23 Jan
2014
23 Jan
'14
4:49 p.m.
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/>
23 Jan
23 Jan
5:10 p.m.
I hope you're going to aggregate those tracts into some larger areas,
because the margins of error on these estimates are going to be
astronomical. Most tracts have fairly low workplace numbers because they
are essentially residential and only have local businesses/schools/churches
providing employment. Tracts with really large employment counts often have
few residents, e.g. airports. Some tracts are low on both, e.g. large
parks. It also depends on how good a job the local area has done at
tracting and retracting every ten years.
Good luck.
Patty Becker
On Thu, Jan 23, 2014 at 5:49 PM, Steven Farber
<Steven.Farber(a)geog.utah.edu>wrote;wrote:
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
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net
https://www.chrispy.net/mailman/listinfo/ctpp-news
--
Patricia C. (Patty) Becker
APB Associates/Southeast Michigan Census Council (SEMCC)
28300 Franklin Rd, Southfield, MI 48034
office: 248-354-6520
home:248-355-2428
pbecker(a)umich.edu
24 Jan
24 Jan
10:16 a.m.
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(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on behalf of Steven
Farber [Steven.Farber(a)geog.utah.edu]
Sent: Thursday, January 23, 2014 5:49 PM
To: ctpp-news(a)chrispy.net
Cc: SEAN CASEY REID; TYLER JOSEPH LARSON; Kevin A Henry (medicalgeography(a)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/>
10:37 a.m.
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(a)chrispy.net
Cc: u0719944(a)utah.edu; medicalgeography(a)yahoo.com; tyler.larson(a)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(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on behalf of Steven
Farber [Steven.Farber(a)geog.utah.edu]
Sent: Thursday, January 23, 2014 5:49 PM
To: ctpp-news(a)chrispy.net
Cc: SEAN CASEY REID; TYLER JOSEPH LARSON; Kevin A Henry (medicalgeography(a)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/>
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net
https://www.chrispy.net/mailman/listinfo/ctpp-news
10:42 a.m.
How would this compare with using LEHD?
Thanks,
Bob
*Robert Shull, PE PresidentEco Resource Management Systems Inc.PO Box
1850Vashon, WA 98070206.414.8751 rshull(a)transportmodeler.com
<rshull(a)transportmodeler.com>*
On Fri, Jan 24, 2014 at 8:37 AM, <Elaine.Murakami(a)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(a)chrispy.net
*Cc: *u0719944(a)utah.edu; medicalgeography(a)yahoo.com; tyler.larson(a)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(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on
behalf of Steven Farber [Steven.Farber(a)geog.utah.edu]
Sent: Thursday, January 23, 2014 5:49 PM
To: ctpp-news(a)chrispy.net
Cc: SEAN CASEY REID; TYLER JOSEPH LARSON; Kevin A Henry (
medicalgeography(a)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/>
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net
https://www.chrispy.net/mailman/listinfo/ctpp-news
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net
https://www.chrispy.net/mailman/listinfo/ctpp-news
27 Jan
27 Jan
10:22 a.m.
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/>
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
10:49 a.m.
Lehd now has age and sex for data in the 2009 to 2001 series.
http://lehd.ces.census.gov/data/lodes/LODES7/LODESTechDoc7.0.pdf
"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).
--
Ed Christopher
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/>
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
_______________________________________________
ctpp-news mailing list
ctpp-news(a)chrispy.net
https://www.chrispy.net/mailman/listinfo/ctpp-news
11:29 a.m.
Hi, Bob
Sorry that I didn’t make my explanation clear in the first email.
LODES does have flows and they have flows by age and flows by gender. But similar to
CTPP, they don’t have two way tabulations, flows by age and gender.
I was hitting “send” button too quickly for the first email. Actually, as part of LODES,
residence information is provided.
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/>
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
_______________________________________________
ctpp-news mailing list
ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>
https://www.chrispy.net/mailman/listinfo/ctpp-news
11:54 a.m.
Thanks Ed and Liang,
I had understood that Steve was trying to get adult "daytime" female
population by census tract. The WAC data appears to have both some age
group stratifications and gender. I meant to ask about the use of the LEHD
data as a question to see how it compares with the CTPP/ACS approach. With
previous experience we have found that the gender fields do not sum to the
total employment values, so there is missing data in the LEHD also. But,
could it be a more complete dataset and could it give a better estimate?
Has anyone else checked this for other areas?
Also, although the age groups are 29 and younger, 30 to 54, and 54 and
older, could it be assumed that most of the employees, even in the 29 and
younger age group could be classified as "adult" ?
Thanks!
