Chuck:

 

Summary Level 060 captures parts of municipalities within county boundaries, not the whole municipality.  We have one borough in neighboring Lancaster County (Adamstown Boro) with a very tiny piece that crosses into Berks.  SUMLEV=”060” – combined with COUNTY=”011” – captures only the Berks County piece for us.

 

Mike

 

Michael D. Golembiewski

Transportation Modeler

 

Phone 610.478.6300 Ext. 6304
Fax 610.478.6316

Web www.countyofberks.com/planning

Email mgolembiewski@countyofberks.com
Berks County Planning Commission
633 Court Street 14th Floor
Reading, PA 19601

 

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From: Charles Purvis <clpurvis@att.net>
Sent: Tuesday, March 15, 2022 8:13 PM
To: The Census Transportation Products Program Community of Practice/Users discussion and news list <ctpp@listserv.transportation.org>
Subject: [CTPP News] Re: CTPP commuter flows in strong MCD states (Vermont test case)

 

County of Berks Warning: This is an external email. Please exercise caution.

 

Ben:

 

Yes, I’m learning a lot about MCDs. I tried pulling Pennsylvania MCDs from TIDYCENSUS for the decennial census, but TIDYCENSUS (and the Census API) doesn’t have “MCD” as a standard geography. Instead, according to the Census Bureau documentation, MCDs in Pennsylvania are “county subdivision”.

 

I adapted a tidycensus script to pull “county subdivision”  (aka Minor Civil Divisions, aka boroughs, townships and cities) for three sets of Pennsylvania PL 94-171 files: 2000, 2010, 2020. This script also has my best script used to calculate racial/ethnic diversity (using the dplyr “mutate” function.)

 

It appears that townships and boroughs can straddle counties. I wonder what happens with an MCD-to-MCD CTPP flow for PA?

 

Philadelphia is a huge county, with a 2020 population of 1,603,797. The best bet here is to use PUMA-of-Residence to PUMA-of-Work for just Philadelphia County. It’s a rectangular “trip table” with multiple rows (PUMAs) and just one column (Philadelphia County), but should be the finest grained commuter flow data for Philadelphia that has primary workplace allocation. (This is the case for the Bay Area, with 54 PUMAs of residence by 9 POWPUMAs — counties — of work!)

 

Here’s my script for Pennsylvania, 2000-2020, “The Best of PL 94171”, at MCD/County Subdivision level.

 

https://gist.github.com/chuckpurvis/27a713f85c1f30aafdfef3451d074077

 

Chuck

 



On Mar 15, 2022, at 1:58 PM, Benjamin Gruswitz <bgruswitz@dvrpc.org> wrote:

 

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)

 

 

 

 

 

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