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.
District 3 / Alvernia University median real estate price is $201,090, which is less expensive than 73.6% of Pennsylvania neighborhoods and 80.3% of all U.S. neighborhoods.
The average rental price in District 3 / Alvernia University is currently $1,951, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 62.3% of the neighborhoods in Pennsylvania.
District 3 / Alvernia University is a suburban neighborhood (based on population density) located in Reading, Pennsylvania.
District 3 / Alvernia University real estate is primarily made up of medium sized (three or four bedroom) to small (studio to two bedroom) townhomes and single-family homes. Most of the residential real estate is occupied by a mixture of owners and renters. Many of the residences in the District 3 / Alvernia University neighborhood are relatively historic, built no later than 1939, and in some cases, quite a bit earlier. A number of residences were also built between 1940 and 1969.
Home and apartment vacancy rates are 8.2% in District 3 / Alvernia University. NeighborhoodScout analysis shows that this rate is lower than 45.8% 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.
People
One of the really interesting characteristics about the District 3 / Alvernia University neighborhood is that, according to NeighborhoodScout's exclusive research, it is an excellent choice in which to reside for college students. Due to its popularity among college students who already choose to live here, its walkability, and its above average safety from crime, the neighborhood is ideal for prospective or already-enrolled college students. Between semesters and during school breaks, you'll notice that the excitement here fluctuates with the college seasons. Despite the excitement however, parents of college-age children can rest easy knowing that this neighborhood has an above average safety rating. For each of these reasons, the neighborhood is rated among the top 1.1% of college-friendly places to live in the state of Pennsylvania.
In addition, an extraordinary 24.8% of the residents of the District 3 / Alvernia University neighborhood are currently enrolled in college. This is such a large part of life in this neighborhood that the neighborhood changes a great deal with the change of semesters and is far quieter during the summer when many students are away.
Real Estate
If you love row houses and attached homes, you will probably really like the District 3 / Alvernia University 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, 47.4% of the residential real estate here is classified as row houses and attached homes.
In addition, if you find historic homes and neighborhoods attractive, you love the details, the history, and the charm, then you are sure to be interested in this neighborhood. With 64.6% of the residential real estate in the District 3 / Alvernia University neighborhood built no later than 1939, and some built considerably earlier, this neighborhood has a greater concentration of historic residences than 97.7% of all neighborhoods in America. In this regard, this neighborhood truly stands out as special.
Occupations
From major sales accounts to fast-food workers, sales and service employees are often the backbone of the local economy. In the District 3 / Alvernia University neighborhood, they truly stand out. NeighborhoodScout's exclusive analysis identifies this neighborhood as having a higher percentage of sales and service workers than 98.2% of all American neighborhoods.
Car Ownership
We Americans love our cars. Not only are they a necessity for most Americans due to the shape of our neighborhoods and the distances between where we live, work, shop, and go to school, but we also fancy them. As a result, most households in America have one, two, or three cars. But NeighborhoodScout's exclusive analysis shows that the District 3 / Alvernia University neighborhood has a highly unusual pattern of car ownership. 22.0% of the households in this neighborhood don't own a car at all. This is more carless households than NeighborhoodScout found in 95.7% of U.S. neighborhoods.
Diversity
Did you know that the District 3 / Alvernia University neighborhood has more Puerto Rican and Dominican ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 19.0% of this neighborhood's residents have Puerto Rican ancestry and 8.8% have Dominican ancestry.
The Neighbors
How wealthy a neighborhood is, from very wealthy, to middle income, to low income is very formative with regard to the personality and character of a neighborhood. Equally important is the rate of people, particularly children, who live below the federal poverty line. In some wealthy gated communities, the areas immediately surrounding can have high rates of childhood poverty, which indicates other social issues. NeighborhoodScout's analysis reveals both aspects of income and poverty for this neighborhood.
The neighbors in the District 3 / Alvernia University neighborhood in Reading are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 75.5% of U.S. neighborhoods. With 12.3% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 55.4% 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 District 3 / Alvernia University neighborhood, 43.0% of the working population is employed in sales and service jobs, from major sales accounts, to working in fast food restaurants. The second most important occupational group in this neighborhood is executive, management, and professional occupations, with 24.2% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (21.4%), and 11.4% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the District 3 / Alvernia University neighborhood is English, spoken by 60.3% of households. Some people also speak Spanish (37.0%).
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 District 3 / Alvernia University neighborhood in Reading, PA, residents most commonly identify their ethnicity or ancestry as Puerto Rican (19.0%). There are also a number of people of German ancestry (12.4%), and residents who report Dominican roots (8.8%), and some of the residents are also of Italian ancestry (8.4%), along with some Irish ancestry residents (5.4%), among others. In addition, 20.5% of the residents of this neighborhood were born in another country.
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 District 3 / Alvernia University neighborhood spend under 15 minutes commuting one-way to work (52.9% of working residents), one of the shortest commutes across America.
Here most residents (66.0%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (20.9%) and 8.7% of residents also hop out the door and walk to work 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.
