Race, Diversity, and Ethnicity in Downtown Jersey City, Jersey City, NJ

The map below shows majority race by area in Downtown Jersey City, as self-identified on the US census. Darker shades indicate a larger racial majority in that neighborhood. This page also contains data and maps on Downtown Jersey City racial diversity and diversity scores. Click here to scroll to diversity data.

Downtown Jersey City, Jersey City, NJ map of race and ethnicity
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White
Hispanic
Black
Asian
Multiple/Other
WhiteHispanicBlackAsianMultiple/Other
Majority race by area

The majority race in Downtown Jersey City overall is white, making up 40.0% of residents. The next most-common racial group is asian at 31.2%. There are more white people in the northwest areas of the neighborhood. People who identify as asian are most likely to be living in the east places. The data below shows how many people identify themselves as each of the following races, which most Americans base on their family's national origin:

Race in Downtown Jersey City

 
Self-Identified Race
Downtown Jersey City, Jersey City, NJ Population
White
40.0%
Hispanic
17.0%
Black
7.1%
Asian
31.2%
Native American
0.1%
Other
4.6%
   

Diversity and Diversity Scores for Downtown Jersey City, Jersey City, NJ

The map below shows diversity in Downtown Jersey City. Areas in green are more diverse, while areas in red are much less diverse. Diversity, in this case, means a mixture of people with different race and ethnicity living close to one another. For example, all-black and all-white areas in the neighborhood would both be considered lacking diversity.

Downtown Jersey City, Jersey City, NJ map of race and ethnicity
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Downtown Jersey City Diversity Score

88

With a diversity score of 88 out of 100, Downtown Jersey City is much more diverse than other US neighborhoods. The most diverse area within Downtown Jersey City's proper boundaries is to the north of the neighborhood. The least diverse areas are located in the east parts of Downtown Jersey City.

Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.

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