, Volume 81, Issue 4, pp 625–640 | Cite as

The geography of opportunity: an exploratory spatial data analysis of U.S. counties

  • Bev WilsonEmail author
  • Andrew J. Greenlee


Rising inequality and the lingering effects of the most recent economic recession continue to engender negative perceptions of access to opportunity in the United States. While prior research has established the importance of geography in understanding opportunity in metropolitan areas, little attention has been given to the spatial distribution of opportunity outside urban areas or its temporal variation. This article builds on existing frameworks for measuring opportunity to calculate a multidimensional opportunity index for counties in the lower 48 states and the District of Columbia for the years 2000 and 2010. We use exploratory spatial data analysis techniques to map and critically examine the geography of opportunity at both time periods across regions and three distinct county typologies with an emphasis on identifying clusters of high and low opportunity. We find that opportunity decreased on average for all counties from 2000 to 2010 as did its standard deviation, consistent with arguments that opportunity in the U.S. has both declined and converged. While the opportunity index remains highest in metropolitan and urban counties, nonmetropolitan and rural areas fared well with respect to the spatial clustering of high opportunity counties. Clusters of high opportunity counties shifted from the Northeast to Midwest regions, while clusters of low opportunity counties in traditional strongholds of persistent poverty like Appalachia, the Mississippi Delta, and Lower Rio Grande Valley have become more fragmented.


ESDA Opportunity Regional analysis Spatial inequality 


Conflict of interest

The authors declare that they have no conflict of interest.


