English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
 Local TagsRelease HistoryDetailsSummary
  Using simulated reproductive history data to re-think the relationship between education and fertility

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.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-0006-B0F2-1 Version Permalink: https://hdl.handle.net/21.11116/0000-0006-B314-9
Genre: Book Chapter

Files

show Files

Locators

show
hide
Locator:
Link (Any fulltext)
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Ciganda, Daniel1, Author
Lorenti, Angelo1, Author
Affiliations:
1Max Planck Institute for Demographic Research, ou_3148316              

Content

show
hide
Free keywords: -
 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.

Details

show
hide
Language(s):
 Dates: 2019
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: Other: 6434
DOI: 10.1007/978-3-030-34971-4_15
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Social Informatics 11th International Conference, SocInfo 2019, Doha, Qatar, November 18–21, 2019, Lecture Notes in Computer Science.
Source Genre: Book
 Creator(s):
Weber, Ingmar, Editor
Darwish, Kareem M. , Editor
Wagner, Claudia, Editor
Zagheni, Emilio1, Editor
Nelson, Laura, Editor
Aref, Samin 1, Editor
Flöck, Fabian, Editor
Affiliations:
1 Max Planck Institute for Demographic Research, ou_3148316            
Publ. Info: Cham : Springer, Lecture notes in computer science
Pages: - Volume / Issue: (11864) Sequence Number: - Start / End Page: 218 - 238 Identifier: ISBN: 978-3-030-34970-7
ISBN: 978-3-030-34971-4