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Re: Defining PUMAs for Census 2020

by Graham, Todd

Guy- I saw your August 24 email RE: "We haven't heard about this from our State Data Center or anyone else so I'm not sure if we're supposed to be involved with it or not, seems like we should be." Right. Census Bureau has put Census State Data Centers (SDCs) in the driver's seat of PUMA delineations. When your state's SDC Lead Agency reaches out depends on how attentive they are to in-state partnerships. * * fun footnote: Until end of 2019, I was a board member and then chairman of the national network of SDCs<https://www.census.gov/about/partners/sdc/member-network/steering-committee…>. What I learned from it: Some states' SDCs are well-resourced, high-performing as partners. Others, less so. But in all cases Census Bureau provides zero funding to the SDCs - never has - so anything a state's SDC is doing (or not) is ultimately discretionary & guided by its own agenda or purpose. Your state's SDC should call Atlanta Regional Council. + same in other states. But if the whole month of September goes by, and Oct. 1st rolls around, you may need to call them, take the initiative. Here is the list of State Lead contacts in all states: https://www.census.gov/about/partners/sdc/member-network.html In my opinion, any MPO serving a region where individual counties have > 200,000 population should be involved. And specifically: enlist the MPO analysts who were involved 2+ years ago in the re-tracting initiative (what Census calls the Participant Statistical Areas Program). They will be really well-prepared for this task... If that describes you, contact your Census State Data Center this fall. Hope that helps. --Todd Graham [Metropolitan Council Logo] Todd Graham Principal Forecaster | Research Metropolitan Council 390 North Roberrt Street, St. Paul, MN 55101 Ph. 651-602-1322 metrocouncil.org<https://www.metrocouncil.org/data> | facebook<https://www.facebook.com/MetropolitanCouncil> | twitter<https://twitter.com/metcouncilnews> From: Guy Rousseau <GRousseau(a)atlantaregional.org> Sent: Tuesday, August 24, 2021 3:48 PM To: Graham, Todd <todd.graham(a)metc.state.mn.us>; ChristopherEd <edc(a)berwyned.com>; Charles Purvis <clpurvis(a)att.net> Cc: Weinberger Penelope <pweinberger(a)aashto.org> Subject: RE: Defining PUMAs for Census 2020 Thanks Todd, Ed and Chuck for the suggestions. We haven't heard about this from our State Data Center or anyone else so I'm not sure if we're supposed to be involved with it or not, seems like we should be. I don't remember MPOs having to delineate PUMAs in the past, especially for 2010's set, though it's possible I missed that, as I wasn't directly involved with that work back then, so I don't think we've been involved with the delineation before. Anyhow, we've got the 2020 Census geography in a geodatabase (GDB), however we don't yet have all the population data, just the tracts. We're still waiting on the tables to join for the blocks and block groups. We looked at the PUMAs (borders in white) in relation to our ARC Super Districts (multicolored) and it looks like most counties have more super-districts than PUMAs in them. We will also look at how the 2020 tracts nest within the 2010 PUMAs and what the 2020 population is. [Map Description automatically generated with low confidence] From: Graham, Todd <todd.graham(a)metc.state.mn.us<mailto:todd.graham@metc.state.mn.us>> Sent: Monday, August 23, 2021 4:01 PM To: The Census Transportation Products Program Community of Practice/Users discussion and news list <ctpp(a)listserv.transportation.org<mailto:ctpp@listserv.transportation.org>> Subject: [CTPP News] Re: Defining PUMAs for Census 2020 Hi Chuck- Thanks for the heads-up. Yes, that is the way to think of PUMAs = as "super-districts" or sub-state regions. Here are my "pro-tips" learned in PUMA drawing 10 years ago: 1. Do not group together fractional pieces of counties when you could keep a county whole, or when you could group multiple whole counties together in a PUMA. 2. When splitting counties into multiple PUMAs, try to arrange for the split lines to be stable city/town boundaries. This means you're looking to create PUMAs where city/town boundaries are aligned with Tract boundaries. (Because Census Geog Dept will require that tracts be the basic units of PUMA assembly.) The reason I emphasize parsimony with counties in point #1 is: The PUMAs you draw will enable or limit the detail of MIGPUMAs as well. (MIGPUMA= Migration origination geographic units) Census Bureau will create MIGPUMAs as the least common denominator grouping of counties that is entirely coincident with a group of PUMAs. So don't split counties unnecessarily. The reason I emphasize city/town boundaries in point #2 -- even though Census Geog discusses tracts as the basic units - is this: The PUMAs you draw will enable or limit the detail of POWPUMAs. (POWPUMAs = Place of Work