Predicting Fertility (PreFer) data challenge

Single Wave Study

General Information

Title

Project Number

340

Abstract

The aim of the challenge is to measure current predictability of fertility outcomes in the Netherlands to advance our understanding of fertility. The PreFer data challenge focuses on the following task: for people aged 18-45 in 2020, predict who will have a(nother) child within the following three years (2021-2023) based on the data up to and including 2020. In the challenge, multiple research teams use two unique data sources to make predictions: the modules and waves from the longitudinal LISS Core Study representing a random representative sample of the Dutch population, and administrative data from Statistics Netherlands covering the entire Dutch population. Comparing and interpreting the models created in the challenge will help quantify the existing knowledge and gain insights.

More information can be found here: https://preferdatachallenge.nl

And at the PreFer GitHub repository: https://github.com/eyra/fertility-prediction-challenge

Longitudinal Type

Single Wave Study

Topics

Data

Health

Well-being (health)

Researcher

Gert Stulp (University of Groningen); Elizaveta Sivak (University of Groningen); Adriënne Mendrik (Eyra); Joris Mulder (Centerdata); Tom Emery (ODISSEI); Javier Garcia Bernardo (Utrecht University); Malvina Nissim (University of Groningen); Paulina Pankowska (VU Amsterdam)

Publisher

Centerdata

Funding Organization

NWO
ODISSEI
OCW (Domeinplan SSH)
Centerdata

DOI

https://doi.org/10.57990/f3ge-3a61

Publications

Combining the strengths of Dutch survey and register data in a data challenge to predict fertility (PreFer) Journal of Computational Social Science, 1-29; Sivak, E., et al.