Geography Courses Online

Despite a claim by Zhang (2004a) that he was the first to provide a rigorous model of the Schelling formulation (several presentations by Fossett [1998] predate his work), he does provide a mathematical interpretation of the agent-based simulation model. That interpretation shows that segregation, or as I prefer the neutral terminology of separation, is a stochastically stable state “that tends to emerge and persist in the long run regardless of the initial state” (Zhang 2004a). It is the finding in Zhang’s study that patterns of separation by race emerge, whatever the initial state, that confirms other studies that have investigated the mechanism of separation and its dynamic.

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The finding that separation can exist in the residential fabric even if most people prefer integrated neighborhoods is important because it explains the continuing patterns of separation even in a world that is increasingly tolerant and where society has made major attempts to eliminate discrimination in the housing market. Of course discrimination still occurs but we do not need to invoke discrimination to observe separate residential areas in our cities. ” Without any discriminatory behavior in the housing market a slight preference for like-color neighbors … can give rise to a high level of residential segregation and cause it to persist” (Zhang 2004b, p. 164). Asymmetrical preferences are an important element of understanding continuing separation.
While the work by Zhang has provided an initial mathematical explanation for the sorting patterns that we see, it is the simulation work of Fossett (2006) that provides the context and a richer link to an urban housing market with prices and actual mobility behavior and vacancies. (6) The SimSeg model provides substabtual evidence that his decade-long approach to the problem has taken us a major step forward in the process of understanding the way in which segregation comes about and provides a compelling spatial presentation of those processes.

