The wealth of property
Note: This post was revised at 10:30 AM to remove vacant lots from the data and map. All calculations have been adjusted. (Thanks, Justin!)
Property tax records are a frequently overlooked resource for regional demographic data. In particular, they can provide a window into distribution of wealth, something census data does a poor job of illustrating. In Tyler, as in most places, property tax data is publicly accessible. Unfortunately, it’s not easily available in bulk. I’ve long put off writing a script to extract the data from the Smith County Appraisal District (SCAD) website, despite knowing it would be a rich source of information. So I was particularly pleased when a friend of a friend at Tyler-based TaxNetUSA offered me the complete Smith County property tax rolls, already cleaned and ready to be analyzed. Thanks to this new, rich data source I can make things like this:
I find this map fascinating for any number of reasons, but first a few caveats about how it was created. It might seem that this would be as simple as selecting properties labeled residential and putting them on a map. In fact, there is no single way of identifying a property as being residential. In order to estimate what constitutes a “home” I used the following process:
- Connect each property tax record to the tax parcel documenting its shape (the parcel shapes are what is actually mapped).
- Connect each tax parcel to the zoning area it is in.
- Filter out all tax parcels not in a residential zone.
- Filter out all parcels with zero “improvement value” to remove vacant lots.
Unfortunately, for reasons that are unclear, this doesn’t come even close to filtering out all businesses, churches, state lands, etc. (Ostensibly the zoning in Tyler is a total mess.) To accomplish this I had to go over the data and generate a long list of rules about what not to include, based on the name of the “owner”. So, for instance, I got rid of anything that ended in “LLC”, “PENTECOSTAL” or “FOUNDATION”. After a few hours of this, I had a set of properties that I believe more or less correspond to individually and jointly owned homes. It should not be believed to be perfect, but any errors should be evenly distributed throughout the dataset.
My first intuition was to shade this map by value increments of $100,000. This had the intriguing property of very clearly illustrating the “one percent” of Occupy Wall Street fame. They have homes valued at more than $500,000 and mostly live around Hollytree Country Club. However, this approach also lumped more than half of all properties (52.5%) into the “less than $100,000” group. When I observed that the median value was only $95,572 it became clear that this approach was obscuring a lot of what was interesting about the underlying data.
Instead of equal intervals, I’ve used quantiles to the represent the data, that is, five groups where each group accounts for 20% of the properties. Thus each color corresponds to approximately 4,723 of the 23,616 mapped properties. This has the much more valuable effect of illustrating where there is poverty (the 20% of homes worth less than $45,841) and prosperity (homes worth more than $173,640).
Even more interestingly, this approach seems to adequately distinguish the lower-middle, middle, and upper-middle classes relative to Tyler norms, though one should bear in mind that apartments are not illustrated at all. As low-income groups tend to cluster in multi-family units one should imagine that population being significantly larger than the map illustrates. Despite these limitations, I feel that this approach adequately demonstrates the reality of the economic divisions in the city. (I’m pleased to note that my neighborhood, Charnwood, is, as in all things, a melting pot.)
I didn’t create this map to invoke the specter of class warfare, though frankly I don’t think we can be reminded too frequently that many Americans can’t afford to eat properly. I did create it in order to demonstrate how geographically and racially aggravated these class divisions are. Tyler north of Front Street is poor and Hispanic. (See the race map, I made last year.) South of Front Street is wealthy and white. The predominantly African American communities in west and northwest Tyler are marginally better off than the Hispanic areas. However, North Tyler is also growing much more rapidly, thanks to a 55% expansion in Tyler’s Hispanic population over the last ten years. These demographic forces are going to have an unprecedented impact on the city during the next decade.
Hopefully this map will encourage individuals to carefully consider Tyler’s class stratification, especially as it impacts efforts to support minority communities, revitalize downtown and prevent economic stagnation. I’ve only just scratched the surface of this property tax data and I expect to do several more blog posts using it. In the meantime, here are a few more facts about the data presented on this map.
- Total value of all properties on the map: $2,942,661,243.
- City property taxes collected on this amount: $6,147,219.
- Total land area: 63438 square acres.
- Median year of home construction: 1960.
Thanks for reading.