geographic units) Census Bureau will create POWPUMAs as the least common denominator grouping of counties + places that is entirely coincident with a group of PUMAs. Stated differently: Census looks for combinations of county + place to uniquely nest within a POWPUMA. Why is this the standard for POWPUMAs? It's because of the questions asked on ACS: ACS asks specifically for the county + place of one's work location. The PUMA final criteria document https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/…<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.censu…> does say all this, but you'd have to read all the way to the last 3 pages of that document to find it. That's all my advice. Good luck! --Todd Graham [Map Description automatically generated] [Metropolitan Council Logo] Todd Graham Principal Forecaster | Research Metropolitan Council 390 North Roberrt Street, St. Paul, MN 55101 Ph. 651-602-1322 metrocouncil.org<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.metro…> | facebook<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.faceb…> | twitter<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Ftwitter.c…> From: Charles Purvis <clpurvis(a)att.net<mailto:clpurvis@att.net>> Sent: Monday, August 23, 2021 12:32 PM To: ctpp(a)listserv.transportation.org<mailto:ctpp@listserv.transportation.org> Subject: [CTPP News] Defining PUMAs for Census 2020 The Census Bureau is ramping up efforts for Census 2020 PUMA delineation. PUMAs are "Public Use Microdata Areas." They are large, contiguous areas of 100,000+ population, built up from census tracts and counties. Here's the main Census Bureau page on PUMA 2020: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/…<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.censu…> The Census Bureau will be kicking off the program in September 2021 (next month!). This will be an announcement to each State Data Center points of contact. If you're an MPO, you might be part of your state's State Data Center Network (as an affiliate data center, regional data center, etc.) Get in touch with your state's SDC. It will be each SDC that provides proposed PUMAs to the Census Bureau. The actual work on defining the new Census 2020 based PUMAs will be November 2021 through January 2022, with the "final" 2020 PUMAs published by summer 2022. My key point: the PUMAs are NOT just for use in the Public Use Microdata Sample, but are used as STANDARD tabulations for the American Community Survey, both the 1-year and 5-year products. As such, the PUMAs can be thought of as "Regional Analysis Districts" or "Superdistricts" or "Regional Districts." They can be SUPER useful in MPO transportation planning analyses. Here is the Census Bureau's statement on the usefulness of PUMAs, from the "Final Criteria" document: "In addition to PUMS data publication, as the ACS was developed and implemented after the 2000 Census, standard PUMAs were adopted as a basic tabulation geographic entity to present summary data. This was in response to concerns raised by SDCs and other stakeholders that the minimum population thresholds for tabulation and dissemination of 1-year and 3-year ACS data (65,000 and 20,000 persons, respectively) would limit the availability of data for the predominantly rural portions of states as well as for many counties. PUMAs met these population size requirements for all ACS data tabulations and their adoption resulted in a substantially larger community of PUMA data users, many of whom do not use PUMS files. This sustained interest in PUMA geography and associated data is expected to continue, therefore the PUMA criteria and guidelines for the 2020 Census are intended to help maintain a stable and comparable dataset." [from: Final Criteria for Public Use Microdata Area for the 2020 Census and the American Community Survey] Note that the current set of Census 2020 PL 94-171 data files do NOT have PUMAs as a standard summary level. This is because the Census 2020 includes the 2020 Census Tracts, and the current PUMAs are based on the 2010 Census Tracts. My recommendation for MPO staffs. To me this is a GIS-heavy process: 1. Map the Census 2010 Census Tracts and PUMAs. 2. Map the Census 2020 Census Tracts. Ideally the 2020 tracts nest within the 2010 tracts, but boundaries do indeed change. 3. Develop an equivalency between 2020 Census Tracts and 2010 PUMAs. 4. Use PL 94-171 data to get Census 2020 census tracts, and aggregated to approximate the 2010 PUMAs. 5. If the county is > 200,000 population, consider how to best re-draw PUMA boundaries. 6. It's a jigsaw puzzle, where none of the potential PUMAs can be less than 100,000. Consider this as "redistricting for MPOs" 7. Involve local actors who are interested: counties, cities, academics, nonprofits, etc. 8. Consider the Bureau's advice on "stable and comparable dataset"... Sometimes you may just keep the old PUMAs! Hope this is of interest: Chuck Purvis, Hayward, California

