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Patterns of Block Group Income Inequality
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Income inequality exists in an area where there is a mix of households that have very high incomes coexisting with a set of households with very low income. The high heterogeneity of income inequality among households typically extends to other demographic, social, economic and housing attributes. A neighborhood with high income inequality is unlikely to be homogeneous in most respects.

This section reviews data and methods to examine/analyze income inequality at the block group level of geography. Block groups (BGs) average 1,200 population and cover the U.S. wall-to-wall. Using higher level geography, even census tracts, may tend to mask the existence of income equality. By using BGs, we are able to examine income inequality patterns for other geography such as cities, counties and school districts (by looking at BGs that intersect with these areas). The next map graphic illustrates how these patterns can be examined using GIS resources.

Visual Analysis of Income Inequality by Neighborhood & School District
The following view shows patterns of income inequality by block group within school districts in the Pelham, NY vicinity just north of New York City. K-12 public schools are shown as yellow markers. The Gini Index, based on ACS 2013, is used as the measure of income inequality. Colors/values of the Gini Index are shown in the legend as the left of the map. See more about the Gini Index below.

  View created with CV XE GIS. Click graphic for larger view.
  The larger view shows BGs labeled with the Gini Index value.

The following related view shows patterns of median household income (MHI) by census tract for the same area as above. This view shows the high median income for the census tracts in the southern section of Pelham school district. Compare patterns in the MHI by tract view with the Gini Index by BG view above.

  View created with CV XE GIS. Click graphic for larger view.
  Tracts labeled with percent population 25 years and over who are high school graduates.

Patterns of Income Inequality by Block Group; New York City area

  View created with CV XE GIS. Click graphic for larger view.

Block Group Income Measures
Block group income measures are only available from the American Community Survey (ACS). Block groups are the smallest geographic level for which data are tabulated from the annually updated ACS. In the applications reviewed here, the ACS 2013 5-year estimates are used.

Using the block group income inequality measures, enables us to examine characteristics in the vicinity of schools and how neighborhood inequality might exist across school districts. Neighborhods with high inequality might directly impact on K-12 student opportunities and educational outcomes.

Gini Index of Income Concentration
The Gini Index can be used as a measure of income concentration/inequality. The Gini Index is based on the Lorenz curve The Gini Index varies from 0 to 1, with a value of 0 indicating perfect equality, where there is a proportional distribution of income across all households. A value of 1 indicates perfect inequality, where one household has all the income and all others have no income.

In the graphic shown below, the Gini Index represents the area (A) between the diagonal, or line of perfect equality, and the Lorenz curve, as a percentage of the total area lying beneath the diagonal (A + B). When income inequality rises, the Lorenz curve bows further downward and the area (A) between it and the diagonal increases in size. The result is that the Gini Index increases.


The Gini Index for the U.S. in the 2013 ACS (0.481) was significantly higher than in the 2012 ACS (0.476). This increase suggests that income inequality increased nationally. Examine state-by-state patterns of income inequality using the interactive table in this related section.

The annually updated ACS 5-year estimates can tell us how income inequality is changing at the block group level. Appealing reasons for using the ACS data include the availability of related subject matter, such as educational attainment, that are relevant to extended analyses.

Analyzing Patterns for Areas of Interest
Use the existing state K-12 schools GIS projects to examine income inequality based on block groups. Project datasets include a block group layer/shapefile that contains the Gini Index and several related income attributes. More about the state K-12 GIS projects.

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ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our software, data and methodologies to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.



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