Bob
*Robert Shull, PE PresidentEco Resource Management Systems Inc.PO Box
1850Vashon, WA 98070206.414.8751 rshull(a)transportmodeler.com
<rshull(a)transportmodeler.com>*
On Mon, Jan 27, 2014 at 9:29 AM, <Liang.Long.CTR(a)dot.gov> wrote:
Hi, Bob
Sorry that I didn’t make my explanation clear in the first email.
LODES does have flows and they have flows by age and flows by gender. But
similar to CTPP, they don’t have two way tabulations, flows by age and
gender.
I was hitting “send” button too quickly for the first email. Actually, as
part of LODES, residence information is provided.
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(a)dot.gov<mailtomailto:
Elaine.Murakami(a)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(a)geog.utah.edu<mailtolto:
Steven.Farber(a)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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12:46 p.m.
Hi, Bob
LODES Does not include self-employed (approx. 10% of workers).
We have done some comparisons among LEHD, ACS and CPS in terms of employment data. Here
is the link: Please go to the third article: Counting Workers: Comparison of Employment
Data for CPS, ACS and LODES
http://www.fhwa.dot.gov/planning/census_issues/ctpp/status_report/sr100113.…
There is also another article of “Comparing Commuting Flows between CTPP and LODES”
http://www.fhwa.dot.gov/planning/census_issues/ctpp/status_report/sr1213.pdf
But I never got a chance to investigate employment by age and gender using LODES. ACS
PUMS data are good source if you are looking for employment information by age and gender
as they provide ages in one year increment. Also, some of the employment status
questions were modified in 2008, resulting in ACS employment estimates which are better
matched with the CPS labor force estimates. But of course, you can only get this
information down to PUMA level (100,000 population thresholds).
Hope this helps.
Liang
________________________________________
From: ctpp-news-bounces(a)chrispy.net [ctpp-news-bounces(a)chrispy.net] on behalf of Robert
Shull [rshull(a)transportmodeler.com]
Sent: Monday, January 27, 2014 12:54 PM
To: ctpp-news(a)chrispy.net
Subject: Re: [CTPP] female daytime population
Thanks Ed and Liang,
I had understood that Steve was trying to get adult "daytime" female population
by census tract. The WAC data appears to have both some age group stratifications and
gender. I meant to ask about the use of the LEHD data as a question to see how it compares
with the CTPP/ACS approach. With previous experience we have found that the gender fields
do not sum to the total employment values, so there is missing data in the LEHD also. But,
could it be a more complete dataset and could it give a better estimate? Has anyone else
checked this for other areas?
Also, although the age groups are 29 and younger, 30 to 54, and 54 and older, could it be
assumed that most of the employees, even in the 29 and younger age group could be
classified as "adult" ?
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 Mon, Jan 27, 2014 at 9:29 AM,
<Liang.Long.CTR@dot.gov<mailto:Liang.Long.CTR@dot.gov>> wrote:
Hi, Bob
Sorry that I didn’t make my explanation clear in the first email.
LODES does have flows and they have flows by age and flows by gender. But similar to
CTPP, they don’t have two way tabulations, flows by age and gender.
I was hitting “send” button too quickly for the first email. Actually, as part of LODES,
residence information is provided.
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
Robert Shull [rshull@transportmodeler.com<mailto:rshull@transportmodeler.com>]
Sent: Friday, January 24, 2014 11:42 AM
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
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<tel:206.414.8751>
rshull@transportmodeler.com<mailto:rshull@transportmodeler.com><mailto: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><mailto: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><mailto:ctpp-news@chrispy.net<mailto:ctpp-news@chrispy.net>>
Cc:
u0719944@utah.edu<mailto:u0719944@utah.edu><mailto:u0719944@utah.edu<mailto:u0719944@utah.edu>>;
medicalgeography@yahoo.com<mailto:medicalgeography@yahoo.com><mailto:medicalgeography@yahoo.com<mailto:medicalgeography@yahoo.com>>;
tyler.larson@utah.edu<mailto:tyler.larson@utah.edu><mailto: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><mailto:ctpp-news-bounces@chrispy.net<mailto:ctpp-news-bounces@chrispy.net>>
[ctpp-news-bounces@chrispy.net<mailto:ctpp-news-bounces@chrispy.net><mailto: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><mailto: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><mailto: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><mailto: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/>
_______________________________________________
ctpp-news mailing list
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9 comments
6 participants
participants (6)
-
Ed Christopher -
Elaine.Murakami＠dot.gov -
Liang.Long.CTR＠dot.gov -
Patricia Becker -
Robert Shull -
Steven Farber