  1. Alvaredo, F., Atkinson, A. B., Piketty, T., & Saez, E. (2013). The top 1 percent in international and historical perspective. Journal of Economic Perspectives, 27(3), 3–20.CrossRefGoogle Scholar
  2. Anselin, L. (1988). Spatial econometrics: Methods and models. Dordrecht: Kluwer Academic Publishers.CrossRefGoogle Scholar
  3. Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115.CrossRefGoogle Scholar
  4. Anselin, L. (1996). The Moran scatterplot as an ESDA tool to assess local instability in spatial association. In M. M. Fischer, H. J. Scholten, & D. J. Unwin (Eds.), Spatial analytical perspectives on GIS (pp. 111–125). London: Taylor & Francis.Google Scholar
  5. Anselin, L., & Getis, A. (2010). Spatial statistical analysis and geographic information systems. In L. Anselin & S. J. Rey (Eds.), Perspectives on spatial data analysis (pp. 35–47). Berlin: Springer.CrossRefGoogle Scholar
  6. Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis. Essex: Longman Scientific & Technical.Google Scholar
  7. Bivand, R. S. (2010). Exploratory spatial data analysis. In M. M. Fischer & A. Getis (Eds.), Handbook of applied spatial analysis (pp. 219–254). Berlin: Springer.CrossRefGoogle Scholar
  8. Bivand, R., Altman, M., Anselin, L., Assunção, R., et al. (2014). spdep: Spatial dependence: Weighting schemes, statistics and models. R package version 0.5-74.Google Scholar
  9. Blanden, J., Gregg, P., & Machin, S. (2005). Intergenerational mobility in Europe and North America. London: Sutton Trust, Centre for Economic Performance, London School of Economics.Google Scholar
  10. Blau, J. R., & Blau, P. M. (1982). The cost of inequality: Metropolitan structure and violent crime. American Sociological Review, 47(1), 114–129.CrossRefGoogle Scholar
  11. Chetty, R., Hendren, N., Kline, P., & Saez, E. (2013). The equality of opportunity project. Retrieved February 10, 2014, from
  12. Cliff, A. D., & Ord, J. K. (1981). Spatial processes: Models & applications. London: Pion.Google Scholar
  13. Corak, M. (2013). Income inequality, equality of opportunity, and intergenerational mobility. Journal of Economic Perspectives, 27(3), 79–102.CrossRefGoogle Scholar
  14. Curtis, K. J., Voss, P. R., & Long, D. D. (2012). Spatial variation in poverty-generating processes: Child poverty in the United States. Social Science Research, 41(1), 146–159.CrossRefGoogle Scholar
  15. Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social vulnerability to environmental hazards. Social Science Quarterly, 84(2), 242–261.CrossRefGoogle Scholar
  16. Danziger, S., Chavez, K., & Cumberworth, E. (2012). Poverty and the great recession. Stanford, CA: Stanford Center on Poverty and Inequality.Google Scholar
  17. de Souza Briggs, X. N. (2005). The geography of opportunity. Washington, DC: Brookings Institution.Google Scholar
  18. Dunne, T. (2012). Household formation and the Great Recession. Cleveland, OH: Federal Reserve Bank of Cleveland.Google Scholar
  19. ERS. (2004). Rural–urban continuum codes. Washington, DC: U.S. Department of Agriculture, Economic Research Service. Retrieved November 2013, from
  20. Ewing, R., Pendall, R., & Chen, D. (2002). Measuring sprawl and its impact. Washington, DC: Smart Growth America.Google Scholar
  21. Galster, G. C., & Killen, S. P. (1995). The geography of metropolitan opportunity: A reconnaissance and conceptual framework. Housing Policy Debate, 6(1), 7–43.Google Scholar
  22. Gasteyer, S., & Carrera, J. (2013). The coal-corn divide: Colliding treadmills in rural community energy development. Rural Sociology, 78(3), 290–317.CrossRefGoogle Scholar
  23. Getis, A. (2008). A history of the concept of spatial autocorrelation: A geographer’s perspective. Geographical Analysis, 40(3), 297–309.CrossRefGoogle Scholar
  24. Getis, A. (2009). Spatial weights matrices. Geographical Analysis, 41(4), 404–410.CrossRefGoogle Scholar
  25. Goodman, C. J., & Mance, S. M. (2011). Employment loss and the 2007–09 recession: An overview. Monthly Labor Review, 134(4), 3–12.Google Scholar
  26. Greenwood, M. J., Hunt, G. L., Rickman, D. S., & Treyz, G. I. (1991). Migration, regional equilibrium, and the estimation of compensating differentials. American Economic Review, 81(5), 1382–1390.Google Scholar
  27. Griffith, D. A. (1992). What is spatial autocorrelation? Reflections on the past 25 years of spatial statistics. Espace Géographique, 21(3), 265–280.CrossRefGoogle Scholar
  28. Griffith, D. A. (2003). Spatial autocorrelation and spatial filtering: Gaining understanding through theory and visualization. Berlin: Springer.CrossRefGoogle Scholar
  29. Haskins, R., & Sawhill, I. (2009). Creating an opportunity society. Washington, DC: Brookings Institution Press.Google Scholar
  30. Hollander, J. B. (2011). Sunburnt cities: The great recession, depopulation and urban planning in the American Sunbelt. Abingdon: Routledge.Google Scholar
  31. Holloway, S. R., & Mulherin, S. (2004). The effect of adolescent neighborhood poverty on adult employment. Journal of Urban Affairs, 26(4), 427–454.CrossRefGoogle Scholar
  32. Howell, A. J., & Timberlake, J. M. (2014). Racial and ethnic trends in the suburbanization of poverty in U.S. metropolitan areas, 1980–2010. Journal of Urban Affairs, 36(1), 79–98.CrossRefGoogle Scholar