3 years, 11 months

CTPP Data Access Software Basics on September 22 at 2-4 pm ET

by Elzinga, Kyla

Hi all, Join us on Wednesday, September 22 at 2-4 pm ET for a CTPP training course on software basics: CTPP Data Access Software Basics on September 22 at 2-4 pm ET The CTPP Program is offering a two-hour training session where you'll learn the basics of the CTPP data access software. You'll learn how to navigate the software, select geographies, find tables, and more! Click the link below to register today. https://aashto.adobeconnect.com/software1/event/registration.html This is the start of a new monthly training series that will cover a range of topics, including basic and advanced software instruction, data issues, charts and graphs, feature presentations, and more. Hope to see you there! Team CTPP

3 years, 11 months

None

by None

I would like to invite you to provide your insight and advice on the methodol= ogies employed and products developed by the American Community Survey (ACS) = Program. In December of 2010, the ACS program released its first five-year da= ta products. With this important milestone achieved, we decided that a compre= hensive assessment of the ACS program was prudent to ensure its continued eff= ectiveness. I commissioned the ACS Program Review Team to plan and implement = this assessment. As a key stakeholder and advocate of the ACS program, your a= ssistance will help us obtain a broad and more robust perspective, as we cont= inue to shape our program in the coming years. We are offering the following = information sharing and engagement options: * Provide recommendations and comments by completing an online feedback form = (http://www.census.gov/acs/www/about_the_survey/program_review_feedback/ <htt= p://links.govdelivery.com:80/track?type=3Dclick&enid=3DZWFzPTEmbWFpbGluZ2lkPT= IwMTIwMjIxLjU3MDc1NjEmbWVzc2FnZWlkPU1EQi1QUkQtQlVMLTIwMTIwMjIxLjU3MDc1NjEmZGF= 0YWJhc2VpZD0xMDAxJnNlcmlhbD0xNjg4NDMxMiZlbWFpbGlkPXB3ZWluYmVyZ2VyQGFhc2h0by5v= cmcmdXNlcmlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmZmw9JmV4dHJhPU11bHRpdmFyaWF0ZUlkP= SYmJg=3D=3D&&&100&&&http://www.census.gov/acs/www/about_the_survey/program_… view_feedback/> ) or filling in a Word Document and sending it to ACS.Program= .Review(a)census.gov;=20 * Learn more by visiting our website (http://www.census.gov/acs/www/about_the= _survey/acs_program_review/ <http://links.govdelivery.com:80/track?type=3Dcli= ck&enid=3DZWFzPTEmbWFpbGluZ2lkPTIwMTIwMjIxLjU3MDc1NjEmbWVzc2FnZWlkPU1EQi1QUkQ= tQlVMLTIwMTIwMjIxLjU3MDc1NjEmZGF0YWJhc2VpZD0xMDAxJnNlcmlhbD0xNjg4NDMxMiZlbWFp= bGlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmdXNlcmlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmZ= mw9JmV4dHJhPU11bHRpdmFyaWF0ZUlkPSYmJg=3D=3D&&&101&&&http://www.census.gov/a… /www/about_the_survey/acs_program_review/> ); or * Ask questions by attending an interactive webinar where we will provide det= ails about the program review. To this email, I have attached the feedback template and the PowerPoint prese= ntation that we will use to facilitate the webinar. Any feedback collected fr= om you by the ACS Program Review Team will be shared with a National Research= Council panel, which is conducting an independent review of the ACS program.= =20 A member of the ACS Program Review Team will follow up with you shortly to pr= ovide logistics on the program review webinar.=20 Thank you in advance for any feedback you wish to provide. =20 * ACS Program Review Briefing Slides 2-21-12.pdf <http://links.govdelivery.co= m:80/track?type=3Dclick&enid=3DZWFzPTEmbWFpbGluZ2lkPTIwMTIwMjIxLjU3MDc1NjEmbW= Vzc2FnZWlkPU1EQi1QUkQtQlVMLTIwMTIwMjIxLjU3MDc1NjEmZGF0YWJhc2VpZD0xMDAxJnNlcml= hbD0xNjg4NDMxMiZlbWFpbGlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmdXNlcmlkPXB3ZWluYmVy= Z2VyQGFhc2h0by5vcmcmZmw9JmV4dHJhPU11bHRpdmFyaWF0ZUlkPSYmJg=3D=3D&&&102&&&http= ://content.govdelivery.com/attachments/USCENSUS/2012/02/21/file_attachments/9= 6415/ACS%2BProgram%2BReview%2BBriefing%2BSlides%2B2-21-12.pdf>=20 * ACS Program Review Feedback Form - Word pre-2007.doc <http://links.govdeliv= ery.com:80/track?type=3Dclick&enid=3DZWFzPTEmbWFpbGluZ2lkPTIwMTIwMjIxLjU3MDc1= NjEmbWVzc2FnZWlkPU1EQi1QUkQtQlVMLTIwMTIwMjIxLjU3MDc1NjEmZGF0YWJhc2VpZD0xMDAxJ= nNlcmlhbD0xNjg4NDMxMiZlbWFpbGlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmdXNlcmlkPXB3ZW= luYmVyZ2VyQGFhc2h0by5vcmcmZmw9JmV4dHJhPU11bHRpdmFyaWF0ZUlkPSYmJg=3D=3D&&&103&= &&http://content.govdelivery.com/attachments/USCENSUS/2012/02/21/file_attachm= ents/96400/ACS%2BProgram%2BReview%2BFeedback%2BForm%2B-%2BWord%2Bpre-2007.doc= >=20 * ACS Program Review Feedback Form - Word 2007 .docx <http://links.govdeliver= y.com:80/track?type=3Dclick&enid=3DZWFzPTEmbWFpbGluZ2lkPTIwMTIwMjIxLjU3MDc1Nj= EmbWVzc2FnZWlkPU1EQi1QUkQtQlVMLTIwMTIwMjIxLjU3MDc1NjEmZGF0YWJhc2VpZD0xMDAxJnN= lcmlhbD0xNjg4NDMxMiZlbWFpbGlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmdXNlcmlkPXB3ZWlu= YmVyZ2VyQGFhc2h0by5vcmcmZmw9JmV4dHJhPU11bHRpdmFyaWF0ZUlkPSYmJg=3D=3D&&&104&&&= http://content.govdelivery.com/attachments/USCENSUS/2012/02/21/file_attachm… ts/96401/ACS%2BProgram%2BReview%2BFeedback%2BForm%2B-%2BWord%2B2007%2B.docx> = =20 =20 ________________________________ US Census Bureau <http://links.govdelivery.com:80/track?type=3Dclick&enid=3DZ= WFzPTEmbWFpbGluZ2lkPTIwMTIwMjIxLjU3MDc1NjEmbWVzc2FnZWlkPU1EQi1QUkQtQlVMLTIwMT= IwMjIxLjU3MDc1NjEmZGF0YWJhc2VpZD0xMDAxJnNlcmlhbD0xNjg4NDMxMiZlbWFpbGlkPXB3ZWl= uYmVyZ2VyQGFhc2h0by5vcmcmdXNlcmlkPXB3ZWluYmVyZ2VyQGFhc2h0by5vcmcmZmw9JmV4dHJh= PU11bHRpdmFyaWF0ZUlkPSYmJg=3D=3D&&&105&&&http://www.census.gov/>=20 Questions? 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3 years, 11 months

