Reforging the Wedding Ring: Exploring a Semi-Artificial Model of Population for the United Kingdom with Gaussian process emulators

Research Team: Jason Hilton

Note: Jakub Bijak from Social Science is the lead author on this project, which is forthcoming in Demographic Research (http://www.demographic-research.org/). Co-Authors: Eric Silverman, Viet Dung Cao

We extend the „Wedding Ring? agent-based model of marriage formation to include some empirical information on the natural population change for the United Kingdom together with behavioural explanations that drive the observed nuptiality trends. We propose a method to explore statistical properties of agent-based demographic models. By coupling rule-based explanations driving the agent-based model with observed data we wish to bring agent-based modelling and demographic analysis closer together. We utilise a Gaussian process emulator to analyse the impact of selected model parameters on two key model outputs: population size and share of married agents. A sensitivity analysis is attempted, aiming to assess the relative importance of different inputs. Given non-linearities in agent-based models such as the Wedding Ring, and the presence of feedback loops, the uncertainty of the model may not be directly computable by using traditional statistical methods. The use of statistical emulators offers a way forward.

Computational Modelling Group

Reforging the Wedding Ring: Exploring a Semi-Artificial Model of Population for the United Kingdom with Gaussian process emulators

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