Traffic Analysis Zone (TAZ) Program

December 2009

December 2009

Census Transportation Planning
Products (CTPP) AASHTO Update
Penelope Weinberger, AASHTO,
[email protected]
CTPP Oversight Board Meeting
On November 12, the CTPP Oversight Board,
chaired by Mary Lynn Tischer, Virginia DOT,
met by conference call. As a result of the
meeting several new subcommittees were
formed to look at areas of interest to the CTPP
community. One group will look at data
archiving and another at research. These groups
intend to explore the hard questions of both how
and where do we keep data, and alternatives to
ACS for small area data. The meeting also
touched on future training needs, TAZ
Delineation and the upcoming data and software
for CTPP ACS three-year (2006-2008) data.
CTPP Access Software
AASHTO has contracted with Beyond 20/20
and Citygate for the development and production of the software. As the software developer
will only get empty tables shells beforehand for
software testing, the work plan includes 12
weeks for data delivery from AASHTO to the
operational web-based software. The software
will primarily be a web-based solution, with a
desktop solution using Beyond 20/20
Professional Browser.
CTPP Three-Year ACS Data Products
The Census Bureau’s ACS Office is working on
the tabulations using ACS records from 20062007-2008 and expects to deliver a file to
AASHTO and FHWA on or before June 2010.
AASHTO will then deliver the file to Beyond
20/20 to be imported into the CTPP Access
Software.

Page 1

U.S. Department of Transportation
Federal Highway Administration
Bureau of Transportation Statistics
Federal Transit Administration
AASHTO Standing Committee on Planning
In cooperation with the TRB Census Subcommittee

The Upcoming 2010 Census
Kristen Rohanna, San Diego Association Of
Governments (SANDAG), [email protected]
For more than 200 years, the Census Bureau has
conducted a census every 10 years to collect
population, housing, and socioeconomic data
from the public. While the U.S. Constitution
mandates a census be held every 10 years for the
purposes of Congressional reapportionment and
legislative redistricting, the data are used for
many other purposes. For example, Federal
funds are allocated based on the official
population counts (e.g., funds for Head Start
programs, public transportation, and road
rehabilitation and construction).
The 2010 Census is rapidly approaching. Even
though Census forms will be sent out during
March, April 1st is the official Census Day. The
Census form will ask 10 questions, including
questions about the number of people living in a
residence, tenure, and race/ethnicity. A copy of
the form can be found at:
http://2010.census.gov/2010census/how/interactiveform.php. The full implementation of the

American Community Survey (ACS) which
began in 2005 and collects more detailed person
and household characteristics, means the 2010
Census will be a short form only Census.
(continued on page 2)

CTPP Five-Year ACS Data Products
The first CTPP using ACS with small area
tabulation will use ACS records from 2006 to
2010. We expect the data will be modified in
some fashion to reduce the use of data suppression to protect individual confidentiality. We
are hopeful that the techniques developed
resulting from NCHRP 08-79 Producing
Transportation Data Products from the
American Community Survey that Comply with
Disclosure Rules will be used. The data are
expected to be released in 2012.

Page 2

December 2009

TAZ Delineation: Agency Responsibility Spreadsheet Due January 8, 2010
Liang Long, Cambridge Systematics, [email protected]
We are now working with the U.S. Census
Bureau (CB) Geography Division on TAZ
delineation for incorporation into the TIGER
file. The incorporation of TAZs into TIGER
will permit the next Census Transportation
Planning Products (CTPP) to use these TAZs for
tabulation and for mapping. The first small area
CTPP is expected to use data from the American
Community Survey for 2006 through 2010.
The Census Bureau will be working with a vendor to develop and distribute a GIS-based software for TAZ delineation. We expect the software to be distributed in spring (April-June)
2011, with four months for files to be returned to
the CB. We are planning for two levels of custom tabulation geography for CTPP: First, the
small TAZs (or base TAZ) will have a
recommended threshold of 1,200 population,
and second, Transportation Analysis Districts
(TAD) will have a recommended threshold of
20,000. The TAD will be accumulations of

TAZs or census tracts and should be designed
with three-year ACS tabulation in mind.
As a first step, I have sent a spreadsheet to each
state DOT. I have asked them to identify the
agency who will most likely define TAZs for
each county or independent city. MPOs can be
selected using a drop-down list in the spreadsheet. For some counties, there may be more
than one MPO who is interested in defining
TAZs. If there are conflicts about which agency
will be the lead agency, these conflicts need to
be resolved before we submit the list to the CB.
State DOTs have been asked to submit their list
by January 8, 2010.
I will compile a list for review in 2010 before it
is sent to the Census Bureau Geography
Division. If you have questions, please contact
me, Liang Long at [email protected],
202-366-6971.

