I’ve finished an analysis of the CTPP 2017-21 data for Table B202105 (workers at workplace by detailed means of transportation). This is for California counties, and California census tracts, summarized to the county-level. The purpose is to ascertain the level of missing data due to absence of secondary allocation (imputation) to the tract-level database.

To reiterate, “primary allocation” of missing values for workplace location is always produced (by the Census Bureau) to the county, place and MCD levels. “Secondary allocation” was used in previous CTPP products, but was discontinued in the 2012-2016 CTPP. Secondary allocation imputes workplace location down to the TAZ or census tract or block group levels. (There may be better ways of stating this. I’m using my human powered AI to construct these statements.)

Results for the San Francisco Bay Area are included in this inserted graphic:
Screenshot 2025-08-27 at 3.47.13 PM.png
Overall, at least in the Bay Area, the least amount of missing secondary allocation are for the bicycle-to-work and walk-to-work modes, at 9 to 11 percent missing values. The most (worst) secondary allocation is for 3-or-more person carpools, 2-person carpools, and other (3) (motorcycle + taxicab + other). 

A possible explanation is that bicycle and walk commuters are more savvy and address-conscious than carpoolers?

As should be expected, workers working at home should never have workplace allocation issues, since the block-tract-place-county of workplace for at-home workers is identical to their home location. Only non-home workers should be factored up in Part 2 tables. 

The weirdness in the work-at-home totals (593,489 from tract data; 593,510 from county summary level) is due to rounding issues at the tract vs county level. Moral of this story: don’t expect tract-level data from the CTPP to aggregate neatly up to the county level. It’s all due to rounding. But tract-level data from standard ACS five-year tables *should* aggregate neatly up to county level.

I’m thinking that the most needed set of “county correction factors” will be for part 3: factoring tract-to-tract commuters based on county-of-residence, county-of-work, and means of transportation. 

Here is my fully fleshed R script to analyze Table B202105 from both tract summary level and county summary level file.

r_scripts.png
r_scripts/ctpp1721_california_b202105_1.R at main · chuckpurvis/r_scripts
github.com


I hope this is of use to the community!

Chuck Purvis
Hayward, CA
clpurvis@att.net