distribution of the population with respect to environmental vulnerability and economic and social disadvantage
is an important part of the story. The poor are relegated to more vulnerable locations, which in turn expose them
to greater risks, which in turn make it difficult to accumulate the resources to improve economically, and so on.
Those who are better off are less vulnerable to begin with, and if disaster should strike, are in a better position to
respond, and possibly move on.
Disasters large and small have the potential to exacerbate inequalities at multiple levels. Little is known
about such dynamics, partly because they are not well suited to standard analytic approaches. The feedbacks
undermine the assumptions of multiple regression, especially that the disturbance is unrelated to the included
predictor variables. The usual “fixes,” for example the use of instrumental variables, do not work because of the
interconnectedness of the system. Instead, sociologists are turning to microsimulation approaches such as agent-
based modeling.
With these approaches, it is possible to examine the macro consequences of micro behavior, including
residential mobility and migration, and the integration of micro and macro processes more generally. Through the
use of “what-if” scenarios, it is possible to consider dynamic responses to climate change, including change that
has not yet happened, but might happen, or may never happen. Agent-based models can link people and place
by being made spatially explicit. In geography, for example, spatially explicit agent-based models have been
developed to describe land use change in a variety of settings (Parker et al. 2008). Sociologists are just beginning
to develop spatially explicit models, and this is an area rich with potential. Spatially explicit models of the
dynamics of social inequality in the face of locally experienced climate change are a natural focus for sociologists.
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