Changing places and policy intervention
Place and mobility are increasingly the focus of policy concern. In particular, there is a concerted effort to understand the spatial concentration of poverty and by extension how we might redress the inner-city concentrations of poverty that are common in many central cities in the United States. The questions are natural extensions of the discussion in the previous section–questions about the separation of poverty populations and the role of neighborhoods in creating particular outcomes and whether mobility opportunities are a viable method for solving these problems.
Neighborhoods and communities have been reified as places of importance in a variety of socioeconomic outcomes. The question about neighborhood effects has generated a substantial and growing literature, which examines the additive marginal effects of neighborhoods on residential outcomes for inner-city poverty populations (Galster 2003). Additive, that is, in terms of explanatory power after controls for socioeconomic and demographic characteristics of the household. There is an increasingly divided approach whereby some suggest that where you live does matter–certainly an outcome that is consistent with much geographic literature on the role of place, but an equally strong position is that nearly all the outcomes are attributable to household composition.
Diez-Roux (2001) does a good job of identifying the problems of doing research that includes neighborhood measures. She notes the issues of neighborhood definition, the lack of distinctions between neighborhood and community, specifying the relevant neighborhood characteristics and the difficulty of distinguishing individual and neighborhood effects on any particular outcome. Significantly, for this paper she identifies geographic scale as a key issue in measuring environmental characteristics (Diez-Roux 2003). Not only is it reasonable to assume that different scales may be relevant for the study of different processes, or to put it differently some processes may operate at very local scales while others operate more broadly across larger environments. Clearly, blocks or groups of blocks are important for social interaction but service areas for health or even shopping may be relevant for other outcomes. People move to and through neighborhoods. Local and international flows change communities, especially their demographic composition. These changes in turn interact with school composition and issues of racial balance in schools. Interventions designed to produce particular outcomes may or may not succeed because of local urban dynamics. The research on mobility within the parameters of legal intervention provides a contested evaluation of the role of social science in predicting outcomes. Can we provide a solution to poverty by moving households from high-poverty to low-poverty areas? Will households who are enabled to move from innercity poverty neighborhoods to suburban low-poverty communities have better outcomes in employment, health, and education levels for the children of these families? At first thought the answer seemingly must be positive, of course a family moving from a high-poverty to a low-poverty area would be advantaged.
Within the context of the metropolitan change it becomes more difficult to be so sure about the outcomes of policy intervention. The moving to opportunity program of the Department of Housing and Urban Development (HUD) was designed as an experimental program to evaluate whether a special mobility program would increase the likelihood of innercity households moving to suburban and low-poverty neighborhoods (Clark 2005). However, well intentioned, such programs must be set within the content of changing metropolitan areas and the restless nature of American households. Cities change and people within cities make changes to bring their residential aspirations into adjustment with the available housing composition. Even when households are provided with incentives to locate in particular low-poverty neighborhoods, changes in their household and external opportunities can change their location choices overtime. Indeed, we find that many households that moved initially to low-poverty neighborhoods later relocate again and the outcome was to reduce the policy aim of having these households live in low-poverty neighborhoods. Why did this occur?
As in all such situations, the intervention is in a dynamic system, and despite the good intentions of the policy intervention, the combination of changing household composition, changing urban structures, and the pull of familiar neighborhoods can combine to undo the best policy plans. Policy is often formulated without a specific recognition of the dynamics of the urban structure, and the dynamics, unless modeled in the policy decision, may well undo the best plans. In addition, the plans are often formulated without a specific recognition of the spatial structure and its complexity. The combination of migration and a changing spatial structure is a context that makes intervention extremely difficult. Observations and the future of spatial science
Clearly, geographers are at the center of analytic questions about how society is organized and how it functions. In some sense it is ironic that this has occurred at a time that large sections of the discipline have moved away from analytic concerns to critical thinking and cultural studies. This essay suggests that the powerful contributions of spatial analysis are central to geography, and to the extent that we do not continue to engage in analytical statistical analysis, we will abandon these approaches to other disciplines anxious to bring space into their analytic traditions.
The emergence of a discourse, which focused on measurement and prediction, placed the discipline firmly within the discourse of science. Even though there may have been a proportional decline in the number of papers with “quantitative themes,” the research by Jackson et al. (2006) shows clearly that there continues to be a strong focus on geographical science. It is likely too that the cross-disciplinary embrace of CIS will continue to strengthen science in geography and geography outside the discipline.
Glscience will almost certainly play an important role in the evolution of spatial statistical analysis and is already important in incorporating spatial structure in models of spatial outcomes. Neighborhoods and communities are central to the organization of our cities and to our lives within them. We are often defined by where we live and our cities are divided by socioeconomic status and that division has a spatial pattern. It is that pattern which is summarized in neighborhoods, and among the questions now engaging investigators is whether the spatial unit matters over and above the composition of the households within the spatial unit. These are questions about neighborhood effects. What are the effects of living in particular neighborhoods after due controls for household composition, and how large are these neighborhood effects? These are questions that place scale and spatial structure at the heart of any statistical analysis and the identification of spatial outcomes in these models is intertwined with issues of statistical specification. It is here that the developing work in Glscience on spatial association is central ( Getis 1999; Anselin 2003).
The research on migration and sorting is an illustration of the powerful contributions that can be created within a rubric of geographical analysis. A continuing tradition of careful statistical modeling, recognizing the complexity of our social and physical world, will “grow” geography and our recognition in the social science community.

Notes

1. The selective references here are only exemplars of the huge and creative body of statistical analysis that grew rapidly at Washington, but also at Iowa and Northwestern and then with the diffusion of the new graduates, at Chicago and Ohio State.
2. The literature on residential mobility and migration is now substantial. This discussion is not designed to summarize that literature, rather the aim is to show the modeling process that has been a central part of creating the body of knowledge about migration and mobility and extensions to debates about migration in the policy arena. We must recognize too an increasing interest in the mirror image of mobility, the immobility of populations (Hanson 2005).
3. The code for a simple formulation (useful for classroom teaching) and a more complicated formulation of SimSeg is available on the Web.
4. Zhang’s model requires instantaneous swapping of agents, rather than the more realistic searching for vacancies.