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to get the data on the AASHTO website, but there was a steep learning curve, and the CB did not supply any TEST data for the software developer to use, only empty table shells. Being an optimist, it would presumably take less than 4 months in the next iteration, however, the very large number of TAZs and census tracts are likely to give any software vendor a headache, especially with the flow tabulations (Part 3). Elaine _______________________________________________ ctpp-news mailing list ctpp-news(a)chrispy.net http://www.chrispy.net/mailman/listinfo/ctpp-news --===============3554036712987317292== Content-Type: text/html Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="attachment.htm" MIME-Version: 1.0 DQo8YnI+PGZvbnQgc2l6ZT0yIGZhY2U9InNhbnMtc2VyaWYiPlRoYW5rIHlvdSwgRWxhaW5lLjwv Zm9udD4NCjxicj4NCjxicj48Zm9udCBzaXplPTIgZmFjZT0ic2Fucy1zZXJpZiI+RGlhbmEgUG9y dGlsbG8sIFJlc2VhcmNoIFByb2dyYW0gU3BlY2lhbGlzdDxicj4NCk9mZmljZSBvZiBUcmF2ZWwg Rm9yZWNhc3RpbmcgYW5kIEFuYWx5c2lzPGJyPg0KVHJhbnNwb3J0YXRpb24gU3lzdGVtIEluZm9y bWF0aW9uPGJyPg0KOTE2LTY1My0zMTgyPGJyPg0KPC9mb250Pg0KPGJyPg0KPGJyPg0KPGJyPg0K PHRhYmxlIHdpZHRoPTEwMCU+DQo8dHIgdmFsaWduPXRvcD4NCjx0ZCB3aWR0aD00MCU+PGZvbnQg c2l6ZT0xIGZhY2U9InNhbnMtc2VyaWYiPjxiPiZsdDtFbGFpbmUuTXVyYWthbWlAZG90LmdvdiZn dDs8L2I+DQo8L2ZvbnQ+DQo8YnI+PGZvbnQgc2l6ZT0xIGZhY2U9InNhbnMtc2VyaWYiPlNlbnQg Ynk6ICZsdDtjdHBwLW5ld3MtYm91bmNlc0BjaHJpc3B5Lm5ldCZndDs8L2ZvbnQ+DQo8cD48Zm9u dCBzaXplPTEgZmFjZT0ic2Fucy1zZXJpZiI+MDMvMTUvMjAxMSAwMzo1MCBQTTwvZm9udD4NCjx0 YWJsZSBib3JkZXI+DQo8dHIgdmFsaWduPXRvcD4NCjx0ZCBiZ2NvbG9yPXdoaXRlPg0KPGRpdiBh bGlnbj1jZW50ZXI+PGZvbnQgc2l6ZT0xIGZhY2U9InNhbnMtc2VyaWYiPlBsZWFzZSByZXNwb25k IHRvPGJyPg0KJmx0O2N0cHAtbmV3c0BjaHJpc3B5Lm5ldCZndDs8L2ZvbnQ+PC9kaXY+PC90YWJs ZT4NCjxicj4NCjx0ZCB3aWR0aD01OSU+DQo8dGFibGUgd2lkdGg9MTAwJT4NCjx0ciB2YWxpZ249 dG9wPg0KPHRkPg0KPGRpdiBhbGlnbj1yaWdodD48Zm9udCBzaXplPTEgZmFjZT0ic2Fucy1zZXJp ZiI+VG88L2ZvbnQ+PC9kaXY+DQo8dGQ+PGZvbnQgc2l6ZT0xIGZhY2U9InNhbnMtc2VyaWYiPiZs dDtjdHBwLW5ld3NAY2hyaXNweS5uZXQmZ3Q7PC9mb250Pg0KPHRyIHZhbGlnbj10b3A+DQo8dGQ+ DQo8ZGl2IGFsaWduPXJpZ2h0Pjxmb250IHNpemU9MSBmYWNlPSJzYW5zLXNlcmlmIj5jYzwvZm9u dD48L2Rpdj4NCjx0ZD4NCjx0ciB2YWxpZ249dG9wPg0KPHRkPg0KPGRpdiBhbGlnbj1yaWdodD48 Zm9udCBzaXplPTEgZmFjZT0ic2Fucy1zZXJpZiI+U3ViamVjdDwvZm9udD48L2Rpdj4NCjx0ZD48 