ulation model, ACS variables such as automobile ownership, family structure (presence or absence of children, which would affect the odds of one or more trips to school in a day), work status (and number of workers in the household), and income (as a correlate of the mode of transportation a person/household might select) can play important roles. The synthetic population model typically draws from analysis of ACS PUMS data, while the activity based transportation model draws from special tabulations of data that the Census Bureau distributes as part of the Census Transportation Planning Package (CTPP).13 CTPP tabulations are coded to the special level of geography typically used by transportation planners: Traffic Analysis Zones (TAZs), collections of census blocks that are defined by the Census Bureau in partnership with local transportation officials and that may be finer grained than census tracts or block groups.
Completing the explanation of the basic outline shown in Figure 2-2, the activity-based model and population synthesizer are part of a feedback loop to the subregional, “neighborhood” forecast. This is because transportation activities can affect the geographic distribution of the future population: Increased traffic congestion in one place might make a certain neighborhood less attractive for future development or, conversely, it might flag an area where the transportation infrastructure must be built up (making the neighborhood more attractive in the long term).
Jarosz stressed that the ACS is essential to transportation planning for the simple reason that it is the only source of small-area trip data, through the detailed CTPP custom tabulation. Through the CTPP, the ACS is the only systematic source of data on flows—giving an indication of where commutes begin and where they end, so that planners can predict how commuters travel between the two. The question of when respondents leave their homes in the morning is sometimes challenged by critics as invasive; Jarosz observed that collection of this information raises privacy concerns, but that both the Census Bureau and the downstream data users are deeply cognizant of those concerns. Like other ACS products, the custom CTPP tabulation is subject to review by the Bureau’s Disclosure Review Board and complies with the privacy protection requirements in Title 13 of the U.S. Code; it is also subject to statistical techniques to curb the disclosure of personally identifiable information.
ulation model and activity-based model used by the Atlanta Regional Commission in more detail, speaking particularly about the challenges of converting their existing models from census long-form sample inputs to ACS inputs.
13As Jarosz noted in her talk, the CTPP data tabulation is funded by pooled funds provided by state transportation departments and metropolitan planning organizations around the country; it was originally compiled from the long-form sample, and is now being converted to the ACS. Though CTPP is often used as shorthand specifically for the data product, the program itself includes training, technical assistance, and research for the transportation community. At the time of the workshop, CTPP tabulations based on 3-year ACS data were available, with 5-year data scheduled for release later in summer 2012.