References

Alberts, B. (2004) “A World that Banks on Science.” A Speech to the National Academy, April 19, 2004, Washington, DC.
Alberts, B. (2005) “Summing Up: Creating a Scientific Temper for the World.” A Speech to the National Academy, May 2, 2005, Washington, DC.
Anselin, L. (1988). Spatial Econometrics: Methods and Models, Dordrecht, The Netherlands: Kluwer Academic Publishers.
Anselin, L. (2003). GeoDa 0.9 Use Guide. Champaign Urbana, IL: Spatial Analysis Laboratory, University of Illinois.
Berry, B. J. L. (1961). “City Size Distributions and Economic Development.” Economic Development and Cultural Change 9, 573-88.
Berry, B. J. L. (1967). Geography of market Centers and Retail Distribution. Englewood Cliffs, NJ: Prentice Hall.
Boyle, P., T. J. Cooke, K. Halfacree, and D. Smith. (2001). “A Cross-National Comparison of the Impact of Family Migration on Women’s Employment Status.” Demography 38, 201-13.
(1981). “Toward a Development Paradigm of Migration with Particular Reference to Third World Settings.” In Migration Decision Making: Multidisciplinary Approaches to Micro-Level Studies in Developed and Developing Countries, 149-85, edited by G. DeJong and R. Gardener. New York: Pergamon Press.
(2004). “Neighborhood choice and neighborhood change.” On-Line Working Papers CCPR-00704, Center for Population Research, UCLA, Los Angeles.
Clark, W. A. V. (1986). “Residential Segregation in American Cities: A Review and Interpretation.” Papulation Research and Policy Review 5, 95-127.
Clark, W. A. V. (1989). “Residential Segregation in American Cities: Common Ground and Differences in Interpretation.” Population Research and Policy Review 8, 193-97.
Clark, W. A. V. (1991). “Residential Preferences and Neighborhood Racial Segregation: A Test of the Schelling Model.” Demography 28, 1-19.
Clark, W. A. V. (1992). “Residential Preferences and Residential Choices in a Multi-Ethnic Context.” Demography 30, 451-66.
Clark, W. A. V. (2002). “Ethnic Preferences and Ethnic Perceptions in Multi-Ethnic Settings.” Urban Geography 23, 237-56.
Clark, W. A. V. (2005). “Intervening in the Residential Mobility Process: Neighborhood Outcomes for Low-Income Populations.” Proceedings of the National Academy of Sciences USA 102, 15307-12.
Clark, W. A. V., and S. Davies Withers. (2002). “Disentangling the Interaction of Migration, Mobility and Labor Force Participation.” Environment and Planning A 34, 923-45.
Clark, W. A. V., and F. Dieleman. (1996). Households and Housing: Choice and Outcomes in the Housing Market. New Brunswick, NJ: Rutgers, The State University of New Jersey, Center for Urban Policy Research.
Clark, W. A. V., and M. Fossett. (2008). “Understanding the Social Context of the Schelling Segregation Model.” Proceedings of the National Academy of Sciences 105, 4109-114.
(2006). “Balancing Move and Work: Women’s Labor Market Exits and Entries after Family Migration.” Population Space and Place 12, 31-34.
(1996). “Family Migration and the Employment of Married Women and Men.” Economic Geography 72, 38-48.
Dacey, M. (1964). “Modified Poisson Probability Law for Point Pattern More Regular than Random.” Annals of the Association of American Geographers 54, 559-65.
Davies Withers, S., and W. A. V. Clark. (2006). “Expectations and Outcomes: The Geography of Family Migration.” Population, Space and Place 12, 273-89.
Dietz, R. (2002). “The Estimation of Neighborhood Effects in the Social Sciences: An Interdisciplinary Approach.” Social Science Research 31, 539-75.
Diez-Roux, A. (2001). “Investigating Neighborhood and Area Effects on Health.” American Journal of Public Health 91, 1783-89.
Diez-Roux, A. (2003). “Residential Environments and Cardiovascular Risk.” journal of Urban Health: Bulletin of the New York Academy of Medicine 80, 569-89.