Zm9udCBzaXplPTEgZmFjZT0ic2Fucy1zZXJpZiI+W0NUUFBdIENUUFAgNS15ZWFyICgyMDA2LTIw MTAgQUNTKSBzY2hlZHVsZTwvZm9udD48L3RhYmxlPg0KPGJyPg0KPHRhYmxlPg0KPHRyIHZhbGln bj10b3A+DQo8dGQ+DQo8dGQ+PC90YWJsZT4NCjxicj48L3RhYmxlPg0KPGJyPg0KPGJyPg0KPGJy Pjxmb250IHNpemU9MiBmYWNlPSJDYWxpYnJpIj5IaSBEaWFuYSDigJMgSSB0aG91Z2h0IEkgaGFk IHJlc3BvbmRlZCB0bw0KeW91ciBxdWVyeSwgYnV0IEkgd2FzIGxvb2tpbmcgYXQgdGhlIGxpc3Rz ZXJ2IGFyY2hpdmUgYW5kIHNhdyB0aGF0IGl0IHdhcw0Kbm90IGFuc3dlcmVkIG9uIHRoZSBDVFBQ IGxpc3RzZXJ2LiA8L2ZvbnQ+DQo8YnI+PGZvbnQgc2l6ZT0yIGZhY2U9IkNhbGlicmkiPiZuYnNw OzwvZm9udD4NCjxicj48Zm9udCBzaXplPTIgZmFjZT0iQ2FsaWJyaSI+VGhlIGN1cnJlbnQgZXhw ZWN0YXRpb25zIGFyZSB0aGF0IHRoZSBDQg0Kd291bGQgZGVsaXZlciB0byBBQVNIVE8gYSBDVFBQ IDUteWVhciBmaWxlICh3aXRoIFRBWiBhbmQgVEFEIGFzIHRhYnVsYXRpb24NCmdlb2dyYXBoeSkg YnkgRGVjZW1iZXIgJm5ic3A7MzEsIDIwMTIuICZuYnNwO0J1dCwgdGhlbiwgQUFTSFRPIHdvdWxk IG5lZWQNCnRvIHdvcmsgd2l0aCBzb21lb25lIGZvciB3ZWItYmFzZWQgZGF0YSBhY2Nlc3MuICZu YnNwO0ZvciB0aGUgQ1RQUCAyMDA2LTIwMDgsDQpCZXlvbmQgMjAyMCBpcyB0aGUgbWFpbiBjb250 cmFjdG9yLiAmbmJzcDtGcm9tIHRoZSB0aW1lIHRoZSBDQiBkZWxpdmVyZWQNCnRoZSBDVFBQIDMt eWVhciBmaWxlLCBpdCB0b29rIG92ZXIgNCBtb250aHMgdG8gZ2V0IHRoZSBkYXRhIG9uIHRoZSBB QVNIVE8NCndlYnNpdGUsIGJ1dCB0aGVyZSB3YXMgYSBzdGVlcCBsZWFybmluZyBjdXJ2ZSwgYW5k IHRoZSBDQiBkaWQgbm90IHN1cHBseQ0KYW55IFRFU1QgZGF0YSBmb3IgdGhlIHNvZnR3YXJlIGRl dmVsb3BlciB0byB1c2UsIG9ubHkgZW1wdHkgdGFibGUgc2hlbGxzLg0KJm5ic3A7ICZuYnNwOyBC ZWluZyBhbiBvcHRpbWlzdCwgaXQgd291bGQgcHJlc3VtYWJseSB0YWtlIGxlc3MgdGhhbiA0IG1v bnRocw0KaW4gdGhlIG5leHQgaXRlcmF0aW9uLCBob3dldmVyLCB0aGUgdmVyeSBsYXJnZSBudW1i ZXIgb2YgVEFacyBhbmQgY2Vuc3VzDQp0cmFjdHMgYXJlIGxpa2VseSB0byBnaXZlIGFueSBzb2Z0 d2FyZSB2ZW5kb3IgYSBoZWFkYWNoZSwgZXNwZWNpYWxseSB3aXRoDQp0aGUgZmxvdyB0YWJ1bGF0 aW9ucyAoUGFydCAzKS4gPC9mb250Pg0KPGJyPjxmb250IHNpemU9MiBmYWNlPSJDYWxpYnJpIj4m bmJzcDs8L2ZvbnQ+DQo8YnI+PGZvbnQgc2l6ZT0yIGZhY2U9IkNhbGlicmkiPkVsYWluZTwvZm9u dD4NCjxicj48Zm9udCBzaXplPTIgZmFjZT0iQ2FsaWJyaSI+Jm5ic3A7PC9mb250Pg0KPGJyPjxm b250IHNpemU9MiBmYWNlPSJDYWxpYnJpIj4mbmJzcDs8L2ZvbnQ+DQo8YnI+PGZvbnQgc2l6ZT0y IGZhY2U9IkNhbGlicmkiPiZuYnNwOzwvZm9udD48Zm9udCBzaXplPTI+PHR0Pl9fX19fX19fX19f X19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fX19fPGJyPg0KY3RwcC1uZXdzIG1haWxp bmcgbGlzdDxicj4NCmN0cHAtbmV3c0BjaHJpc3B5Lm5ldDxicj4NCmh0dHA6Ly93d3cuY2hyaXNw eS5uZXQvbWFpbG1hbi9saXN0aW5mby9jdHBwLW5ld3M8YnI+DQo8L3R0PjwvZm9udD4NCjxicj4N Cg== --===============3554036712987317292==--

