Exploring the role of Residential Preference
in Segregation with Simulation
David W. Wong
dwong2@gmu.edu
A controversial issue in the study of segregation and
ethnic diversity is the role of various factors such as institutional, political,
socioeconomic and ethnic in creating or perpetuating the levels of racial
separation. One argument suggests that the segregation can simply be the
result of individual racial preferences on residential choice. Using a simulation,
Schelling examined the pattern of residential choice with very simple preference
rules. Clark empirically examined the racial preferences of multiethnic groups
in Los Angeles. Results of the study partially supported the importance of
racial preferences.
Previous studies, either using simulation or based upon
empirical data, were relatively weak in the modeling the spatial aspect of
the segregation in the context of racial preference. Schelling model does
not have an explicit spatial dimension and the rules were relatively simplistic.
Also, the evaluation of segregation level is limited to the use of traditional
aspatial measures, which are incapable to handle the so-called checkerboard
problem. This paper reports an effort to develop a simulation with explicit
geographical dimension in terms of the outcomes and in terms of the residential
choice. The model runs on real world data collected for any geographical
entity, and is built upon ArcView GIS. Major premises of the model are similar
to previous studies arguing that segregation could be an outcome of relatively
simple race-based residential preference and population characteristics of
the neighborhood can be a significant factor. To evaluate the level of spatial
segregation, a set of spatial segregation measures in addition to traditional
segregation will be used. Using Washington, DC as an example, this paper
demonstrates the operation of this model and presents some of the results.