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.
Kiest Park median real estate price is $253,045, which is more expensive than 42.9% of the neighborhoods in Texas and 31.1% of the neighborhoods in the U.S.
The average rental price in Kiest Park is currently $1,810, based on NeighborhoodScout's exclusive analysis. Rents here are currently lower in price than 48.4% of Texas neighborhoods.
Kiest Park is an urban neighborhood (based on population density) located in Dallas, Texas.
Kiest Park real estate is primarily made up of medium sized (three or four bedroom) to small (studio to two bedroom) single-family homes and townhomes. Most of the residential real estate is owner occupied. Many of the residences in the Kiest Park neighborhood are older, well-established, built between 1940 and 1969. A number of residences were also built before 1940.
In Kiest Park, 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 Kiest Park 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 have a mixture of ages of homes in them, from new to old, but this neighborhood stands out due to its concentration of residential real estate built in one time frame: from 1940 through 1969, generally considered older, well-established homes. This was a busy time in America for home construction. After the end of World War II, as GIs came home, bought newly built homes on the edges of cities with the help of the GI Bill, and began their families. This housing era generally coincides with the 'Baby Boom' generation (1945 - 1964), and many baby boomers grew up in homes built in this era. But what is so interesting about the Kiest Park neighborhood, is that an incredible 82.2% of the homes here were built in this era. So when you walk its streets or drive through, this neighborhood has a look and feel that harkens to that era in American life, a very important slice of Americana.
Occupations
NeighborhoodScout's exclusive research identifies the Kiest Park neighborhood as having one of the highest concentrations of people employed in manufacturing or as laborers of any neighborhood in America. In fact, despite the loss of manufacturing jobs nationally, this neighborhood has 43.4% of its working residents employed in such fields, which is a higher proportion than 96.3% of American neighborhoods.
Diversity
Did you know that the Kiest Park neighborhood has more Mexican ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 82.3% of this neighborhood's residents have Mexican ancestry.
Kiest Park is also pretty special linguistically. Significantly, 75.4% of its residents five years old and above primarily speak Spanish at home. This is a higher percentage than 98.1% of all U.S. neighborhoods.
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 Kiest Park neighborhood in Dallas are middle-income, making it a moderate income neighborhood. NeighborhoodScout's exclusive analysis reveals that this neighborhood has a higher income than 45.1% of the neighborhoods in America. With 19.1% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 67.3% 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 Kiest Park neighborhood, 43.4% 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 21.5% of the residents employed. Other residents here are employed in executive, management, and professional occupations (18.6%), and 16.5% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the Kiest Park neighborhood is Spanish, spoken by 75.4% of households. Some people also speak English (24.6%).
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 Kiest Park neighborhood in Dallas, TX, residents most commonly identify their ethnicity or ancestry as Mexican (82.3%). There are also a number of people of English ancestry (3.2%), and residents who report Sub-Saharan African roots (2.4%), and some of the residents are also of Italian ancestry (1.7%), along with some German ancestry residents (1.3%), among others. In addition, 27.7% 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 Kiest Park neighborhood spend between 15 and 30 minutes commuting one-way to work (41.5% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (76.9%) 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 (10.0%) . 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.
