Dara
Thank you for these materials. They are very helpful. After taking a closer look at the CTPP flow tables we are still left with a question about why the components of certain tables do not add up to the table total. For example when
we filter for Cambridge, MA as both residence and workplace, the “Total” shown in Table B303100 is 37,500 while the component cells add up to 22,470. This problem appears in all the part 3 tables whose universe is household workers. (We do not see a similar
issue in all tables based purely in worker characteristics, regardless of living arrangement. Those seem to consistently sum to 27,725.)
Can anyone shed light on why the table components to sum to the sum stated in the table?
Thanks
Cliff Cook
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From: Dara Goldberg (DCP) <DGoldberg@planning.nyc.gov>
Sent: Monday, August 12, 2019 11:13 AM
To: Cook, Cliff <ccook@cambridgema.gov>
Cc: Werner, Bailey <bwerner@cambridgema.gov>; Le Zhang (DCP) <LZHANG@planning.nyc.gov>
Subject: RE: 2012-16 CTPP Question about Counts
Hello Cliff,
The reason the flows are off is because the CTPP methodology for reporting geographies below the county level has been revised for this release (though AASHTO has yet to release documentation stating such). Missing records for smaller geographies
are no longer imputed for Parts 2 and 3, therefore, tracts/places will no longer add to counties, nor will they have complete counts. This has resulted in a “truer” data set, albeit with missing records. Part 1 remains the same (i.e. “complete”), because it
represents ACS data at place of residence. I’ve attached a memo summarizing the challenges with the new release.
My colleague Le, who I have CC’d, put together the attached presentation explaining this issue, which we shared with our MPO members a couple of months ago. Le will be presenting this to the CTPP oversight board in Arkansas next week. Unfortunately,
there was no documentation released accounting for the methodological change, and we believe transportation planners will rely on the current release to have a “complete” count as the prior releases had. Therefore, this release is not comparable to the prior
releases for smaller geographies.
In the meantime, we have assumed a proportional allocation to account for missing records (though this of course introduces a bias into the results – also covered in Le’s presentation).
Hopefully this helps! Happy to answer any questions you might have.
Regards,
DARA GOLDBERG
SENIOR PLANNER | REGIONAL PLANNING DIVISION
NYC DEPT. OF CITY PLANNING
120 BROADWAY, 31st FLOOR •
NEW YORK, NY 10271
212-720-3312 I
DGOLDBERG@planning.nyc.gov
From: ctpp-news [mailto:ctpp-news-bounces@chrispy.net]
On Behalf Of Cook, Cliff
Sent: Monday, August 12, 2019 10:58 AM
To: ctpp-news@chrispy.net
Cc: Werner, Bailey <bwerner@cambridgema.gov>
Subject: [CTPP] 2012-16 CTPP Question about Counts
We are working to collect information about the resident labor force in Cambridge, Massachusetts. We set the residence
as the State-Place of Cambridge city, MA, and the workplace as POW State-Place of Cambridge city, MA.
The numbers in the CTPP Flows tables are not adding up as expected. Table A304100 – Total workers (1) (Workers 16 years
and over) provides an estimate of 27,725 (MOE 847), whereas Table B303100 – Household income in the past 12 months (2016$) (9) (Workers 16 years and over in households) provides a total estimate of
37,300 (MOE 2,054). Furthermore, when we add up the count of workers in each income bracket in Table B303100 they sum to
22,470.
I could understand if the total number of resident workers 16 and older in households was smaller than total workers over
16, but we cannot make sense of how the reverse could be true. It also doesn’t explain why the sum of all categories is smaller than the listed total. Could data suppression account for this? That would seem unlikely at the level of a city of our size.
Could the results be due to data suppression at smaller geographic levels having a ripple effect on a larger geo? I understand workers with an unclear or imprecise work address are excluded from the flow data. Are these issues a result of that screening
or is this a different type of issue?
Interestingly, the numbers make sense as expected when we look at the Residence tables for the same geography. Table A102101
– Total workers (1) (Workers 16 years and over) provides an estimate of 61,925 (MOE 1,008) and Table A103100 – Total Workers in households (1) (Workers 16 years and over in households) estimates 54,195 (MOE 1,075).
Any help on interpreting our resident labor force stats is appreciated.
Cliff Cook
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