The Upcoming 2010 Census (continued)
Over the past few years, the Census Bureau has been working with many cities, counties, and
metropolitan planning organizations (MPO) around the country to ensure that everyone is counted. 2010
Census planning activities included the Local Update to Census Addresses (LUCA) program and the
Participant Statistical Areas Program (PSAP). The LUCA program gave local jurisdictions the
opportunity to confirm all addresses in its jurisdiction and supply addresses that were missing from the
Census Bureau’s master address list. The PSAP gave local jurisdictions input into the census geography
boundaries, such as block groups, that are used to distribute the data.
Currently, the Census Bureau is conducting outreach for the 2010 Census. Local Census offices have
opened up in many cities around the country. Working with many local organizations, including
cities/counties, MPOs, and community groups, local Census Bureau staff have helped establish numerous
Complete Count Committees to get the word out. The Census Bureau is conducting a media campaign to
promote the 2010 Census as well. More information about promotional materials can be found at:
http://2010.census.gov/partners/materials/.

December 2009

Page 3

Sources of Employment Data
Ed Christopher, FHWA Resource Center Planning Team, [email protected]
A major concern in transportation planning is
the acquisition of quality employment data.
Employment data are used in transportation
planning to model the journey to work, conduct
economic assessments, carry out transit and travel demand planning, examine and plan social
service delivery and evaluate fixed physical
infrastructure investments. Rarely is it collected
solely for transportation purposes. For the
transportation community this means using
someone else’s data.

To help those interested in this topic I have tried
to assemble a list of the sources of employment
(jobs) data from both private and public sources.
This list should be considered a draft and does
not include every possible supplier of these
types of data. If anyone has a source that they
would like to add, please contact me, Ed
Christopher at [email protected],
708-283-3534.

a. PRIVATE
InfoUSA

http://www.infousa.com/

Dun & Bradstreet

http://www.dnb.com/

Experian

http://www.experian.com/products/national_business_database.html
http://www.experian.com/

Claritas

http://en-us.nielsen.com/tab/product_families/nielsen_claritas

Geo Results

http://www.georesults.com/

MapInfo Business Points

http://www.MapInfo.com/

AGS – Applied Geographic Solutions

http://www.appliedgeographic.com/

Equifax

http://www.equifax.com/

Global Insight

http://www.globalinsight.com/

0-0 DataNetwork Corporation

http://www.0-0.net/

b. FEDERAL
Quarterly Census of Employment and Wages-(ES202) Program

http://www.bls.gov/cew/

Current Employment Statistics (CES) program

http://www.bls.gov/ces/

Current Population Survey (CPS)

http://www.census.gov/cps/

Local Area Unemployment Statistics (LAUS)

http://www.bls.gov/lau

American Community Survey (ACS)

http://www.census.gov/acs/www/

Longitudinal Employer-Household Dynamics (LEHD) Program

http://lehd.did.census.gov/led/index.php

Census Transportation Planning Package 2000 (CTPP 2000)

http://www.dot.gov/ctpp/

Regional Industrial Multiplier System (RIMS)

http://www.bea.gov/regional/

Page 4

December 2009

Commute Differences by Gender
Randall Crane, University of California at Los Angles, [email protected]
Lois Takahashi, University of California at Los Angles, [email protected]
such as wages and other measures of the rewards
of one’s career.

This is an excerpt of a paper given at the TRB
international conference on Women’s Issues in
Transportation, October 2009.

This report uses 20 years (1985 to 2005) of the
American Housing Survey. Questions on the
commute trip include self-reported travel times
and distances, and demographic characteristics,
including income, education level, marital status, race/ethnicity, age, gender, and family
structure. This analysis is restricted to national
totals, with analysis using the urban sample
alone.

Historically, in the United States, men have
commuted further and longer than their female
counterparts. But, as women’s participation rate
in the labor force approaches men’s, and young
women increase their influence on household
location decisions, how gender influences
travel - especially the commute - might be
changing too.

Looking at Table 1, there is no evidence of a
closing gap in commute times in these data. The
difference in commute times by gender ranges
from 8 to 14 percent over the 20-year period,
with women’s commute time consistently
shorter than men’s. Both men and women
increased their average commute time by 11.5
percent over the same period.

