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.
University of Maryland Baltimore County median real estate price is $480,916, which is more expensive than 53.2% of the neighborhoods in Maryland and 63.6% of the neighborhoods in the U.S.
The average rental price in University of Maryland Baltimore County is currently $3,301, based on NeighborhoodScout's exclusive analysis. The average rental cost in this neighborhood is higher than 75.5% of the neighborhoods in Maryland.
University of Maryland Baltimore County is a suburban neighborhood (based on population density) located in Catonsville, Maryland.
University of Maryland Baltimore County real estate is primarily made up of large (four, five or more bedroom) to medium sized (three or four bedroom) single-family homes. Most of the residential real estate is renter occupied. Many of the residences in the University of Maryland Baltimore County neighborhood are newer, built in 2000 or more recently. A number of residences were also built between 1940 and 1969.
In University of Maryland Baltimore County, the current vacancy rate is 0.0%, which is a lower rate of vacancies than 100.0% of all neighborhoods in the U.S. This means that the housing supply in University of Maryland Baltimore County is very tight compared to the demand for property here.
Notable & Unique Neighborhood Characteristics
Many things matter about a neighborhood, but the first thing most people notice is the way a neighborhood looks and its particular character. For example, one might notice whether the buildings all date from a certain time period or whether shop signs are in multiple languages. This particular neighborhood in Catonsville, the University of Maryland Baltimore County neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
Real Estate
Renter-occupied real estate is dominant in the University of Maryland Baltimore County neighborhood. The percentage of rental real estate here, according to exclusive NeighborhoodScout analysis, is 98.6%, which is higher than 98.9% of the neighborhoods in America. If you were to buy and live in the property you bought here, you would be almost alone in doing so. This neighborhood has the distinction of having one of the lowest real estate vacancy rates of any neighborhood in America. With just 0.0% of the real estate vacant, this indicates an exceptionally strong demand for real estate in the University of Maryland Baltimore County neighborhood, and/or an issue with creating enough supply for the demand. This could have the effect of increasing real estate prices, increasing supply to meet demand, or both.
In addition, some neighborhoods are made up of apartments. Some consist of row houses, and most - by far - consist of a mixture of housing types. But the University of Maryland Baltimore County neighborhood stands out due to the total dominance of detached, single-family homes here. There are nearly no other types of residential real estate in the neighborhood. In fact, this neighborhood has a higher proportion of single-family homes in its real estate stock than 98.8% of all American neighborhoods.
Furthermore, one way that the University of Maryland Baltimore County neighborhood really stands out, is that it has more large 4, 5, or additional bedroom homes and real estate than 97.6% of the neighborhoods in America. When you walk or drive around this neighborhood, you'll instantly notice the size of the homes here which definitely makes a strong visual statement.
People
In a nation where 1 out of every 4 children lives in poverty, the University of Maryland Baltimore County neighborhood stands out as being ranked among the lowest 0.0% of neighborhoods affected by this global issue.
In addition, an extraordinary 95.6% of the residents of the University of Maryland Baltimore County 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.
Also, one of the really interesting characteristics about the University of Maryland Baltimore County 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 0.5% of college-friendly places to live in the state of Maryland.
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 University of Maryland Baltimore County neighborhood have a highly unusual car ownership. Residents of this neighborhood must really love automobiles. NeighborhoodScout's Analysis reveals that 84.6% of the households here have four, five, or more cars. That is more cars per household than in 100.0% of the neighborhoods in the nation.
Modes of Transportation
More people in University of Maryland Baltimore County choose to walk to work each day (22.1%) 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.
Migration / Stability
Some neighborhoods have more internal cohesiveness than others. While other neighborhoods feel like a collection of strangers who just happen to live near each other. Sometimes this comes down to not only the personalities of the people in a place, but how long people have been together in that neighborhood. NeighborhoodScout's research has revealed some interesting things about the rootedness of people in the University of Maryland Baltimore County neighborhood. In the University of Maryland Baltimore County neighborhood, a greater proportion of the residents living here today did not live here five years ago than is found in 98.6% of U.S. Neighborhoods. This neighborhood, more than almost any other in America, has new residents from other areas.
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 University of Maryland Baltimore County neighborhood in Catonsville are low income, making it among the lowest income neighborhoods in America. NeighborhoodScout's research shows that this neighborhood has an income lower than 100.0% of U.S. neighborhoods. In addition, 0.0% 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 100.0% of America's neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the University of Maryland Baltimore County neighborhood, 34.7% of the working population is employed in executive, management, and professional 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 33.6% of the residents employed. Other residents here are employed in clerical, assistant, and tech support occupations (22.3%), and 8.8% in manufacturing and laborer occupations.
Languages
The languages spoken by people in this neighborhood are diverse. These are tabulated as the languages people preferentially speak when they are at home with their families. The most common language spoken in the University of Maryland Baltimore County neighborhood is English, spoken by 75.9% of households. Other important languages spoken here include Spanish, Polish and French.
Ethnicity / Ancestry
Culture is shared learned behavior. We learn it from our parents, their parents, our houses of worship, and much of our culture – our learned behavior – comes from our ancestors. That is why ancestry and ethnicity can be so interesting and important to understand: places with concentrations of people of one or more ancestries often express those shared learned behaviors and this gives each neighborhood its own culture. Even different neighborhoods in the same city can have drastically different cultures.
In the University of Maryland Baltimore County neighborhood in Catonsville, MD, residents most commonly identify their ethnicity or ancestry as Asian (10.1%). There are also a number of people of Sub-Saharan African ancestry (9.6%), and residents who report Irish roots (6.5%), and some of the residents are also of German ancestry (5.5%), along with some Italian ancestry residents (4.7%), among others. In addition, 10.2% 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 University of Maryland Baltimore County neighborhood spend under 15 minutes commuting one-way to work (51.4% of working residents), one of the shortest commutes across America.
Here most residents (48.5%) 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 (22.1%) and 14.2% 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.
