In this post we conclude our exploration into income distribution in New Jersey by discussing the connection between equality and exclusion. In our most recent post, we hinted that low indicators of inequality do not necessarily indicate the best possible outcomes. This is because income equality and inequality can be seen in both high-income and low-income communities. Factoring median income into this analysis can yield to a more nuanced understanding of how communities are affected by their income distribution dynamics. To start such a nuanced conversation, we have conducted a composite analysis to simultaneously observe the Gini Index, the 80/20 Household Income Ratio, and Median Household Income of every municipality in New Jersey.
Methods of Analysis
To begin to construct this composite analysis, we ranked every municipality’s Gini Index and 80/20 Household Income Ratio based on quartiles of all municipalities. For instance, if a municipality’s Gini Index fell within the lowest quartile of all municipalities, it received a “1” ranking. While a municipality with a Gini Index within the second quartile received a “2” ranking, and so on. This ranking process was repeated in an identical manner for municipalities’ 80/20 Household Income Ratio. For each municipality, the two resulting ranking numbers were added together to create one composite ranking score. This composite ranking ranged from 2-8, with higher numbers indicating more income inequality. This process is illustrated below to show some possible results of the composite score.
Each municipality’s Composite Score was itself ranked based on quartiles of all municipalities. This classification method is seen below. Again, higher numbers indicate more income inequality.
In order to account for relative income level, each municipality’s median household income was compared to the median household income of the State of New Jersey. This comparison led to the classification method seen below.
Finally, the individual composite classes shown in Tables 2 and 3 were combined to create twelve distinct typologies of income inequality that measure both household income distribution and household income, relative to all New Jersey municipalities. The typologies are shown below.
Understanding the Results
Classifying municipalities into the twelve typologies listed above help us to account for the role relative income plays in understanding how income distribution effects communities. Below, four of the Income Inequality Typologies are discussed in order to highlight how income distribution shapes these communities.
Typology: Low-Income, 1 (Egg Harbor, Netcong, Victory Gardens, Audubon Park). This typology only includes six municipalities. They are small towns, none of which exceed 4,500 in population. They are communities that are exclusively low-income, meaning income that exists in the economy is distributed relatively equally among the few residents. These towns are also small in geography or located in environmentally-sensitive areas, meaning it may be difficult to attract new services, amenities, jobs, and higher-income residents. These communities should focus on the services that meet the needs of their small and relatively homogenous population.
Typology: Low-Income, 4 (Newark, Paterson, Trenton, Camden, Passaic). Municipalities in this typology have some of the lowest median household incomes seen in the state, yet income that exists in the economy is distributed relatively unequally, compared to other municipalities in the state. This group of municipalities includes most of the large cities, and those with high unemployment and poverty. While it is worthwhile to attract additional jobs, services and amenities, along with building housing that caters to higher-income residents in order to strengthen the local economy and tax base, cities in this typology simultaneously need to guard against further income inequality by protecting and catering to existing low-income residents through such policies as rent control, job-training and education programs, and Community Benefits Agreements.
Typology: High-Income, 1 (Piscataway, West Milford, Roxbury, Vernon). Municipalities in this typology have median household incomes of at least 120% of the state median household income and have some of the highest levels of income equality in the state. The combination of high income and equality means these communities are exclusive to mainly-high-income residents. For instance, 80% of the households in Millstone Township, a community of 10,500 in Monmouth County, earns at least $71,000 per year. Such levels of exclusion effectively ensure lower-income residents employed in vital community service occupations are unable to afford housing costs in these communities. Local land use and housing policies such as inclusionary zoning, workforce housing, and others that ease development regulations and lower the costs to build new homes could help to make these communities available to lower-income households.
Typology: High-Income, 4 (Hoboken, West Orange, Manalapan, Montclair). Municipalities in this typology have median household incomes of at least 120% of the state median household income and yet have some of the highest levels of income inequality in the state. Most communities in this typology are attractive to higher-income residents due to their proximity to job centers and/or their proximity to commuter rail transportation that connects residents to jobs or amenities. Proximity to jobs and transit also makes these communities attractive to lower-income residents who are more likely to be dependent on public transportation. The greater presence of lower-income households (relative to the High-Income, 1 Typology) demonstrates a willingness by the community to provide housing options for the wide range of its residents. Local land use and housing policies such as rent control, inclusionary housing, and workforce housing as well as economic development policies such as job training and education programs should be preserved in order to ensure lower-income residents’ continued inclusion and protection from displacement.
Use the interactive feature below to search for your communities of interest.
Author: John Manieri, AICP
Research, Analysis, and Technical Assistance: Steve Scott
U.S. Census Bureau, 2010-2014 5-year American Community Survey. Table B19080
U.S. Census Bureau, 2010-2014 5-year American Community Survey. Table B19083
U.S. Census Bureau, 2010-2014 5-year American Community Survey. Table S1903