Research on environmental (in)justice (EJ) confronts the issue of whether environmental harms (aka “disamenities”) are disproportionately placed in minority communities and, if so, what factors lead to this outcome. Some hypotheses are economics including income, racism, party politics (in one-party systems), and “the strength of local networks” (Aldrich, 2008, 145). The idea that network power might matter ties in with other concepts in the literature, such as Hamilton’s (1995) idea of the importance of collective action capacity in fending off unwanted land uses.

Kim, Eckerd, and Campbell—in various combinations—are pursuing an ongoing project using agent-based modeling (ABM) to explore the factors leading to minority-based environmental injustice. ABM is uniquely suited to the study of EJ. First, the complexity of the emergence of urban outcomes is not well suited to analysis by static methods. Second, because the studied behavior may be invidious (if, e.g., racism is a factor), survey methodologies are unlikely to be successful. Third, though of course models should return to empirics, in some cases the combinations of different factors necessary to fully understand independent impacts may not be readily observable. For example, to understand the independent effect of minority status and income status, we need to be able to study not only situations in which minorities are poorer, but in which minorities are richer, yet such empirical data can be rare in the US.

Three previous papers in this stream of research have been presented at APPAM’s annual research conferences (2010-2012). In order to explore the relationship between social capital, social networks, and EJ outcomes, the paper proposed for the 2013 conference will add social capital and network capacity to the ABM. Some scholars have argued that, rather than exercising a preference for racism, the rational firm locates in communities that are less likely to put up effective political resistance and mount successful NIMBY (Not In My Back Yard) campaigns. In the US context, they argue, these communities tend to be disproportionately minority. The proposed ABM will let us analyze this contention directly, looking at the effect of minority status alone and with and without social capital and social networks.

In operationalizing the model, we start from the Coleman (1988) view of the accumulation of social capital, arguing that social capital may be conceived of as a community “good” that can be expended. However, if higher status communities use social capital in NIMBY-like campaigns, this has impacts beyond to communities that do not have sufficient stocks of social capital. We also will gain insight from an ABM analysis by Abdollahian, Zining, and Nelson (forthcoming), which looks at social networks and their effects on the siting of high-tension power lines, but which does not examine EJ.

The presence of minority-based environmental injustice is a troubling policy problem. The use of ABM can help us explore many sets of causes, including emergent unintended ones. Understanding causes should help us develop more effective policies. In addition, ABM, with its ability graphically to represent complex phenomena, can communicate with policymakers.