Much of the literature focuses on the role of
household responsibilities in women’s travel
behavior, and another part of the literature
explores women’s changing roles in labor markets. The availability of men and women for
home-centered activities, such as child rearing or
elder care, will vary with their opportunity costs,

Table 1. Mean One-Way Commute Duration (Minutes), by Sex, Year, and Mode
By Car or Truck
Year

Women

Men

1985

18.2

20.9

1987

N/A

1989

By Bus/Transit
Men

Percent Difference

38.8

38.8

0%

N/A

N/A

N/A

N/A

N/A

N/A

N/A

1991

18.8

20.9

10.0%

35.9

38.8

7.5%

1993

18.8

21.1

10.9%

36.6

37.0

1.1%

1995

19.4

21.1

8.1%

34.3

35.6

3.7%

1997

19.2

22.3

13.9%

35.8

38.4

6.8%

1999

19.6

22.9

14.4%

36.9

36.7

-0.5%

2001

19.7

22.8

13.6%

35.1

34.4

-2.0%

2003

20.1

23.2

13.4%

35.1

36.8

4.6%

2005

20.3

23.3

12.9%

36.6

37.9

3.4%

11.5%

11.5%

-5.7%

-2.3%

Percent Change
1985-2005

Percent Difference Women
12.9%

Source: American Housing Survey, excluding non-urban, group and institutional quarters, and trips of 0 duration.

December 2009

Page 5

Figure 1. Gap by Mode, 1985-2005, as of % Difference in Mean One-Way Commute Time (Clockwise from
upper left)

Figure a. Gender Gap by Mode

Figure b. White Gender Gap by Mode

Figure c. Black Gender Gap by Mode

When race/ethnicity are accounted for, different
patterns start to emerge. Hispanic women’s
commute time by car shows greater convergence
with Hispanic men from 1991 to 1995, but
shorter commute times by car in other periods.
Hispanic women’s commute time by bus, however, showed relative convergence with Hispanic
men. For Black/African American women and
men, women’s commute time by car was shorter
than men’s, but less so than with white or
Hispanic women and men. For Black women’s
commute time by bus, there is much more
variability, and during many of the years, Black
women had longer commute times by bus than
Black men.
The gender gap in commute length of older
workers is growing, even while that of younger
workers steadily closes. At the same time, racial
differences in mode choice and commute times
are becoming less pronounced, both by race and
by gender, thus, gendered elements of travel

Figure d. Hispanic Gender Gap by Mode

demand are evolving, if not in predictable
directions.
•

The gender gap in commuting times
widened slightly. While women’s commutes are lengthening in duration, they are
not quite matching the growth in the average
male commute time.

•

The gender gap in transit use is shrinking
by race, largely because Hispanic and Black
commuting by transit dropped dramatically.

•

The gender gap is growing for older workers, while narrowing for younger workers.

Due to space constraints, the tables and figures for
the results by age are not included in this excerpt.
The report concludes that while gender matters as
much as ever for commuting patterns, it also
appears to be greatly influenced by race and age.
The gender gap remains, but changes across
groups and life course stage.

Page 6

December 2009

Model-Based Synthesis of Household Travel Survey Data
Liang Long, Cambridge Systematics Inc., [email protected]
Jane Lin, University of Illinois at Chicago, [email protected]
Introduction
Household travel data synthesis/simulation has
become a very promising alternative or supplement of survey data to both small urban areas
and large metropolitan regions in which data are
expensive to collect or the data required to support the planning process become outdated.
This study proposes and applies model-based
approaches (i.e., Small Area Estimation (SAE)
methods) to synthesize household travel characteristics. The proposed methods address the
sampling- biases concerns in the existing
methods. Specifically, three SAE methods – the
Generalized Regression Estimators (GREG)
method, the Empirical Best Linear Unbiased
Predictor (EBLUP) method, and the Synthetic
method – an EBLUP without random area
effects, are applied to synthesize household travel characteristics at census tract level. The
SAE framework of synthesizing household travel characteristics is demonstrated with the 2001
National Household Travel Survey data (NHTS)
and Census Transportation Planning Package
(CTPP) 2000 data in the Des Moines metropolitan area in central Iowa.
Tract Level Estimation and Validation
Figure 1 plots the SAE estimates with the CTPP
values across 107 census tracts in Des Moines,

