The Case for Census Tract Demographics

I think I have an old cassette tape in the attic on which Peter Francese, founder and former Publisher of American Demographics magazine, makes the case for census tracts versus Zip Codes as the best unit of analysis for geodemographic clustering. That was long before census data became available for block groups, now the standard clustering unit. But some of his points in favor of census tracts, if memory serves, have regained validity in today’s analytics-obsessed environment.

Census tracts are generally more homogeneous, demographically, than Zip Codes which can encompass many census tracts. Census tracts, generally, retain more consistent boundaries over time compared to constantly evolving Zip Codes designed for mail delivery. Tracts, in fact, are designed for tracking demographic and economic change over time.

Meanwhile, block groups have suffered. American Community Survey data, the Census Bureau’s continuous replacement survey for the decennial long-form survey, is published for block groups along with the attendant margins of error. Analysts need to keep a close eye on levels of error when poking around ACS block group data. In contrast, ACS census tract data generally have smaller margins of error and can be used with more confidence. Some routines to improve block group data, in fact, recur to census tract data.

Now, along comes the mutual love fest (excuse me, “integration”) of location intelligence and business intelligence. Analysts love maps, and they love intelligent maps even more. Clearly, digital maps, whether in a complex GIS environment or served to mobile devices, can be highly useful and sometimes highly misleading. One key to “useful” is good data. Good demographic data needs to be reasonably current and acceptably accurate for the purpose at hand.

Census tract data offer some advantages worth considering:

1.      Five-year ACS data at census tract level is reasonably accurate for many purposes.

2.      Census tract digital maps can be more pleasing to the eye and easier to manipulate compared with block group data or Zip Code data.

3.      Digital map tiling and file transfer rates using census tracts can be reasonably efficient.

4.      Census tracts nest nicely into counties and metropolitan areas allowing for easier recognition of localities and places.

5.      Retail trade areas can reasonably be delineated as a group of adjacent census tracts, resolving the tradeoff between data accuracy and cost of analysis.

Bottom line: Self-directed business intelligence analysts (from novice to Jedi), faced with the challenges of incorporating location intelligence data into their projects, should consider the advantages of census tracts in the context of point or choropleth thematic mapping.

Tom ExterComment