Methodology, Dynamic microsimulation, Demography

Research articles · Dec 31, 2010

Validating a dynamic population microsimulation model: Recent experience in Australia

Ann Harding, Marcia Keegan, Simon Kelly

National Centre for Social and Economic Modelling (NATSEM), University of Canberra, Australia

Volume 3(2) Autumn 2010

Cite as: A. Harding, M. Keegan, S. Kelly; 2010; Validating a dynamic population microsimulation model: Recent experience in Australia; International Journal of Microsimulation; 3(2); 46–64. doi: 10.34196/ijm.00038

Abstract

Available published research on microsimulation tends to focus on the results of policy simulations rather than upon validation of the models and their outputs. Dynamic population microsimulation models, which age an entire population through time for some decades, create particular validation challenges. This article outlines some of the issues that arise when attempting to validate dynamic population models, including changing behaviour, the need to align results with other aggregate ‘official’ projections, data quality and useability. Drawing on recent experience with the construction of the new Australian Population and Policy Simulation Model (APPSIM), the article discusses the techniques being used to validate this new dynamic population microsimulation model.

This article contains 8 figures.

Figures

Figure 1. Output structure of a typical discrete time dynamic population microsimulation model.
Figure 2. Outline of the processes simulated in APPSIM/2010A.
Figure 3. Extract from APPSIM ‘everyone output’ for Year t.
Figure 4. Sample labour force output from APPSIM’s automatically generated summary statistics report.
Figure 5. Percentage of people who are retired, age 55–74, APPSIM and HILDA 2006, by age and sex.
Figure 6. Labour force states of men in 2047, APPSIM and treasury projections.
Figure 7. Labour force transitions in HILDA and APPSIM, 2004–2005.
Figure 8. Distribution of years spent in labour force by sex, 65–70 year olds in 2051.