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Reforging the wedding ring: exploring a semi-artificial model of population for the United Kingdom with Gaussian process emulators

Reforging the wedding ring: exploring a semi-artificial model of population for the United Kingdom with Gaussian process emulators
Reforging the wedding ring: exploring a semi-artificial model of population for the United Kingdom with Gaussian process emulators
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 demographic 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 present a Semi-Artificial Model of Population, which aims to bridge demographic micro-simulation and agent-based traditions. We then utilise a Gaussian process emulator – a statistical model of the base model – 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. The resulting multi-state model of population dynamics has enhanced predictive capacity as compared to the original specification of the Wedding Ring, but there are some trade-offs between the outputs considered. The sensitivity analysis allows the identification of the most important parameters in the modelled marriage formation process. The proposed methods allow for generating coherent, multi-level agent-based scenarios aligned with some aspects of empirical demographic reality. Emulators permit a statistical analysis of their properties and help select plausible parameter values. Given non-linearities in agent-based models such as the Wedding Ring, and the presence of feedback loops, the uncertainty of the model cannot be assessed directly using traditional statistical methods. The use of statistical emulators offers a way forward
729-766
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Hilton, Jason
da31e515-1e34-4e9f-846d-633176bb3931
Silverman, Eric
641120a2-6584-46a6-a33b-4ea9133463af
Cao, Viet Dung
2d688630-bdf3-495b-8484-d88908d91f2f
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Hilton, Jason
da31e515-1e34-4e9f-846d-633176bb3931
Silverman, Eric
641120a2-6584-46a6-a33b-4ea9133463af
Cao, Viet Dung
2d688630-bdf3-495b-8484-d88908d91f2f

Bijak, Jakub, Hilton, Jason, Silverman, Eric and Cao, Viet Dung (2013) Reforging the wedding ring: exploring a semi-artificial model of population for the United Kingdom with Gaussian process emulators. Demographic Research, 29 (27), 729-766. (doi:10.4054/DemRes.2013.29.27).

Record type: Article

Abstract

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 demographic 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 present a Semi-Artificial Model of Population, which aims to bridge demographic micro-simulation and agent-based traditions. We then utilise a Gaussian process emulator – a statistical model of the base model – 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. The resulting multi-state model of population dynamics has enhanced predictive capacity as compared to the original specification of the Wedding Ring, but there are some trade-offs between the outputs considered. The sensitivity analysis allows the identification of the most important parameters in the modelled marriage formation process. The proposed methods allow for generating coherent, multi-level agent-based scenarios aligned with some aspects of empirical demographic reality. Emulators permit a statistical analysis of their properties and help select plausible parameter values. Given non-linearities in agent-based models such as the Wedding Ring, and the presence of feedback loops, the uncertainty of the model cannot be assessed directly using traditional statistical methods. The use of statistical emulators offers a way forward

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More information

Published date: 9 October 2013
Organisations: Social Statistics & Demography, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 359635
URI: http://eprints.soton.ac.uk/id/eprint/359635
PURE UUID: 0375f491-b619-4640-adc2-946b35970717
ORCID for Jakub Bijak: ORCID iD orcid.org/0000-0002-2563-5040
ORCID for Jason Hilton: ORCID iD orcid.org/0000-0001-9473-757X

Catalogue record

Date deposited: 07 Nov 2013 13:31
Last modified: 24 Sep 2019 00:42

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Contributors

Author: Jakub Bijak ORCID iD
Author: Jason Hilton ORCID iD
Author: Eric Silverman
Author: Viet Dung Cao

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