Lehd now has age and sex for data in the 2009 to 2001 series.
"Datasets for 2009-2011 contain additional variables (Race, Ethnicity,
Education, and Sex) on the Residence file (RAC) and Workplace (WAC)
files that are not available in other years of data. And datasets for
2011 contain further additional variables (Firm Age and Firm Size) on
the WAC files."
I haven't looked at any of this or played with it but it could be promising.
On 1/27/2014 10:22 AM, Liang.Long.CTR(a)dot.gov wrote:
Hi, Bob
LEHD doesn't have residence information. And I don't think LEHD provides
employment data by age and gender either.
Liang
________________________________________
From: ctpp-news-bounces(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on behalf of Robert
Shull [rshull(a)transportmodeler.com]
Sent: Friday, January 24, 2014 11:42 AM
To: ctpp-news(a)chrispy.net
Cc: u0719944(a)utah.edu; medicalgeography(a)yahoo.com; tyler.larson(a)utah.edu
Subject: Re: [CTPP] female daytime population
How would this compare with using LEHD?
Thanks,
Bob
Robert Shull, PE
President
Eco Resource Management Systems Inc.
PO Box 1850
Vashon, WA 98070
206.414.8751
rshull@transportmodeler.com<mailto:rshull@transportmodeler.com>
On Fri, Jan 24, 2014 at 8:37 AM,
<Elaine.Murakami@dot.gov<mailto:Elaine.Murakami@dot.gov>> wrote:
I didn't manage to send my response last night. I suggest you use the ACS PUMS
To run a 4-way cross tab of industry and occupation by age and sex. The geography is
limited to residential geography at Puma level.
-----Original Message-----
From: Long, Liang CTR (FHWA)
Sent: Friday, January 24, 2014 11:28 AM Eastern Standard Time
To: ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
Cc: u0719944@utah.edu<mailto:u0719944@utah.edu>;
medicalgeography@yahoo.com<mailto:medicalgeography@yahoo.com>;
tyler.larson@utah.edu<mailto:tyler.larson@utah.edu>
Subject: Re: [CTPP] female daytime population
Hi, Steve
Your methodology is totally fine with me.
I wish we had the cross table of sex by age for workers for both Part 1 and Part 2, so
you can get measures of female workers for 40 years up.
Liang
________________________________________
From: ctpp-news-bounces@chrispy.net<mailto:ctpp-news-bounces@chrispy.net>
[ctpp-news-bounces@chrispy.net<mailto:ctpp-news-bounces@chrispy.net>] on behalf of
Steven Farber [Steven.Farber@geog.utah.edu<mailto:Steven.Farber@geog.utah.edu>]
Sent: Thursday, January 23, 2014 5:49 PM
To: ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
Cc: SEAN CASEY REID; TYLER JOSEPH LARSON; Kevin A Henry
(medicalgeography@yahoo.com<mailto:medicalgeography@yahoo.com>)
Subject: [CTPP] female daytime population
We are trying to come up with an estimate of adult “daytime” female population for each
census tract in Salt Lake City.
Intuitively, for a census tract, A, this estimate is: (the number of women who have a
workplace in A) plus (the number of women live in A) minus (the number of working women
who live in A).
From the 5-year CTPP, we will use tables A20211,
A101203, and A11600 for the three terms in the above calculation. We will only calculate
the measure for women 16 years and older (although ideally we’d like to have a measure for
just 40 years and up).
Can anyone from this list provide me with feedback about this methodology? Are there any
big issues that I need to be aware of? Is there a better way to be doing this?
In the end, we would like a daytime measure of the female population in order to
calculate mammography accessibility metrics.
Many thanks for your comments.
Steve
Steven Farber, PhD
Assistant Professor
Department of Geography
University of Utah
http://stevenfarber.wordpress.com<http://stevenfarber.wordpress.com/>
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