The Geography of the Higley 1000
The concept of “neighborhood” in America is to say the least, amorphous. Realtors are notorious at “stretching” ill-defined neighborhood boundaries of wealthy places in the interest of generating higher prices through a halo effect.
Mapping companies vary from identifying virtually every sub-division (ADC Maps) to the grudging vagueness of a few well known neighborhoods (eg. Thomas Brothers Guides, Rand McNally). I have used a variety of resources in trying to identify individual neighborhoods including extensive use of the internet. Although I may not have identified every single neighborhood at this point, I think any fair observer will find that my sample is impressive and further refinement will do little to alter the basic statistics.
The basic building blocks of all of the statistics on this website are Census Tracts and Block Groups. A typical tract has about 2,000 households which are then subdivided into Block Groups (ideally about 500 households). The Census originally drew the Tracts and Block Groups to be socio-economically homogeneous.
The Census Bureau first used tracts in selected urban neighborhoods in the 1940 Census. The system of Census Tracts gradually expanded over the decades until it covered the entire country by the 2000 Census. The point of the system was to maintain geographic boundaries from decade to decade to allow researchers to compare socio-economic changes over times within set boundaries. At the same time the system had to be supple enough to accommodate growth (particularly on the ever expanding suburban fringe). For the most part, the boundaries appear to be well drawn.
For the 2010 Census, I was forced to abandon using Block Groups as the data is no longer easily available. Retrograde changes to the website over the interface that was used 10 years ago make using Block Group data virtually impossible. Leave it to outsourcing to the private sector to ruin a good thing. The witless Republicans in Congress outsourced the website to IBM and as a result the Census website managed to go backwards in usability.
Mean Household Income
The mean household income statistics will immediately strike the viewer of this web-site as being incredibly modest considering the pricey real estate they must support. This is because of the way the Census collected income data in 2000. The one in six households that received a “long form” were limited to six income categories in which they could not claim more than $999,999 income in each category. The two categories “Wages” and “Investment Income” would account for the bulk of the income reported by households in the Higley 1000 effectively capping reported income at approximately $2 million dollars. The other categories such as “Social Security” or “Government Assistance” hardly apply to the Higley 1000!
The bottom line of this discussion is that Mean Household Income should have a big asterisk next to it as being representative, not necessarily absolute.
Another complicating factor is the Servant issue. If live-in household servants have their own kitchen and bathroom facilities, they are counted as a “household”. This would account for some of the lower incomes found in almost every tract and block group. This also would account for some of the minority households found in the Higley 1000. It is possible to tease out household income by race at the Block Group level to determine just how much the “staff” factors affects Higley 1000 neighborhoods.
Although neighborhood and mean income may be an inexact science, the Census does collect racial data in a perfect count (theoretically!). Every one is counted and cataloged by race. In the interest of simplicity, I have used the four categories of Non-Hispanic White, Asian, Hispanic, and Black. Hispanics can be of any race and include Cubans, Mexicans, and all other Latin-Americans. “Asians” include everything from the most common Asian ethnic group, Chinese to the less common Hmong. Not satisfactory, but racial sub-categories are not available at the Block Group level. For the 2010 Census, I plan to break down the Asian racial groups as that information is available at the tract level.
During the course of my research over 3,000 neighborhoods and places, I was struck by the low mean household incomes in affluent retirement communities. Plush places from Hilton Head to Palm Springs failed to have a high enough mean household income to make the Higley 1000.
In 2010, the paucity of retirement places in the Higley 1000 has lifted a bit. Evidently, wealthy people are taking up residence in many communities that formerly were left to the seasonal help. Huge increases in mean household income were found in places as diverse as Southampton, NY and Kiawah Island, South Carolina.
Apartments & Condominiums
Nothing lowers mean household income of a Block Group faster than the presence of rental apartments. Surprisingly, condominiums also appear to cause a dramatic decline in mean household income. Could it be that when considering condominiums, there is also a retirement factor influencing income?
Higley Designated Places
I have included a relatively small number of neighborhoods that I am personally acquainted with and feel comfortable estimating their income. As household and race statistics are broken down on a block by block basis by the Census, the racial make-up of these places is accurate.
I will not enumerate Higley Designated Places for the 2010 Census
Places that Bear further Research
In spite of my best efforts, I have not been able to properly name about 100 neighborhoods in the Higley 1000. I have used several methods as placeholder names until further research helps me refine the naming of these places. I have used several methods when all else has failed. I’ve used directional names for some (North, Southwest, etc.), a country club, a public park, or a geographic feature. When all else fails, I use the name of a prominent street that runs through the neighborhood. I am well aware that some of my names probably mean nothing locally.
My hope is that my blog feature will allow me to correct these nomenclature failings in the future!