lecture Notes in Computer Science. (Lecture notes in computer science, pp. 218-238). Cham: Springer.

Cite as: https://hdl.handle.net/21.11116/0000-0006-B0F2-1

Abstract

The weakening negative educational gradient of fertility is usually interpreted as the expression of changes in the way education shapes reproductive decisions across cohorts. We argue, however, that the reversal of the statistical association does not imply a reversal in the underlying mechanisms that connect education and fertility. Instead, we believe the reversal in the statistical association emerges as a result of the convergence of the life-course of individuals with different educational attainment levels across two dimensions: the ability to control the reproductive process and the desire for a given family size. In order to show this we reproduce the results reported in previous studies by using simulated reproductive trajectories, generated from a model that assumes no change in the way education shapes reproductive intentions over time. Beyond our substantive focus, we intend to show how our understanding of key demographic processes could change if we were able to incorporate in our modeling difficult or impossible to observe quantities.