David—i do not know if you have seen this from the ACS Handbooks. See page 17.
On Mar 16, 2022, at 1:53 PM, David Heller
<dheller(a)sjtpo.org> wrote:
Hello:
I am still a little confused why using overlapping ACS datasets is not good practice.
Can someone explain it to me?
Thank you.
David Heller, PP/AICP
Program Manager - Systems Performance and Subregional Programs
South Jersey Transportation Planning Organization
782 S Brewster Road, Unit B6
Vineland, New Jersey 08361
(856) 794-1941 |
www.sjtpo.org
From: Benjamin Gruswitz <bgruswitz(a)dvrpc.org>
Sent: Tuesday, March 15, 2022 4:59 PM
To: The Census Transportation Products Program Community of Practice/Users discussion and
news list <ctpp(a)listserv.transportation.org>
Subject: [CTPP News] Re: CTPP commuter flows in strong MCD states (Vermont test case)
Yes, Chuck, this is a data advantage for strong MCD regions--the workplace allocation is
complete at this subcounty level that covers all areas of each county (as opposed to
place, which doesn't have county-wide coverage). And our TAZs nest within our
municipal boundaries, so fitting their flows to the MCD total is a good way to go for
adjustments. The only issue in our region is that Philadelphia is both a county and MCD,
so we don't get a subcounty control for our TAZ workplace fitting within our high
pop/high employment urban center the way we do for our smallest boroughs and townships (we
have one borough with a population of 10 and employment of 25).
Thanks for always pointing us to good resources and encouraging our experienced and
burgeoning R users to explore CTPP data with that toolset!
Ben
Working from Home | 301.655.3170
Ben Gruswitz, AICP | Manager, Socioeconomic & Land Use Analytics
(Pronouns: he/him)
Delaware Valley Regional Planning Commission
190 N Independence Mall West, 8th Floor
Philadelphia, PA 19106-1520
215.238.2882 |
www.dvrpc.org
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On Tue, Mar 15, 2022 at 4:05 PM Charles Purvis <clpurvis(a)att.net> wrote:
Being a west coaster, I rarely dabble in MCDs - Minor Civil Divisions, or NECTAs (New
England City and Town Areas). I thought this deserves some exploration.
I created a new version of my R-package CTPPr script that pulls in intra-state Vermont
total commuters: county-to-county, tract-to-tract, and MCD-to-MCD. I’ve shared my Vermont
code on my GIST GITHUB. I screwed up yesterday, and had the other scripts in “secret”
mode. Oops, sorry. I’ve made the correction.
https://gist.github.com/chuckpurvis
There are 14 counties in Vermont, 184 census tracts, and 255 MCDs (towns) in Vermont. The
255 MCDs are “wall-to-wall” coverage of the entire state (i.e., no lingering
unincorporated “balance of county” areas.) I was surprised that there are fewer census
tracts than MCDs in Vermont, but I had some notion that the MCD-to-MCD flow data could be
quite valuable (in certain states!)
According to the CTPPr documentation, probably the official CTPP documentation, as well,
there are MCD-to-MCD commuter flows for the twelve “strong MCD” states.
From some random US Treasury document:
"Since the government services provided by MCDs differ greatly by state, the Census
Bureau refers to
twelve states with MCDs that generally provide a wide range of general government
services as “strong-
MCD” states. In these states, MCDs are generally are treated as municipalities according
to state statutes
and codes. In eight other states, MCDs typically play less of a governmental role and
provide more limited
government services, even though they are still active governments (“weak-MCD” states).
The twelve
strong-MCD states are Connecticut, Maine, Massachusetts, Michigan, Minnesota, New
Hampshire, New
Jersey, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin. The eight weak-MCD
states are
Illinois, Indiana, Kansas, Missouri, Nebraska, North Dakota, Ohio, and South
Dakota."
Here are the highlights of this Vermont test case:
Total Workers, Intra-State, Vermont:
County-to-County = 298,422 total workers
MCD-to-MCD = 299,415 total workers
tract-to-tract = 214,970 total workers.
The county-to-county and MCD-to-MCD totals for Vermont should be very, very close, since
they both have the “standard allocation procedures” that the Census Bureau uses to impute
missing workplace to the county and place level. I’m pretty sure the difference between
county-to-county and MCD-to-MCD is rounding issues? Can never tell.
The tract-to-tract file does not have the standard allocation procedures applied: it’s
the raw data, rounded of course. If I were Vermont, I’d stick with MCD-to-MCD flows as the
best bet for controls. Adjust/factor any of the TAZ-to-TAZ flow data to MCD-to-MCD.
Happy Ides of March,
Chuck Purvis
Hayward, California
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