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.
Hunt Club median real estate price is $331,272, which is more expensive than 30.9% of the neighborhoods in Maryland and 42.0% of the neighborhoods in the U.S.
The average rental price in Hunt Club is currently $2,288, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 64.5% of Maryland neighborhoods.
Hunt Club is a densely urban neighborhood (based on population density) located in Montgomery Village, Maryland.
Hunt Club real estate is primarily made up of small (studio to two bedroom) to medium sized (three or four bedroom) apartment complexes/high-rise apartments and townhomes. Most of the residential real estate is occupied by a mixture of owners and renters. Many of the residences in the Hunt Club neighborhood are established but not old, having been built between 1970 and 1999. A number of residences were also built between 1940 and 1969.
In Hunt Club, the current vacancy rate is 2.6%, which is a lower rate of vacancies than 82.7% of all neighborhoods in the U.S. This means that the housing supply in Hunt Club is very tight compared to the demand for property here.
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
Most neighborhoods are composed of a mixture of ages of homes, but the Hunt Club stands out as rather unique in having nearly all of its residential real estate built in one time period, namely between 1970 and 1999, generally considered to be established, but not old housing. What you'll sense when you look around or drive the streets of this neighborhood is that many of the residences look the same because of this similarity of age. In fact, 94.3% of the residential real estate here was built in this one time period.
In addition, one of the really unique and interesting things about the look and setting of the Hunt Club neighborhood is that it is almost entirely dominated by large apartment buildings, such as apartment complexes or high-rise apartments. 82.7% of the residential real estate here is classified as such. This puts this neighborhood on the map as having a higher proportion of large apartment buildings than 97.1% of all neighborhoods in America.
Diversity
Did you know that the Hunt Club neighborhood has more Brazilian and Belgian ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 3.1% of this neighborhood's residents have Brazilian ancestry and 0.9% have Belgian ancestry.
Hunt Club is also pretty special linguistically. Significantly, 0.9% of its residents five years old and above primarily speak Persian at home. While this may seem like a small percentage, it is higher than 97.5% of the neighborhoods in America.
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 Hunt Club neighborhood in Montgomery Village are lower-middle income, making it a below average income neighborhood. NeighborhoodScout's research shows that this neighborhood has an income lower than 67.8% of U.S. neighborhoods. In addition, 9.0% 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 53.2% of America'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 Hunt Club neighborhood, 39.8% 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 24.6% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (24.3%), and 10.7% in clerical, assistant, and tech support 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 Hunt Club neighborhood is Spanish, spoken by 42.6% of households. Other important languages spoken here include English, French and Langs. of India.
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 Hunt Club neighborhood in Montgomery Village, MD, residents most commonly identify their ethnicity or ancestry as English (8.6%). There are also a number of people of Asian ancestry (7.1%), and residents who report Mexican roots (6.9%), and some of the residents are also of Sub-Saharan African ancestry (5.3%), along with some German ancestry residents (4.9%), among others. In addition, 40.3% of the residents of this neighborhood were born in another country.
Getting to Work
Even if your neighborhood is walkable, you may still have to drive to your place of work. Some neighborhoods are located where many can get to work in just a few minutes, while others are located such that most residents have a long and arduous commute. The greatest number of commuters in Hunt Club neighborhood spend between 15 and 30 minutes commuting one-way to work (28.8% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (61.6%) 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 (13.2%) and 8.7% of residents also ride the bus 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.
