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48 I N N O VAT I O N S I N T R AV E L D E M A N D M O D E L I N G , V O L U M E 1 sures may be closer to the true causal effect. A tion in sensitivity to build environment attributes due to problem with this approach is that most travel sur- both demographic and unobserved factors in both resi- vey data sets do not collect attitudinal data. dential choice and automobile ownership decisions. A second method is to use a two-stage instru- mental variable approach in which the endogenous explanatory built environment attributes are first INNOVATIVE METHODS FOR PRICING STUDIES regressed on instruments that are related to built environment attributes but have little correlation Arun Kuppam, Maren Outwater, and Rob Hranac with the randomness of the primary travel behav- ior of interest. The instrumental variable method is Arun Kuppam discussed the innovative methods for not applicable to a nonlinear structure, however. examining pricing strategies used in the Washington Also, ignoring the sampling variance in the pre- State Comprehensive Toll Study. He provided an dicted values of built environment attributes can overview of the limitations of using traditional modeling lead to incorrect conclusions. techniques in pricing studies, the approach used in the A third approach is to examine travel patterns study, and preliminary results. Volume 2 contains a of households immediately before and after a paper on the topic.3 The following points were covered household relocation. This approach assumes that in his presentation. households move because of factors unrelated to their built environment attribute preferences. One Current forecasting models have limitations for use potential problem with this approach is that relo- with pricing studies. One concern relates to possible cating households are themselves a self-selected inaccurate traveler values of time by trip purpose, mode, group. and time period. The lack of temporal detail in time-of- A proposed modeling framework was developed to day choice models is also a problem. There is also a need address these concerns. The general methodology con- to model strategies to optimize tolls for pricing studies. trols for residential sorting due to observed and unob- This element of the Washington State Comprehen- served attributes. It considers the direct and indirect sive Toll Study had five objectives. The first objective effects of individual and household attributes on travel was to apply values of time for different market segments decisions as well as recognizes unobserved taste varia- in a trip-based model. The second objective was to cap- tion. It focuses on automobile ownership as a travel deci- ture variations in time of day by 30-minute time periods. sion because automobile ownership impacts almost all The third objective was to develop an approach that is aspects of daily activity-travel patterns. The framework sensitive to pricing scenarios. The fourth objective was does not consider attitudinal variables and it uses traffic to capture travel behavior that reflects the tendency to analysis zones as surrogates for neighborhoods. shift to nearby time periods. The fifth objective was to There are a number of reasons for studying auto- develop a tool to optimize tolls by time periods. mobile ownership related to the built environment. Market segmentation was used in the model. The Automobile ownership is an intervening variable in the four general categories were work trips by income group, effect of the built environment on travel decisions. There nonwork trips by purpose, truck trips by class, and auto- is less research on the effect of built environment charac- mobile trips by mode. Four income groups were used: teristics on automobile ownership. Automobile owner- income less than $25,000, $25,000 to $45,000, $45,000 ship impacts almost all aspects of daily activity-travel to $75,000, and more than $75,000. The nonwork trip patterns. purposes were home-based college, home-based school, The joint residential choice and automobile owner- home-based shop, home-based other, non-home-based ship model was developed and tested on an empirical work, and non-home-based other. The truck trips by class analysis of residential choice and automobile ownership were light duty, medium duty, and heavy duty. The auto- decisions in the San Francisco Bay area. The analysis mobile trips by mode were single-occupant vehicles, high- indicates that the built environment attributes affect res- occupancy vehicles (HOV-2 and HOV-3+), and vanpool. idential location decisions, as well as automobile owner- The value of time by market segment was calculated ship decisions. There are random variations in sensitivity for peak and off-peak periods. The equivalent minutes for to built environment attributes, however. Household a $3.00 toll were also estimated. For example, the value of demographics appear to have a more dominant effect on time for drive-alone work trips by individuals in the over automobile ownership than built environment factors, $75,000 income group was $37.04 and the equivalent although both are important. Use of the population or minutes for a $3.00 toll were 4.9. For individuals in the density measures or both as proxy variables for built environment measures, such as street block density and 3 See Kuppam, A. R., M. L. Outwater, and R. C. Hranac. Innovative transit accessibility, appears appropriate. There is varia- Methods for Pricing Studies. Volume 2, pp. 142149.