3 years, 11 months

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3 years, 11 months

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3 years, 11 months

Comparing CTPPr and Beyond 2020 for retrieving CTPP2012/16 data

by Charles Purvis

I was looking for a convenient way to download specific tables from the 2012/16 CTPP package. I have found that there are two main methods to consider: using the web-based Beyond 2020 software; and using the r-package CTPPr created by Westat. The R-Package CTPPr The CTPPr package is great for downloading simple, one-cell tables, but gets complicated in multi-cell tables (which is most of the tables!!!) The issue is that CTPPr extracts the CTPP data in “list” format with just a few columns: geography, characteristic #1, estimate and margin of error. With a simple one-dimensional table, it outputs four columns, So, a simple table such as means of transportation to work (18) will have eighteen records (rows) of data for each piece of geography. A simple two-way table, say Table A104201 (Vehicles Available (6) by Poverty Status (4)), will have 24 records (rows) per piece of geography. A detailed two-way table, say Table A102214 (Occupation (25) by Industry (15)), will have 375 records (rows) of data per unit of geography. That’s a long database. On the other hand, the r-package TIDYCENSUS can output the decennial census and ACS databases in either “LIST” format or “WIDE” format. See the TIDYCENSUS documentation of when you would choose the long “LIST format versus the “WIDE” format. The “WIDE” format would produce one record (row) of data for each piece of geography. So, a two-way table of 6 by 4 would yield 49 columns: the geography, the 24 estimates, and the 24 margins of errors. Unforturnately the CTPPr package does not export data in “WIDE” format i.e., one record per each geographic area. And I don’t have the R skill sets to convert this type of data frame from a LIST to WIDE format, and creatively updating variable names to be more mnemonic, and memorable! Beyond 2020 for the CTPP The web-based software “Beyond 2020” has been developed for the Census Transportation Planning Products (CTPP) as an AASHTO, USDOT, and the CTPP Oversight Board. It’s a State DOT funded, cooperative program with many actors and moving pieces. The AASHTO home page for the CTPP is here: https://ctpp.transportation.org/ <https://ctpp.transportation.org/> The AASHTO page for retrieving CTPP data is here: http://data5.ctpp.transportation.org/ <http://data5.ctpp.transportation.org/> Or bookmark this page for the introduction page to Beyond 2020 for the CTPP2012/16. http://data5.ctpp.transportation.org/ctpp1216/Browse/browsetables.aspx <http://data5.ctpp.transportation.org/ctpp1216/Browse/browsetables.aspx> 1. Sign in. You need to be registered (it’s free) to use the Beyond2020/CTPP software. The “sign in” button is hiding in the upper right hand quadrant of the web page. Remember your username and password. 2. Explore the upper middle bar. This “gray” bar from left to right shows “data set” in a drop down menu, and Selected Geography in two drop-down menus for RESIDENCE geography and WORKPLACE geography. This is key. The user will probably want to define several sets of residence and workplace geographies for their geo-areas of interest. a. What I consider key in selecting geographies is to get the labels right. There’s a pull-down menu in the “select labels” panel in geo-selection panel that opts for “name” or “key” or “FIPS Code” or “FIPS and Name” or “Split FIPS Code”. I like the “FIPS and Name” option, since this returns the detailed FIPS code with a detailed “Name” of the geography, e.g., “Census tract 4001.00 in Alameda County, California”. The FIPS code would be “06001400100” for that particular tract! b. Save the geographic selection. Use names that make sense. Override or delete geographic selection sets until you get everything right! 3. Select the table of interest. A simple one-way table, say, A102103 (workers by class of worker (9)) will have 19 columns: a column for the geography, and columns for each of the 9 estimates, and 9 margins of error. 4. A complex two-way table, say, A102214 (workers by occupation (25) by Industry (15)) will have 750 columns!! 5. Check to be sure that the geography label is correct. Again, I prefer having both the FIPS code and the area name showing! 6. Download the table. As with most software, there are usually more than one way to do this: the “file” menu in the upper left hand corner of the web page, and a “green arrow pointing down” in the middle top row. a. I usually opt for “comma-delimited ASCII format (*.csv), with the “data format” using “multi-dimensional”. This is most similar to what you see in your current table view. b. Test the “list format”… this will give you a narrow, but long database! c. Test the “XML format”. You can open up the XML file in Excel, and the formatting is almost the same as you see in your Beyond 2020 session. If your intent is a detailed table that’s almost ready for publication, this is a good bet. d. Test the “ESRI shapfile (*.shp)” file format. This works great in producing a GIS-ready SHP file, but the variable names are basically useless, e.g., a simple two-way table, say household size (5) by vehicles available (6) will return 60 columns of data plus the geography column. The variables will be named “F0” through “F59”. Maybe there are batch processes that will rename variable names in DBF file? Maybe an option is to import the DBF file associated with SHP file into the R-package, then have a script which renames the variables for the simple one-way or two-way tables using the analyst’s mnemonic (memory-jogging) variable names. For me, “PHH1_VHH0_E” is a good mnemonic name for the Estimate of one-person, zero-vehicle households! e. I created an R-script which reads in the DBF exported from Beyond 2020, for Table A202105 (Means of Transportation to Work (18)), for the 58 California counties-of-work. It uses the R package “dplyr” to rename variable F0 through F35 to something more friendly, like “dralone_est” and “athome_moe”. I add a few new variables like carpool 2+, carpool 3+ and “transit”, then export the R data frame to both a DBF (readable by the GIS!) and XLSX Excel format. f. Renaming variables in either Excel or this R package method is quite a chore. But if your intent is to get Excel tables that are almost “ready to print” then I would suggest exporting data from Beyond 2020 in XML format. If your intent is to have a simply variable name for use in GIS or other statistical analyses, then either edit the Excel file (add a row and create your own variable names) or use the R package to rename variables. Attached is my r-script to rename variables exported from Beyond 2020 in SHP file format. Hope this is of use. I started work on this earlier this month. I forgot I wanted to share it. Chuck Purvis, Hayward, California.

