This is a small community in a single neighborhood.
As throughout the site, some neighborhood-level data are reserved for subscribers.
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.
Dayton is a very small city located in the state of Oregon. With a population of 2,677 people and just one neighborhood, Dayton is the 126th largest community in Oregon.
Occupations and Workforce
Unlike some cities, Dayton isn’t mainly white- or blue-collar. Instead, the most prevalent occupations for people in Dayton are a mix of both white- and blue-collar jobs. Overall, Dayton is a city of service providers, sales and office workers, and managers. There are especially a lot of people living in Dayton who work in sales jobs (11.22%), business and financial occupations (9.43%), and office and administrative support (8.34%).
One interesting thing about the economy is that relatively large numbers of people worked from their home: 17.47% of the workforce. While this number may seem small overall, as a fraction of the total workforce this is high compared to the rest of the county. These workers are often telecommuters who work in knowledge-based, white-collar professions. For example, Silicon Valley has large numbers of people who telecommute. Other at-home workers may be self-employed people who operate small businesses out of their homes.
Setting & Lifestyle
Demographics
The citizens of Dayton are slightly better educated than the national average of 21.84% for all cities and towns, with 22.69% of adults in Dayton having a bachelor's degree or advanced degree.
The per capita income in Dayton in 2022 was $25,262, which is low income relative to Oregon, and lower middle income relative to the rest of the US. This equates to an annual income of $101,048 for a family of four. However, Dayton contains both very wealthy and poor people as well.
Dayton is an extremely ethnically-diverse city. The people who call Dayton home describe themselves as belonging to a variety of racial and ethnic groups. The greatest number of Dayton residents report their race to be White. Dayton also has a sizeable Hispanic population (people of Hispanic origin can be of any race). People of Hispanic or Latino origin account for 40.72% of the city’s residents. Important ancestries of people in Dayton include German, English, Irish, Scottish, and European.
Foreign born people are also an important part of Dayton's cultural character, accounting for 15.35% of the city’s population.
The most common language spoken in Dayton is English. Other important languages spoken here include Spanish and Italian.
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 Dayton, the neighborhood, has some outstanding things about the way it looks and its way of life that are worth highlighting.
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 neighborhood in Dayton are upper-middle income, making it an above average income neighborhood. NeighborhoodScout's exclusive analysis reveals that this neighborhood has a higher income than 66.4% of the neighborhoods in America. With 20.4% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 69.5% of U.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 neighborhood, 31.9% 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 28.9% of the residents employed. Other residents here are employed in manufacturing and laborer occupations (22.3%), and 15.6% 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 neighborhood is English, spoken by 71.2% of households. Other important languages spoken here include Spanish and Italian.
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 neighborhood in Dayton, OR, residents most commonly identify their ethnicity or ancestry as Mexican (32.7%). There are also a number of people of German ancestry (17.3%), and residents who report English roots (11.9%), and some of the residents are also of Irish ancestry (6.4%), along with some Scottish ancestry residents (3.8%), among others. In addition, 17.3% 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 neighborhood spend between 15 and 30 minutes commuting one-way to work (43.3% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (71.2%) 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 (13.8%) . 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.