Iowa. The NHTS sample averages also are
included in the plot. It is apparent that the SAE
estimates, especially the EBLUP and Synthetic
ones, are much closer to the validation values
(CTPP values) than the NHTS sample averages.
Using NHTS sample averages produces large
biases. The fact that the EBLUP and Synthetic
estimations are better than the GREG’s indicates
significant area heterogeneity across the census
tracts and thus mixed effect models are better.
Table 1 compares the mean values and standard
deviations among the SAE estimates, sample
averages from NHTS and the CTPP values. The
t-test is used to compare the mean values and the
non-parametric Kolmogorov-Smirnov twosample test is used to compare the distribution
between each data pair. By either measure, the
Synthetic estimates are statistically identical to
the CTPP values (at the 0.05 significant level).
This result is consistent with the visual inspection in Figure 2. Mean Absolute Relative Error
(MARE) measures the average absolute deviation of the estimated values from the true values.
It is another way to tell how closes the estimated
values to the true values. Not surprisingly, the
Synthetic estimates give the least MARE. This
is consistent with the previous findings.

Census tract level SAE

GREG
EBLUP

9

Synthetic
Sample average

CTPP value

40

70

# work trips/household

8
7
6
5
4
3
2
1
0
0

10

20

30

50
60
Census tract

80

90

100

110

Figure1. Estimated and observed number of work trips at census tract level.

December 2009

Page 7

Table 1. Comparison of SAE Estimates to CTPP Values for Number of Work Trips
Means

Standard
Deviation

T Value
(Pr > T)

Per Household Trip
Rate (Pr > Ksa)

CTPP Value
Sample Average

2.648

-

-

-

3.61

0.7200

<0.0001

<0.0001

EBLUP

2.981

0.4169

<0.0001

<0.0001

0.1508

Synthetic

2.65

0.1807

0.8251

0.0968

0.0517

GREG

2.84

0.5586

<0.0001

<0.0001

0.2571

Conclusion
This paper has proposed and evaluated modelbased small area estimation methods to synthesize household travel survey data in smalland mid-size metropolitan areas. The SAE
approach addresses the sampling biases concerns
in the existing methods. The paper has verified
that SAE is a plausible statistical approach to
providing reliable and unbiased travel information for local areas. The proposed methods of
dealing with household travel survey data in this
research and the analysis findings will provide a
useful and economical tool for practitioners,
planners and policy-makers in transportation
analyses.

MARE

This study is part of the transferability study of
household travel survey data funded by the
Federal Highway Administration (FHWA).
For detailed information of this study, please
refer to the following paper:
Long, L., J. Lin, W. Pu. Model-Based Synthesis
of Household Travel Survey Data in Small- and
Mid-Size Metropolitan Areas. Transportation
Research Record, Journal of Transportation
Research Board 2105: 64-70, 2009.

Page 8

December 2009

CTPP Hotline – 202/366-5000

E-mail: [email protected]
CTPP Listserv: http://www.chrispy.net/mailman/listinfo/ctpp-news
CTPP Web Site: http://www.dot.gov/ctpp
FHWA Web Site for Census issues: http://www.fhwa.dot.gov/planning/census
2005-2007 ACS Profiles: http://ctpp.transportation.org/profiles_2005-2007/ctpp_profiles.html
AASHTO Web Site for CTPP: http://ctpp.transportation.org
1990 and 2000 CTPP downloadable via Transtats: http://transtats.bts.gov/
TRB Subcommittee on census data: http://www.trbcensus.com
AASHTO
Penelope Weinberger
PH: 202/624-3556
E-mail: [email protected]

FHWA
Elaine Murakami
PH: 206/220-4460
E-mail: [email protected]

Michelle Maggiore
PH: 202/624-3625
E-mail: [email protected]

Ed Christopher
PH: 708/283-3534
E-mail: [email protected]

Jonette Kreideweis, MN DOT
Vice Chair, SCOP CTPP Oversight Board
PH: 651/366-3854
E-mail: [email protected]

Liang Long
PH: 202/366-6971
E-mail: [email protected]

Census Bureau: Housing and Household
Economic Statistics Division
Melissa Chiu
PH: 301/763-2421
E-mail: [email protected]
FTA
John Sprowls
PH: 202/366-5362
E-mail: [email protected]
John Giorgis
PH: 202/366-5430
E-mail: [email protected]

TRB Committees
Catherine Lawson
Urban Data Committee Chair
PH: 518/442-4773
E-mail: [email protected]
Clara Reschovsky
Census Subcommittee Co-Chair
PH: 202/962-3332
E-mail: [email protected]
Kristen Rohanna
Census Subcommittee Co-Chair
PH: 619/699-6918
E-mail: [email protected]

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