An agent-based model of housing search and intraurban migration in the Twin Cities of Minnesota

Intraurban migration defines many neighbourhood dynamics and consequently impacts land use patterns in the long term. Housing location decision-making is a complex process involving many features of the housing market that interact with the perceptions of home searchers. Although modellers have paid much attention to the prices and utilities of the environmental, ecological, and public services associated with housing, the housing search process is neglected in many agent-based land use models involving urban housing market. The challenge of incorporating housing search partially lies in the prohibitive cost of identifying, recording, and quantifying housing search activities at a large scale. This paper presents an agent-based model of intraurban migration featuring straightforward yet empirically accurate rules for housing search. Drawing on intervening opportunity and intraurban migration theories, this model is specified and calibrated using real-world housing vacancies and relocation origin-destination pairs extracted from parcel records available in the Twin Cities for 2005 to 2007. Multiple validation methods, including inner migration rates, Syrjala tests, and minimum spanning tree comparisons, show that the search rules based on housing vacancy distribution and negative exponential distance-decay probability can satisfactorily simulate the pattern of the housing search and locational choices made by homeowners in the Twin Cities of Minnesota.