  33. Isserman, A. (2005). In the national interest: Defining rural and urban correctly in research and public policy. International Regional Science Review, 28(4), 465–499.CrossRefGoogle Scholar
  34. Isserman, A. M., Feser, E., & Warren, D. E. (2009). Why some rural places prosper and others do not. International Regional Science Review, 32(3), 300–342.CrossRefGoogle Scholar
  35. Jeffrey, C. (2010). Geographies of children and youth I: Eroding maps of life. Progress in Human Geography, 34(4), 496–505.CrossRefGoogle Scholar
  36. Johnson, R. C. (2011). The place of race in health disparities: How family background and neighborhood conditions in childhood impact later-life health. In H. B. Newburger, E. L. Birch, & S. M. Wachter (Eds.), Neighborhood and life chances: How place matters in modern America (pp. 18–36). Philadelphia, PA: University of Pennsylvania Press.Google Scholar
  37. Kelly, M. (2000). Inequality and crime. Review of Economics and Statistics, 82(4), 530–539.CrossRefGoogle Scholar
  38. Kneebone, E., & Garr, E. (2010). The suburbanization of poverty: Trends in metropolitan America, 2000 to 2008. Washington, DC: Brookings Institution.Google Scholar
  39. Lyson, T. A., & Falk, W. W. (1993). Forgotten places: Uneven development in rural America. Lawrence, KS: University Press of Kansas.Google Scholar
  40. Messner, S. F., Anselin, L., Baller, R. D., Hawkins, D. F., Deane, G., & Tolnay, S. E. (1999). The spatial patterning of county homicide rates: An application of exploratory spatial data analysis. Journal of Quantitative Criminology, 15(4), 423–450.CrossRefGoogle Scholar
  41. Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37, 17–23.CrossRefGoogle Scholar
  42. National Bureau of Economic Research. (2014). US Business Cycle Expansions and Contractions. Accessed November 30, 2014.
  43. OMB (Office of Management and Budget). (2000). Standards for defining metropolitan and micropolitan areas. Federal Register, 65, 82227–82238.Google Scholar
  44. Opportunity Nation. (2014a). Opportunity Nation: The shared plan to restore opportunity. Retrieved February 2014, from
  45. Opportunity Nation. (2014b). The opportunity index data and methodology. Retrieved February 2014, from
  46. Partridge, M. D., Rickman, D. S., Olfert, M. R., & Ali, K. (2012). Dwindling U.S. internal migration: Evidence of spatial equilibrium or structural shifts in local labor markets? Regional Science and Urban Economics, 42(1–2), 375–388.CrossRefGoogle Scholar
  47. powell, j. a., Reece, J., Rogers, C., & Gambhir, S. (2007). Communities of opportunity: A framework for a more equitable and sustainable future for all. Columbus, OH: Kirwan Institute for the Study of Race and Ethnicity, The Ohio State University.Google Scholar
  48. Rosenbaum, J. E., Reynolds, L., & DeLuca, S. (2002). How do places matter? The geography of opportunity, self-efficacy, and a look inside the black box of residential mobility. Housing Studies, 17, 71–82.CrossRefGoogle Scholar
  49. Rothstein, J. (2012). The labor market four years into the crisis: Assessing structural explanations. Industrial and Labor Relations Review, 65(3), 467–500.CrossRefGoogle Scholar
  50. Sawicki, D. S., & Flynn, P. (1996). Neighborhood indicators: A review of the literature and an assessment of conceptual and methodological issues. Journal of the American Planning Association, 62(2), 165–183.CrossRefGoogle Scholar
  51. Selvin, H. C. (1958). Durkheim’s suicide and problems of empirical research. American Journal of Sociology, 63(6), 607–619.CrossRefGoogle Scholar
  52. Stiglitz, J. E. (2012). The price of inequality: How today’s divided society endangers our future. New York, NY: W.W. Norton & Co.Google Scholar
  53. Tankersley, J., & Guo, J. (2014). Congrats, America. You have less economic opportunity than you did in 1970. The Washington Post. Retrieved from
  54. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240.CrossRefGoogle Scholar
  55. Tönnies, F. (1957). Community and society (Gemeinschaft und gesellschaft). (C. P. Loomis, Trans.). East Lansing, MI: Michigan State University Press. (Original work published 1887).Google Scholar
  56. Walker, R. E., Keane, C. R., & Burke, J. G. (2010). Disparities and access to healthy food in the United States: A review of food deserts literature. Health & Place, 16(5), 876–884.CrossRefGoogle Scholar
  57. Waller, L. A., & Gotway, C. A. (2004). Applied spatial statistics for public health data (Vol. 368). New York: Wiley.Google Scholar
  58. Wang, M., Kleit, R. G., Cover, J., & Fowler, C. S. (2012). Spatial variations in U.S. poverty: Beyond metropolitan and non-metropolitan. Urban Studies, 49(3), 563–585.CrossRefGoogle Scholar
  59. Weber, J., Low, S., & Walsh, N. (2014). County-level oil and gas production in the US. Washington, DC: USDA, Economic Research Service.Google Scholar
  60. Zickuhr, K., & Smith, A. (2013). Home Broadband 2013. Washington, DC: Pew Research Center. Retrieved May 2014, from

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Urban and Regional PlanningUniversity of Illinois at Urbana-ChampaignChampaignUSA

Personalised recommendations