A method for emerging empirical age structures in agent-based models with exogenous survival probabilities

This work was inspired by a problem faced by policymaking users of agent-based models: how to generate the empirical age distribution in a model with a constant steady-state population. Traditional methods such as survival probability imputation do not work because the assumed statistical model used to estimate those probabilities differs from the agent-based one. Here, we develop a methodology to estimate the correct survival probabilities and generate a large variety of age distributions.

For many applications of agent-based models (ABMs), an agent’s age influences important decisions (e.g. their contribution to/withdrawal from pension funds, their level of risk aversion in decision-making, etc.) and outcomes in their life cycle (e.g. their susceptibility to disease). These considerations make it crucial to accurately capture the age distribution of the population being considered. Often, empirical survival probabilities cannot be used in ABMs to generate the observed age structure. This may be due to discrepancies between samples (e.g. when empirical survival probabilities are calculated across the whole population, but only a sub-population is being modelled) or models (between the survival model underpinning the ABM and the statistical model used to produce empirical survival probabilities). In these cases, imputing empirical survival probabilities will not generate the observed age structure of the population, and assumptions such as exogenous agent inflows are required (but not necessarily empirically valid). In this paper, we propose a method that allows for the preservation of agent age-structure without the exogenous influx of agents, even when only a subset of the population is being modelled. We demonstrate the flexibility and accuracy of our methodology by performing simulations of several real-world age distributions. This method is a useful tool for those developing ABMs across a broad range of applications.