A Typical Neighborhood

[As usual for these map-based posts, the bigger your screen, the better.]

As promised in my previous post, today I’ll look at the most typical Single Family Detached Home neighborhoods in the US. First, we have to define ‘typical’. As you may recall, there are about 6600 census tracts that met the definition of a SFDH neighborhood. I’ll look at four pieces of data for each:

• The average age of the homes
• The average number of bedrooms
• The average footprint size
• The average density (the number of other buildings within 100 meters)

These data points indicate how old the neighborhood is (the first item in that list), how big the houses are (the next two items), and how closely-packed the houses are (the final item). Each tract has this set of data. Take, for example, the neighborhood I lived in from 1987-2006, in San Diego (Scripps Ranch):

Here are the numbers for homes in this neighborhood:

• Average age: 39.6 years
• Average number of bedrooms: 3.53
• Average footprint: 224.95 square meters (2421 square feet)
• Average density: 25

If we average the data across all 6600 SFDH neighborhoods, here’s what we get:

Age	45.76 years (built in mid 1970s)
Bedrooms	3.34
Footprint	203.31 square meters
Density	24.46

That’s what the typical SFDH neighborhood looks like.

Comparing our Scripps Ranch neighborhood to the average: it was very close when it comes to density (25 vs. 24.46), it had somewhat above-average footprints and bedroom counts, and it’s about six years younger. Reasonably close to the typical neighborhood, it seems, but saying “reasonably close” is pretty vague. What we really want is a systematic way of determining how close each neighborhood is to the average. Some way of identifying the “most typical” neighborhoods.

To determine this, I looked for the tracts whose four data points are all closest to the average. [Details: For each of the four data, determine the average. Normalize the data values such that those closest to the average equal 100. Then, take the harmonic mean of the four normalized values. The tracts with the highest value are considered the most typical.] Without further ado, here are the closest-to-average SFDH neighborhoods. You can click on each one to get a birds-eye view, then use Street View to see the houses.

Tract	Age	Bedrooms	Footprint	Density
Edmonds, Washington (501.01)	45.8	3.37	200.0	23
Littleton, Colorado (120.53)	48.2	3.46	201.5	24
Santa Clarita, California (9108.08)	43.8	3.25	206.8	23
Chino Hills, California (1.09)	44.7	3.40	218.4	25
Livonia (Detroit), Michigan (5576)	45.4	3.48	207.2	23
Riverside, California (409.04)	45.8	3.27	206.2	28
Bartlett (Memphis), Tennessee (206.35)	45.9	3.20	188.9	25
Addison (Chicago), Illinois (8402.02)	44.5	3.30	190.1	27
Mission Viejo, California (320.32)	45.6	3.50	210.3	26
Omaha, Nebraska (74.50)	45.1	3.39	181.8	26

I see lots of California suburbs, which is not surprising given the era (mid 70s). It was the middle of the boom years for the state. Also, states in the middle of the country are represented. Noticeably absent from this list are the Northeastern states (e.g., New York, Massachusetts, Pennsylvania). Even if you expand the list to include the top 100, those states barely show up. The Northeast was still building houses in the 70s, they just didn’t quite look like the rest of the country. The SFDH neighborhoods are recognizable, but the spacing is a bit different (generally, the footprints are smaller and the homes are spaced a little further apart).

By the way, our Scripps Ranch neighborhood ranked 112th out of 6600. That’s remarkably typical. Is that a good thing or not?

One final note. An interesting thing happens if I take the Age variable out of the equation. In that case, we’re looking for neighborhoods where the homes are close to the average in Bedrooms, Footprint, and Density, no matter when they were built. When you do this, you find a bunch of newer neighborhoods that look like the ones listed above. But you don’t really see many older neighborhoods with the same characteristics. Neighborhoods of this specific shape and size, now common as dirt, didn’t really exist much before the 1960s.