New subject: Working at Home in America: 2019 vs 2021:

16 Sep 2022

Hey Ed:

My guess with Redmond, WA and Dublin, CA is that they both popped the magical 65,000 total
population barrier in 2021.

Of course, my detailed spreadsheets found enough weirdness to question everything.

Pearland, Texas. Population = 131,448 (2019) and 120,694 (2021). Table DP03 shows workers
by mean of commute for 2019 but not for 2021. My R script results match what I can find on
data.census.gov <http://data.census.gov/>. Why the population decline? I’m
suspicious.

Meridian, Idaho. Population = 114,161 (2019) and 125,959 (2021). Again, table DP03 shows
workers by means of commute for 2019 but not for 2021. Again, matches data.census.gov
<http://data.census.gov/>.

The Villages, Florida. Population 85,377 (2019) and 80,691 (2021). No data on workers by
means of transportation to work for either year. This makes sense (?) since The Villages
is the largest age 55+ community in the USA. VERY few commuters to be expected. But what
happened with total population? A decline? 

Question: Is the 2021 ACS taking into account data on total population, population by
age/sex from the now available Census 2020?? I don’t know.

Both the US and States pull both 1 and 52 (states + DC + PR) in my R script for both 2019
and 2021. That’s a relief.

County = 840 in 2019; 841 in 2021… The joined dataset is 852 counties.  A little more
messy.

Place = 634 places in 2019; 634 places in 2021; but the joined dataset is 650 places. Some
places pop-in; some places are popping-out. Good grief.

PUMA = 2,364 in 2019; 2,364 in 2021; and joined together, still, 2,364. We get the most
number of geographic areas in the single-year ACS using PUMAs. And it’s wall-to-wall,
shore-to-shining-shore coverage. This is really good to know and to share.

I think we have 2,487 PUMAs based on Census 2020, but I need some verification/ backup
from Census Bureau or State Data Centers to check over my analyses.

I may want to do a test run at the county and place level, for a single year, say 2021,
for commuting data in tables DP03, B08006, and C08006. DP03 has data on workers by 6 means
of transportation; B08006 has data on workers by 13 means of transportation; C08006 has
data on workers by 8 means of transportation. I think the fewer categories, the less
suppression? 

I went to the White Sox / Athletics game this past Sunday. Dave Stewart’s number retired.
Rickey, Dennis, Carney, McGwire, Reggie, Wally Haas, and LaRussa were all there. A’s win
the game, too. Fun day in Oakland.

Chuck

...
  On Sep 15, 2022, at 5:25 PM, Ed Christopher
&lt;edc(a)berwyned.com&gt; wrote:

 Thanks Chuck. Its always interesting to see the different summaries that people are
putting together. Being a small area guy I am sort of wondering what the suppression rule
is that is "NAing" the Bethesda and Dublin data in 2019.  

 On 9/15/2022 4:31 PM, Charles Purvis wrote:
  I’m assembling some of my tweets from today’s
efforts. If you’re on twitter, follow my at @charleypurvis

 New #ACSdata on workers working at home. Top ten states + US. Using #tidycensus  . What
REALLY surprised me is that the US work-at-home share increased from 5.72% in 2019 to
15.82% in 2020 (experimental weights) and FURTHER INCREASED to 17.86 in 2021! Wow. Use
Table DP03 for data

 <table1_athome.png>

 Table 2. Ranking of US Counties #ACSData . DC and neighbor counties; San Francisco;
Seattle; NYC; and Atlanta. #tidycensus . These increases are staggering / newsworthy. Had
to verify using data.census.gov <http://data.census.gov/> to be sure!

 <table2_athome.png>

 Table 3. Work at home by Place (City) of Residence. DC, San Francisco and Seattle
suburbs. Redmond and Dublin are super-fast growing burbs. #ACSData #tidycensus . Data
matches @kyle_e_walker tweet from this morning. Lots of stories to tell.

 <table3_athome.png>

 Now focusing on Working-at-Home in the nine-county San Francisco Bay Area. #ACSData
#tidycensus . Work at home share increased from 6.5% (2019) to 32.8% (2021) in Bay Area.
Wow. A low of 12.8% in Solano to a high of 45.6% in San Francisco County. @MTCBATA

 <table4_athome.png>

 Number of workers working at home almost quintupled (five-fold increase) in the Bay Area,
2019 to 2021. #ACSData #tidycensus . From doubling plus in Sonoma County to a staggering
septupling (seven-fold increase) in Santa Clara County (Silicon Valley) @MTCBATA Pretty
wow.

 <Table5_athome.png>

 The tables are just screenshots of excel tables that I prepared this morning/early
afternoon.

 That’s all for now.

 Chuck

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Re: Working at Home in America: 2019 vs 2021: