CTPP

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3041 discussions

CTPP commuter flows in strong MCD states (Vermont test case)

by Charles Purvis

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 <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

3 years, 4 months

Comparing CTPP Total Workers at various geographic summary levels

by Charles Purvis

This may be of interest to users of the 2012-2016 CTPP. The Part 3 journey-to-work “flow” tables DO INCLUDE the Census Bureau’s (primary) allocation of workers to county-of-work, and place-of-work (and by extension, POWPUMA-of-work, since all POWPUMAs are single counties or groups of counties). So, the user can readily match the CTPP commuter flows with “standard” American Community Survey 2012-16 tables (retrieved via data.census.gov <http://data.census.gov/> or the r-package “tidycensus”). On the other hand, the Part 3 CTPP tables DO NOT INCLUDE the “extended” allocation of workers, that is, allocated (imputed) to the tract, TAZ or TAD of workplace. I really can’t point to the documentation where this is made any clearer. So, I examined the county-to-county total commuters (CTPP Table A302301) for 9 states, plus the Northern California Mega-Region (24 counties). I then compared the county-to-county total commuters to the tract-to-tract summary level, summed to county-to-county level. The basic finding is that the tract-to-tract total commuter file is missing about 20 percent of the workers. They were *not* allocated (imputed) to the tract-of-work level. (I can think of dozens of strategies to handle this predicament.) Here’s a table summarizing these results. I’ve also uploaded my R-scripts for three states: Idaho, Alaska, and Delaware, to my GIST/Github:https://gist.github.com/chuckpurvis <https://gist.github.com/chuckpurvis> Can somebody double-check my work? Check it using datafiles downloaded from the Beyond 2020 CTPP and/or datafiles pulled using the r-package CTPPr. Sometimes CTPPr doesn’t work for VERY large data pulls, or even smaller areas (like Alaska state for whatever reason.) Hopefully this is worth discussing. cheers and Happy Pi Day! Chuck

3 years, 4 months

REMINDER: Upcoming CTPP Training: Getting to Know CTPP Data on Wednesday, March 16 at 2:00 pm Eastern

by Elzinga, Kyla

[https://files.constantcontact.com/ccfdce84701/6fbaaa3b-507d-401a-955f-0d632…] [https://files.constantcontact.com/ccfdce84701/dbea4755-7fcb-4bd8-9ae3-67fd3…] Join an Interactive CTPP Training on March 16! Getting to Know CTPP Data Wednesday, March 16th, 2022 - 2:00PM to 4:00PM ET The monthly CTPP training continues with the next session: Getting to Know CTPP Data. This two-hour training session will provide an overview of the custom data tabulations in the CTPP and cover topics such as ACS data collection, important information to know about what's included - and not - in the CTPP, and how CTPP compares with other data sources. You'll learn about how the data is collected, how to interpret the data, significance testing, the margin of error, and more! Click here to register today.<https://aashto.adobeconnect.com/ctppdata_march2022/event/registration.html> Course Format: * Overview of ACS data collection and what to know about ACS data * What is included - and not - in CTPP data * Comparison with other data sources REQUIREMENTS: * The Adobe Connect Application (download available here<https://r20.rs6.net/tn.jsp?f=001VnO5dqPjGkUbmkouH7lKD4lbbq0XCGj5qcebMbbIggo…>) * Upon registration, more background information will be provided that you should review on: * ACS Questionnaire * How to use Adobe Connect Registration is limited, so please reserve a seat only if you plan to attend live. This is part of a recurring monthly series on the third Wednesday of every month. Stay tuned for more information on the next session on April 20. Visit https://ctpp.transportation.org/upcoming-events/<https://r20.rs6.net/tn.jsp?f=001VnO5dqPjGkUbmkouH7lKD4lbbq0XCGj5qcebMbbIggo…> to stay up-to-date on future trainings and events.

3 years, 4 months

R script to use the package CTPPr, and TIDYVERSE: Households by Household Size by Vehicles Available by Tenure

by Charles Purvis

I’m still learning everything about sharing nicely. I’ve uploaded my r-script to my Github Gist. This might be a better way of “sharing code”? https://gist.github.com/chuckpurvis/281a786c06593afbf256f184a567a5ce <https://gist.github.com/chuckpurvis/281a786c06593afbf256f184a567a5ce> This script uses the R package CTPPr to pull the California place-level 2012-16 data on households by household size (5) by vehicles available (5) by Tenure (5). That’s a pretty complex table with 125 cells per geography. And CTPPr automatically downloads the standard estimate (SE, not the 90% Margin of Error), so that’s about 250 records per each piece of geography. Ouch. The function “pivot_wider” in the r package “dplyr” is used to rewrite the dataset from this “long” format to more of a “wide” format. It’s pulling the “estimates” (Households) separately from the “standard errors”, and then re-combining them. The result of this first phase is a data set with many fewer rows, and lots of columns with really long variable names. But there’s a solution! The next phase is to rename variables and re-code variable values into much shorter, mnemonic variable names, and then to do a new set of pivot_wider to create a data set with much easier to read variable names! I would STRONGLY recommend learning the R package “dplyr” if you’re going to be analyzing census data using either CTPPr or tidycensus. Take care, Chuck Purvis Hayward, California

3 years, 5 months

frataring commuter matrices in R

by Charles Purvis

Help! I’m trying to fratar (iterative proportional fitting, raking) a 58 by 58 commuter matrix using R packages. I could use some help. Attached are my initial scripts and input database to create the 58 by 58 “seed” matrix (2012-16 CTPP, Total Workers, Table A302100). I’m just a little mystified as to how to implement the raking/frataring given the different IPF packages available: Ipfp, mlfit, mipfp, rakeR, rake…… My goal is to rake the 58 by 58 county-to-county total commuters for California, using the 2012/2016 CTPP to estimates of individual years: 2012, 2013, 2014, 2015, 2016. Chuck

3 years, 5 months

Reminder: CTPP Data Access Software Advanced Training TODAY

by Elzinga, Kyla

[https://files.constantcontact.com/ccfdce84701/6fbaaa3b-507d-401a-955f-0d632…] [https://files.constantcontact.com/ccfdce84701/dbea4755-7fcb-4bd8-9ae3-67fd3…] Join an Interactive CTPP Training on February 16! CTPP Data Access Software Advanced Wednesday, February 16th, 2022 - 2:00PM to 4:00PM ET As a follow-up to the CTPP Data Access Software Basics course, the CTPP program is offering a two-hour training session that will dive even deeper into the capabilities of the CTPP data access software. In this interactive course, you will have the opportunity to work with your classmates to answer in-depth questions using the CTPP data and software. You'll learn how to display data as charts and maps, plot flow data, and more! Click here to register today.<https://aashto.adobeconnect.com/febsoftwareadvanced/event/registration.html> Course Format: * Brief introduction to the CTPP * Demonstration of advanced software functions * Interactive group exercise REQUIREMENTS: * The Adobe Connect Application (download available here<https://r20.rs6.net/tn.jsp?f=001JembHX17_C-B1Lt5rBccfoxndVjK5qQTgk8Ht9T3sjE…>) * Attendance of the CTPP Data Access Software Basics training OR familiarity with the basic software functions. Registration is limited, so please reserve a seat only if you plan to attend live. This is part of a recurring monthly series on the third Wednesday of every month. Stay tuned for more information on the next training on March 16. Visit https://ctpp.transportation.org/upcoming-events/<https://r20.rs6.net/tn.jsp?f=001JembHX17_C-B1Lt5rBccfoxndVjK5qQTgk8Ht9T3sjE…> to stay up-to-date on future trainings and events.

3 years, 5 months

New 5-year ACS data products to be released March 17, 2022

by Charles Purvis

The Census Bureau announced today that the 2016-2020 ACS data products will be released on St. Patrick’s Day: Thursday, March 17, 2022. This will allow analysts to examine three non-overlapping sets of five-year ACS products: 2006-2010, 2011-2015 and 2016-2020. https://www.census.gov/programs-surveys/acs/news/data-releases/2020/release… <https://www.census.gov/programs-surveys/acs/news/data-releases/2020/release…>

3 years, 5 months

Reminder: CTPP users survey - please participate

by Mohammadian, Abolfazl

Dear Colleague, Thanks to those who have already completed the survey. In case you overlooked the first email (and you are a transportation professional in the U.S.), please consider participating in this short survey<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY>, even if you are not a frequent CTPP user. I am helping AASHTO to understand how best to serve Census transportation data users. The survey<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY> takes about 15 minutes to complete. All of your responses will be private and will only be presented in aggregate format. FYI, the CTPP is a State DOT-funded, cooperative program that produces special tabulations of American Community Survey (ACS) data that have enhanced value for transportation planning, analysis, and strategic direction. This study<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY> is the first step to understand data utilization by the users’ community as well as determining the gaps in CTPP products that can be addressed by introducing new tables. Here is the link to the questionnaire: https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY Best Regards, Kouros --------------------------------------- Abolfazl (Kouros) Mohammadian, PhD Professor and Department Head Civil, Materials, and Environmental Engineering University of Illinois Chicago Co-Editor in Chief, Transportation Letters Associate Editor, Transportation Research Record Email: kouros(a)uic.edu<mailto:kouros@uic.edu> Twitter: @K_Mohammadian<https://twitter.com/K_Mohammadian> ---------------------------------------

