Analysing Urban Systems using Agent-Based Modelling

This paper outlines the application of an agent-based model( ABM) within the context of urban systems. The model is developed with the goal of exploring residential market dynamics under various scenarios, and addresses two issues of concern to Australian urban systems, namely interest rates and population growth. Simulated agents are faced with the selection of a residence, and use market and non-market factors in decision making. From the field of discrete choice theory, a preference based utility calculation is linked to the attributes of properties, as provided from GIS data and populated from a variety of secondary literature sources. In a second decision making step, the affordability of residences is calculated based on prevailing interest rates, and compared to income based thresholds for housing expenditure. The model highlights the benefits of micro scale simulation in the ability to represent and report not only the average outcomes of policy impacts, but how the impacts are distributed within the society, addressing the issue of 'social gap'. Impacts of two sets of scenarios are examined, comparing different possible interest rate changes, and increases in population growth through immigration. It is shown that the ABM methodology is uniquely able to identify thresholds of change across varying scenarios, and offers particular value in the ability to communicate the distributive effects of impacts. A generic urban landscape and agent population is simulated using data from ABS, Brisbane DCDB and Sydney community profiles, with discussion on techniques and data sources to calibrate specific case studies.