Research proposal 'Understanding fertility outcomes by quantifying the (un)predictable' funded

Gert Stulp, assistant professor at University of Groningen, receives a NWO VIDI grant for his research proposal ‘Understanding fertility outcomes by quantifying the (un)predictable’. The aim of the project is to make better predictions about the number of children that people will have.

**Prediction is difficult**

How many houses should we build? Will the pension system still be sustainable in the future? And will there be enough medical care for everyone? The answers to these and other important policy questions are largely determined by how many children will be born in the future. However, this future birth rate proves to be quite difficult to predict. This is largely due to the fact that it is still rather unclear which factors determine reproductive behaviour. With his VIDI grant, Gert, together with two PhD students, hopes to gain more insight into this topic over the coming years, hopefully contributing to better predictions.

**Data challenge: How well can we predict fertility?**

One of the components of the VIDI project is a data challenge, an approach that has proven to be very successful within the data sciences, but is new within the social sciences. Gert: “Data challenges are competitions in which all participants work with the same dataset and try to make the best possible predictions about a certain outcome in another dataset. In my project, the challenge is to use the LISS panel, a dataset with more than a thousand variables, to predict the variation in the number of children that people will have.”

In principle anyone can join the data challenge, regardless of their location or discipline. Gert expects a mix of sociologists, demographers, and data scientists, and of both theory- and data -driven approaches. The model that explains the most variance in the number of children wins a prize: the winners are invited to give a key-note lecture at a specially organized conference.

**Simulations: What can we never predict?**

By using theory-driven simulations, Gert also hopes to gain more insight into the role of chance or randomness. “How many children people will have is partly determined by chance. Based on medical science we have a pretty good idea of the chance of conception and the chance that a fertilized egg will develop into a baby. Even if you have couples with the exact same characteristics, there could be a difference in their number of children because of this chance element. You can compare it to throwing a dice: sometimes you roll six in one go, while other times you need several throws. You cannot predict outcomes based on chance effects with a statistical model”.

**More insight into what we (do not) know**

By combining the insights of both projects, Gert hopes that at the end of the VIDI project he will have a better understanding of what we can and cannot predict. “The data challenge shows how much variation in the number of children we can explain based on variables that are already known. The simulation models give us more insight into the role of chance or randomness, or, in other words, the variation in the number of children that you cannot predict. If you know what you can predict and what you never will be able to predict, then what is left is what you have not yet predicted, but could possibly predict in the future, for example through new theories and better measurement.”