3 years, 6 months

2020 ACS PUMS with Experimental Weights

by Charles Purvis

Questions: 1) Will the Census Bureau be developing and releasing a 2019 (yes, 2019) Public Use Microdata Sample (PUMS) using Experimental Weights? I’m not sure this is a simple-to-answer question, but it bears asking. The Census Bureau released (November 30, 2021) the Year 2020 ACS PUMS using Experimental Weights. And the iPUMS site just this week (1/25/22) launched the 2020 ACS PUMS-X on their wonderful/amazing website! Also on 11/30/21, the Bureau released the 54 tables that will be the sum total of regular tables on the 2020 ACS. There will be NO 2020 single-year estimates available either on data.census.gov <http://data.census.gov/> or through the API (application programming interface, like the R-package tidycensus.) These 54 tables are only available at the national and state level. Region, county and large place level data will (apparently) not be released for these 54 tables. I also read the working paper by Census Bureau staff: "Addressing Nonresponse Bias in the American Community Survey During the Pandemic Using Administrative Data” https://www.census.gov/library/working-papers/2021/acs/2021_Rothbaum_01.html <https://www.census.gov/library/working-papers/2021/acs/2021_Rothbaum_01.html> The Rothbaum working paper goes into incredible detail on the need to replace the traditional weights used in the ACS with experimental weights / new weights / “entropy balance weights” / “experimental entropy balance weights” / ACS experimental weights. The paper shows a lot of comparisons between older ACS data, typically 2009 to 2019, and ACS-X data with the experimental weights, for 2019 and 2020. Yes, the Census Bureau has implemented the experimental weighting procedure for 2019. The Bureau is pretty clear about data users NOT comparing the ACS 2005-2019 using the “standard weights” with the ACS 2020 using the experimental weights. Well, at least that’s their advice/admonition/plea. Year 2020 data is incomparable. It’s like 61* (Maris) versus 60 (Ruth). I think we need ACS-X data (ACS with Experimental Weights) for multiple years in order to make some sense out of this bedlam: 2019, 2020 and 2021. There’s obviously a major time and cost with creating these data, but it will be worth the investment. A followup question is: 2) Will the five-year 2016-2020 data, tentatively scheduled for release March 20, 2022 (plus or minus weeks?) be weighted using ACS standard weights? ACS experiment weights? A hybrid? I scoured the Census Bureaus’ website, read the transcript from the 11/30/21 webinar, scoured the state data center and ACS data community websites, and couldn’t find answers. Help? Chuck Purvis

3 years, 6 months

CTPP user survey - please participate

by Mohammadian, Abolfazl

Dear Colleague, If you are a transportation professional in the U.S., please consider participating in this short survey<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY>, even if you are not a frequent CTPP user. I am helping AASHTO to understand how best to serve Census transportation data users. The survey<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY> takes about 15 minutes to complete. All of your responses will be private and will only be presented in aggregate format. The CTPP is a State DOT-funded, cooperative program that produces special tabulations of American Community Survey (ACS) data that have enhanced value for transportation planning, analysis, and strategic direction. This study<https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY> is the first step to understand data utilization by the users’ community as well as determining the gaps in CTPP products that can be addressed by introducing new tables. Here is the link to the questionnaire: https://uic.ca1.qualtrics.com/jfe/form/SV_dolfGg2cMOoCuTY Best Regards, Kouros --------------------------------------- Abolfazl (Kouros) Mohammadian, PhD Professor and Department Head Civil, Materials, and Environmental Engineering University of Illinois Chicago Co-Editor in Chief, Transportation Letters Associate Editor, Transportation Research Record Email: kouros(a)uic.edu<mailto:kouros@uic.edu> Twitter: @K_Mohammadian<https://twitter.com/K_Mohammadian> ---------------------------------------

3 years, 6 months

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