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 $190,711, which is more expensive than 27.0% of the neighborhoods in Pennsylvania and 19.6% of the neighborhoods in the U.S.
The average rental price in District 3 / Alvernia University is currently $1,760, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 47.8% of Pennsylvania neighborhoods.
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.
District 3 / Alvernia University has a 10.0% vacancy rate, which is well above average compared to other U.S. neighborhoods (higher than 61.6% of American neighborhoods). Most vacant housing here is vacant year round. This could either signal that there is a weak demand for real estate in the neighborhood or that large amount of new housing has been built and not yet occupied. Either way, if you live here, you may find many of the homes or apartments are empty.
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 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, 47.8% of the residential real estate here is classified as row houses and attached homes.
In addition, do you watch 'This Old House' on Public Television? Do you love the idea of fixing up a Colonial or Victorian era home, complete with the charm of yesteryear? Do you like to stroll or drive streets lined with gracious older residences? If you found yourself nodding yes to any of these questions, you are going to be interested in this unique neighborhood. The District 3 / Alvernia University neighborhood stands out on a national scale for the sheer concentration of historic residences it contains: 60.5% of the residential real estate here was built from 1939 or earlier, some much earlier. This is a greater concentration of historic homes than 96.6% of the neighborhoods in the United States.
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 1.8% of college-friendly places to live in the state of Pennsylvania.
In addition, neighborhoodScout's analysis shows that the District 3 / Alvernia University neighborhood has a greater concentration of residents currently enrolled in college than 98.1% of the neighborhoods in the U.S. With 23.9% of the population here attending college, this is very much a college-focused neighborhood.
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, 15.5% of this neighborhood's residents have Puerto Rican ancestry and 5.3% have Dominican 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 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 66.8% of U.S. neighborhoods. In addition, 3.3% of the children seventeen and under living in this neighborhood are living below the federal poverty line, which is a lower rate of childhood poverty than is found in 70.4% of America's neighborhoods.
A neighborhood is far different if it is dominated by enlisted military personnel rather than people who earn their living by farming. It is also different if most of the neighbors are clerical support or managers. What is wonderful is the sheer diversity of neighborhoods, allowing you to find the type that fits your lifestyle and aspirations.
In the District 3 / Alvernia University neighborhood, 31.2% of the working population is employed in manufacturing and laborer occupations. The second most important occupational group in this neighborhood is sales and service jobs, from major sales accounts, to working in fast food restaurants, with 28.8% of the residents employed. Other residents here are employed in executive, management, and professional occupations (22.7%), and 17.3% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the District 3 / Alvernia University neighborhood is English, spoken by 66.5% of households. Some people also speak Spanish (30.7%).
Ethnicity / Ancestry
Boston's Beacon Hill blue-blood streets, Brooklyn's Orthodox Jewish enclaves, Los Angeles' Persian neighborhoods. Each has its own culture derived primarily from the ancestries and culture of the residents who call these neighborhoods home. Likewise, each neighborhood in America has its own culture – some more unique than others – based on lifestyle, occupations, the types of households – and importantly – on the ethnicities and ancestries of the people who live in the neighborhood. Understanding where people came from, who their grandparents or great-grandparents were, can help you understand how a neighborhood is today.
In the District 3 / Alvernia University neighborhood in Reading, PA, residents most commonly identify their ethnicity or ancestry as German (15.7%). There are also a number of people of Puerto Rican ancestry (15.5%), and residents who report Italian roots (8.4%), and some of the residents are also of Polish ancestry (5.9%), along with some South American ancestry residents (5.5%), among others. In addition, 18.4% 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 (47.7% of working residents), one of the shortest commutes across America.
Here most residents (68.8%) 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 (17.3%) and 8.8% 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.