3 years, 11 months

NPR Article on race alone plus race in combination

by Charles Purvis

This is a fascinating, excellent article by Hansi Lo Wang and Ruth Talbot for the National Public Radio: https://www.npr.org/2021/08/22/1029609786/2020-census-data-results-white-po… <https://www.npr.org/2021/08/22/1029609786/2020-census-data-results-white-po…> “This is How the White Population is Actually Changing Based on New Census Data” The article is a must read if you’re interested in race/ethnicity in Census Bureau data. They basically used the PL 94-171 data to tally up the persons who ticked off “white” as well as “white” plus any other racial group. I did this (for the Bay Area) using the 2010 Census data, in Excel. But this was excruciating given the number of combinations in a 70 cell table. I am hoping that some enterprising analyst has created R-package code to take PL 94-171 data (using the R package PL94171) and create these extra variables: white alone plus white in combination with other races black alone plus black in combination with other races asian alone plus asian in combination with other races NHOPI alone plus NHOPI in combination with other races AIAN alone plus AIAN in combination with other races other alone plus other in combination with other races NHOPI = Native Hawaiian or Other Pacific Islander AIAN = American Indian or Alaskan Native. Anybody willing to share their R code???? cheers, Chuck Purvis, Hayward, California

3 years, 11 months

Re: Defining PUMAs for Census 2020 When will the 2020 Census Summary File #1 be released?

by Graham, Todd

Hi Chuck- RE: QUESTION: When will the 2020 Census Summary File #1 be released? Census Bureau announced in 2019 that the product formerly known as SF1 would be reduced -- fewer tables, especially fewer crosstabs -- and that the new collection of tables would be called Demographic & Housing Characteristics (DHC). I have not seen any news lately on what the final set of DHC tables will include. It's possible that this is *still* unsettled? I am not surprised that you found nothing on census.gov. Census execs were earlier promising DHC as a product... but then in 2021 they pivoted to: make no promises of anything. They scrubbed mentions of DHC off of census.gov. (oh. But they didn't get everything... https://www2.census.gov/about/partners/cac/nac/meetings/2021-05/presentatio… ) WHEN will we see the DHC product? was asked by journalists at the August 12 webcast press conference - and Census spokespeople would not answer the question. Hopefully we get DHC product sometime in 2022. Earlier than 2022 seems unlikely because DAS/Differential Privacy processing is going to add multiple months. But I would be guessing. Again, If someone has actual intel, point us there! --TG [Metropolitan Council Logo] Todd Graham Principal Forecaster | Research Metropolitan Council 390 North Roberrt Street, St. Paul, MN 55101 Ph. 651-602-1322 metrocouncil.org<https://www.metrocouncil.org/data> | facebook<https://www.facebook.com/MetropolitanCouncil> | twitter<https://twitter.com/metcouncilnews> From: Charles Purvis <clpurvis(a)att.net> Sent: Wednesday, August 25, 2021 1:31 PM To: The Census Transportation Products Program Community of Practice/Users discussion and news list <ctpp(a)listserv.transportation.org> Subject: [CTPP News] Re: Defining PUMAs for Census 2020 Todd: The pro-tips on building PUMAs (discourage splitting counties; encourage consistency with city boundaries) make great sense. (I've had a lot of fun using the POWPUMA data from PUMS. In California we have 58 counties and 41 POWPUMAs. Good for trying to analyze county-to-county commute patterns over the years.) QUESTION: When will the 2020 Census Summary File #1 be released? I can't find the information on the Census Bureau's website. My hunch is that it will be about four months after the PL 94-171 data is released, perhaps by December 2021??? The SF1 (STF1A to old-timers) will have the detailed "short form" tabulations including: households by household size, detailed age cohort tables; householder tables; detailed hispanic groups; detailed asian groups; owner/renter tenure; etc. Chuck On Aug 23, 2021, at 1:01 PM, Graham, Todd <todd.graham(a)metc.state.mn.us<mailto:todd.graham@metc.state.mn.us>> wrote: Hi Chuck- Thanks for the heads-up. Yes, that is the way to think of PUMAs = as "super-districts" or sub-state regions. Here are my "pro-tips" learned in PUMA drawing 10 years ago: 1. Do not group together fractional pieces of counties when you could keep a county whole, or when you could group multiple whole counties together in a PUMA. 2. When splitting counties into multiple PUMAs, try to arrange for the split lines to be stable city/town boundaries. This means you're looking to create PUMAs where city/town boundaries are aligned with Tract boundaries. (Because Census Geog Dept will require that tracts be the basic units of PUMA assembly.) The reason I emphasize parsimony with counties in point #1 is: The PUMAs you draw will enable or limit the detail of MIGPUMAs as well. (MIGPUMA= Migration origination geographic units) Census Bureau will create MIGPUMAs as the least common denominator grouping of counties that is entirely coincident with a group of PUMAs. So don't split counties unnecessarily. The reason I emphasize city/town boundaries in point #2 -- even though Census Geog discusses tracts as the basic units - is this: The PUMAs you draw will enable or limit the detail of POWPUMAs. (POWPUMAs = Place of Work geographic units) Census Bureau will create POWPUMAs as the least common denominator grouping of counties + places that is entirely coincident with a group of PUMAs. Stated differently: Census looks for combinations of county + place to uniquely nest within a POWPUMA. Why is this the standard for POWPUMAs? It's because of the questions asked on ACS: ACS asks specifically for the county + place of one's work location. The PUMA final criteria document https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/…<https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.censu…> does say all this, but you'd have to read all the way to the last 3 pages of that document to find it. That's all my advice. Good luck! --Todd Graham