Durlauf, S. (2004). “Neighborhood Effects.” In Handbook of Regional and Urban Economics, Vol. 4, 2173-242, edited by J. V. Henderson and J. F. Thisse. Amsterdam: Elsevier.
Forest, B. (2005). “The Changing Demographic, Legal and Technological Contexts of Political Representation.” Proceedings of the National Academy of Sciences USA 102, 15331-36.
Fossett, M. (1998). “SimSeg: A Computer Program to Simulate the Dynamics of Residential Segregation by Social and Ethnic Status.” Race and Ethnic Studies Institute Technical Report, Texas A and M University.
Fossett, M. (2006). “Ethnic Preferences, Social Distance Dynamics and Residential Segregation: Theoretical Explorations Using Simulation Analysis.” Journal of Mathematical Sociology 30, 185-273.
Fossett, M., and W. Warren. (2005). “Overlooked Implications of Ethnic Preferences for Residential Segregation in Agent Based Models.” Urban Studies 42, 1893-917.
(1991). “The Modifiable Areal Unit Problem in Multivariate Statistical Analysis.” Environment and Planning A 23, 1025-44.
Galster, G. (1988). “Residential Segregation in American Cities: A Contrary Review.” Population Research and Policy Review 7, 113-21.
Galster, G. (2003). “Investigating Behavioral Impacts of Poor Neighborhoods: Towards New Data an Analytic Strategies.” Housing Studies 18, 893-914.
Garrison, W. L. (1956). “Applicability of Statistical Inference to Geographical Research.” Geographical Review 46, 427-29.
(1959). Studies of Highway Development and Geographic Change. Seattle, WA: University of Washington Press.
Getis, A. (1999). “Spatial Statistics. Chapter 16.” In GIS: Principles, Techniques, Management, and Applications, 239-51, edited by P. Longley, M. Goodchild, D. Maguire, and D. Rhind. New York: Wiley.
(1976). Spatial Choice and Spatial Behavior. Columbus, OH: Ohio State University Press.
(1981). Dynamic Spatial Models. Alphen aan de Rijn, The Netherlands: Sijthoff and Noordhoff.
Haggett, P. (1965). Locational Analysis in Human Geography. London: St. Martins Press.
Hanson, S. (2005). “Perspectives on the Geographic Stability and Mobility of People in Cities.” Proceedings of the National Academy of Sciences USA 102, 15301-06.
Jackson, A., R. Harris, L. Hepple, A. Hoare, R.J. Johnston, K. Jones, and P. Plummer. (2006). “Geography’s Changeng Lexicon: Measuring Disciplinary Change in Anglophone Human Geography Through Journal Context Analysis.” Geoforum 37, 447-54.
Krugman, P. (1991). Geography and Trade. Cambridge, MA: MIT Press.
(2002). “The Residential Preferences of Blacks: Do They Explain Persistent Segregation?” Social Forces 80, 937-80.
Martin, R. (1999). “The New Geographical Turn in Economics: Some Critical Reflections.” Cambridge Journal of Economics 23, 65-91.
Moore, E. G. (1972) “Residential Mobility in the City.” Resource Paper No. 13, Commission on College Geography, Washington, DC.
Housing and Households in American Cities: Structure and Change in Population Mobility 1974-1982.” In Housing Demography, 203-31, edited by D. Myers. Madison, Wl: University of Wisconsin press.
(1981). “The modifiable unit problem.” In Quantitative Geography, 127-44, edited by N. Wrigley. London: Pion.
Schelling, T. (1971). “Dynamic Models of Segregation.” Journal of Mathematical Sociology 1, 143-86.
Schelling, T. (1978). Micromotives and Macrobehavior. New York: Norton.
Smits, J. (2001). “Career Migration Self-Selection and the Earnings of Married Men and Women in the Netherlands, 1981 1993.” Urban Studies 38, 541 62.
“Geographic Area and Map Projections.” Geographical Review 53, 59-78.
Zhang, J. (2004a). “Residential Segregation in an All-Integrationist World.” Journal of Economic Behavior and Organization 54, 533-50.
Zhang, J. (2004b). “A Dynamic Model of Residential Segregation.” Journal of Mathematical Sociology 28, 147-70.
Correspondence: Prof. William A.V. Clark, Department of Geography, 1255 Bunche Hall, University of California, Los Angeles, CA 90095