What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Chester North median real estate price is $150,811, which is less expensive than 84.8% of Pennsylvania neighborhoods and 88.2% of all U.S. neighborhoods.
The average rental price in Chester North is currently $1,794, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 47.5% of Pennsylvania neighborhoods.
Chester North is an urban neighborhood (based on population density) located in Chester, Pennsylvania.
Chester North real estate is primarily made up of medium sized (three or four bedroom) to small (studio to two bedroom) townhomes and apartment complexes/high-rise apartments. Most of the residential real estate is renter occupied. Many of the residences in the Chester North neighborhood are older, well-established, built between 1940 and 1969. A number of residences were also built before 1940.
Home and apartment vacancy rates are 8.7% in Chester North. NeighborhoodScout analysis shows that this rate is lower than 43.1% of the neighborhoods in the nation, approximately near the middle range for vacancies.
Notable & Unique Neighborhood Characteristics
The way a neighborhood looks and feels when you walk or drive around it, from its setting, its buildings, and its flavor, can make all the difference. This neighborhood has some really cool things about the way it looks and feels as revealed by NeighborhoodScout's exclusive research. This might include anything from the housing stock to the types of households living here to how people get around.
Real Estate
If you love row houses and attached homes, you will probably really like the Chester North neighborhood. The ambiance, the charm, of row houses is something special. And in sheer abundance of row houses, this neighborhood truly stands out. The real estate here has a higher proportion of row houses and attached homes than nearly any neighborhood in America. In fact, 43.5% of the residential real estate here is classified as row houses and attached homes.
Modes of Transportation
More people in Chester North choose to walk to work each day (14.9%) than almost any neighborhood in America. If you are attracted to the idea of being able to walk to work, this neighborhood could be a good choice.
Car Ownership
Most American households own a car or other vehicle. Many own two cars or perhaps three. In the United States, it is useful to have an automobile not only for commuting, but also for shopping and getting to other services one needs. But NeighborhoodScout's analysis revealed that households in the Chester North neighborhood have a highly unusual car ownership. 27.3% of the households in this neighborhood don't own a car at all. This is more carless households than NeighborhoodScout found in 96.8% of U.S. neighborhoods.
Diversity
Did you know that the Chester North neighborhood has more Sub-Saharan African ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 16.7% of this neighborhood's residents have Sub-Saharan African ancestry.
The Neighbors
There are two complementary measures for understanding the income of a neighborhood's residents: the average and the extremes. While a neighborhood may be relatively wealthy overall, it is equally important to understand the rate of people - particularly children - who are living at or below the federal poverty line, which is extremely low income. Some neighborhoods with a lower average income may actually have a lower childhood poverty rate than another with a higher average income, and this helps us understand the conditions and character of a neighborhood.
The neighbors in the Chester North neighborhood in Chester are low income, making it among the lowest income neighborhoods in America. NeighborhoodScout's research shows that this neighborhood has an income lower than 94.8% of U.S. neighborhoods. With 16.3% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 63.5% of U.S. neighborhoods.
What we choose to do for a living reflects who we are. Each neighborhood has a different mix of occupations represented, and together these tell you about the neighborhood and help you understand if this neighborhood may fit your lifestyle.
In the Chester North neighborhood, 35.3% of the working population is employed in clerical, assistant, and tech support occupations. The second most important occupational group in this neighborhood is executive, management, and professional occupations, with 24.7% of the residents employed. Other residents here are employed in sales and service jobs, from major sales accounts, to working in fast food restaurants (21.9%), and 18.1% in manufacturing and laborer occupations.
Languages
The most common language spoken in the Chester North neighborhood is English, spoken by 90.5% of households. Some people also speak Spanish (4.9%).
Ethnicity / Ancestry
Culture is the shared learned behavior of peoples. Undeniably, different ethnicities and ancestries have different cultural traditions, and as a result, neighborhoods with concentrations of residents of one or another ethnicities or ancestries will express those cultures. It is what makes the North End in Boston so fun to visit for the Italian restaurants, bakeries, culture, and charm, and similarly, why people enjoy visiting Chinatown in San Francisco.
In the Chester North neighborhood in Chester, PA, residents most commonly identify their ethnicity or ancestry as Sub-Saharan African (16.7%). There are also a number of people of German ancestry (6.0%), and residents who report English roots (5.9%), and some of the residents are also of Irish ancestry (3.8%), along with some Puerto Rican ancestry residents (3.7%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in Chester North neighborhood spend between 15 and 30 minutes commuting one-way to work (44.9% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (65.3%) drive alone in a private automobile to get to work. In addition, quite a number also hop out the door and walk to work to get to work (14.9%) and 8.8% of residents also carpool with coworkers, friends, or neighbors for their daily commute. In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