3 years, 11 months

Defining PUMAs for Census 2020

by Charles Purvis

The Census Bureau is ramping up efforts for Census 2020 PUMA delineation. PUMAs are “Public Use Microdata Areas.” They are large, contiguous areas of 100,000+ population, built up from census tracts and counties. Here’s the main Census Bureau page on PUMA 2020: https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/… <https://www.census.gov/programs-surveys/geography/guidance/geo-areas/pumas/…> The Census Bureau will be kicking off the program in September 2021 (next month!). This will be an announcement to each State Data Center points of contact. If you’re an MPO, you might be part of your state’s State Data Center Network (as an affiliate data center, regional data center, etc.) Get in touch with your state’s SDC. It will be each SDC that provides proposed PUMAs to the Census Bureau. The actual work on defining the new Census 2020 based PUMAs will be November 2021 through January 2022, with the “final” 2020 PUMAs published by summer 2022. My key point: the PUMAs are NOT just for use in the Public Use Microdata Sample, but are used as STANDARD tabulations for the American Community Survey, both the 1-year and 5-year products. As such, the PUMAs can be thought of as “Regional Analysis Districts” or “Superdistricts” or “Regional Districts.” They can be SUPER useful in MPO transportation planning analyses. Here is the Census Bureau’s statement on the usefulness of PUMAs, from the “Final Criteria” document: "In addition to PUMS data publication, as the ACS was developed and implemented after the 2000 Census, standard PUMAs were adopted as a basic tabulation geographic entity to present summary data. This was in response to concerns raised by SDCs and other stakeholders that the minimum population thresholds for tabulation and dissemination of 1-year and 3-year ACS data (65,000 and 20,000 persons, respectively) would limit the availability of data for the predominantly rural portions of states as well as for many counties. PUMAs met these population size requirements for all ACS data tabulations and their adoption resulted in a substantially larger community of PUMA data users, many of whom do not use PUMS files. This sustained interest in PUMA geography and associated data is expected to continue, therefore the PUMA criteria and guidelines for the 2020 Census are intended to help maintain a stable and comparable dataset.” [from: Final Criteria for Public Use Microdata Area for the 2020 Census and the American Community Survey] Note that the current set of Census 2020 PL 94-171 data files do NOT have PUMAs as a standard summary level. This is because the Census 2020 includes the 2020 Census Tracts, and the current PUMAs are based on the 2010 Census Tracts. My recommendation for MPO staffs. To me this is a GIS-heavy process: 1. Map the Census 2010 Census Tracts and PUMAs. 2. Map the Census 2020 Census Tracts. Ideally the 2020 tracts nest within the 2010 tracts, but boundaries do indeed change. 3. Develop an equivalency between 2020 Census Tracts and 2010 PUMAs. 4. Use PL 94-171 data to get Census 2020 census tracts, and aggregated to approximate the 2010 PUMAs. 5. If the county is > 200,000 population, consider how to best re-draw PUMA boundaries. 6. It’s a jigsaw puzzle, where none of the potential PUMAs can be less than 100,000. Consider this as “redistricting for MPOs" 7. Involve local actors who are interested: counties, cities, academics, nonprofits, etc. 8. Consider the Bureau’s advice on “stable and comparable dataset”… Sometimes you may just keep the old PUMAs! Hope this is of interest: Chuck Purvis, Hayward, California

3 years, 11 months

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