Transportation Spending by Low-Income California Households ...

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services, health care, drug treatment facilities, and shopping areas). Lowincome individuals will find it difficult to have successful work lives if their child care, health care, and other needs are not met because of lack of transportation. Information on personal characteristics (for example, geographic location, employment status, income, household composition, race and ethnicity, language fluency, and participation in such means-tested programs as Food Stamps and CalWORKs) would be useful for tailoring programs to the specific needs of different groups. In particular, the data could identify populations for whom the cost of transit presents a barrier to transit use or a financial hardship. Households could report on whether they have trouble paying for multi-ride discount passes and whether spreading the payments out over the course of the month would make a significant difference for them. Surveys could also be used to assess how well information about transportation affordability programs is being distributed and absorbed. Because data collection is expensive and time-consuming, one costefficient way to gain more information about transportation affordability issues would be to piggy-back on data collection efforts already in place. Several relevant surveys and questionnaires have already been fielded in the Bay Area—for example, the needs assessment for Alameda County welfare recipients done by the Public Health Institute, the transportation survey fielded by the LIFETIME grassroots organization, and various transit ridership surveys. Although these studies have provided many useful insights into transportation behaviors and needs, future research could address the monetary costs of transportation more thoroughly. Health and human services agencies frequently survey program participants, and transportation planning agencies could collaborate with HHS agencies to ask useful questions about transportation on welfare-towork surveys. Some past surveys of TANF recipients have asked such questions as “Is transportation ever a barrier to getting to work?” The answers are informative, but it would be even more helpful to identify which specific aspects of transportation are serving as barriers to employment (for example, monetary costs, time costs, or lack of mobility). The questions posed in the Green et al. (2000) study of Alameda County, the Moreno et al. (2000) study in Los Angeles 128
County, and the Blumenberg and Haas (2001) study of Fresno County provide good examples of transportation questions that could serve as a starting point for designing future surveys of welfare recipients. 1 Another possibility for collaboration with social services agencies would be to add transportation information to their administrative databases. One advantage of administrative program data is that such data allow researchers to link information on residential location and workplace location. Adding information about such items as monetary costs, mode choice, travel time, and transportation assistance would expand research options even further. Another way to extend current research would be to bring greater emphasis on low-income populations to transportation planning data collection efforts. MTC and individual transit agencies within the Bay Area periodically conduct ridership surveys. Efforts could be made to oversample low-income and nonwhite populations to ensure that sample sizes are large enough to do statistically valid analyses on specific subgroups (for example, low-income Hispanic married households with children). In addition, ridership surveys could ask respondents to rank their concerns regarding transit service, including monetary costs. Adding affordability questions to the ridership surveys could help identify those groups for whom the cost of transit is problematic, by looking at differences with respect to demographic characteristics, transfer behavior, transit providers and routes. 2 Another avenue for possible extensions to ongoing research is to add more information on monetary costs to national transportation surveys. The National Household Travel Survey, the Census long form, the American Community Survey, and the American Housing Survey all contain helpful data on transportation but do not address monetary _____________ 1 Further information is also available in Blumenberg et al. (2003). 2 In the future, the TransLink® card will become a useful mechanism for collecting data and will be able to link information on travel behavior to information about the cost of the trip. However, as the TransLink® system is currently set up, its relevance for analyzing the low-income population is somewhat limited because it does not link the travel information to any passenger characteristics (such as income level). One could instead do analyses at the neighborhood level—however, it will not be possible to identify where bus trips originate or end unless GPS is installed on the buses. 129
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Transportation Spending by Low-Inco
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Foreword Mismatches between jobs an
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Summary Transportation is an import
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Table S.1 Median Annual Transportat
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about 5 to 10 percent of the median
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providing discounted transit fares
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5. COMMUTE BEHAVIOR IN THE BAY AREA
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Figures S.1. Vehicle Ownership and
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4.3. Costs of Illustrative Within-C
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1. Introduction Costs associated wi
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of “welfare-to-work” transporta
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lays out policy options for address
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2. Data and Methods In this report,
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advantage to this approach is that
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3. Transportation Expenditures in M
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Table 3.2 Vehicle Use, Vehicle Owne
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Components of Vehicle-Related Expen
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inspection, and auto club membershi
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income households and the higher-in
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eport looks primarily at cost and n
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The results from Table 3.5 indicate
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variation in transportation costs w
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overall household expenditures for
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31 Table 3.9 Transportation Expendi
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Table 3.10 Comparison of California
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Table 3.11 Comparison of the San Fr
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Table 3.10 have lower expenditure f
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4. Costs of Illustrative Bay Area C
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0-300 301-600 601-1100 1101-6813 Ba
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Table 4.2 Place of Work Comparison
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Concord CONTRA COSTA SAN FRANCISCO
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Administration (FHWA) mileage rate
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49 Table 4.3 Costs of Illustrative
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participants who took transit or ca
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Table 4.4 Costs of Illustrative Wit
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commutes is $4,240, whereas the hig
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The results from this chapter seem
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5. Commute Behavior in the Bay Area
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We also looked at mode choice using
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longer for higher-income workers if
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Table 5.3 (continued) Low- Income H
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Table 5.5 depicts the share of the
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73 Table 5.6 Mode Choice and Vehicl
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75 Table 5.8 Mode Choice and Vehicl
Page 99 and 100: households report having access to
Page 101 and 102: Table 5.9 (continued) % Using Each
Page 103 and 104: • Marin to San Francisco: As with
Page 105 and 106: Table 5.10 Median Commute Durations
Page 107 and 108: 85 Table 5.11 Differences in Mode C
Page 109 and 110: Table 5.13 Mode Choice, Work Schedu
Page 111: trips, make more household-supporti
Page 114 and 115: only expenditures. Paying a given n
Page 116 and 117: improving service quality rather th
Page 119: Part II Policy Strategies and Areas
Page 122 and 123: potential social costs such as poll
Page 124 and 125: • Increasing income directly, to
Page 126 and 127: grants for developments that meet c
Page 128 and 129: make it easier for various entities
Page 130 and 131: pass.” 10 Perhaps discounts could
Page 132 and 133: free transit is most likely not app
Page 134 and 135: have fares based on the time of day
Page 136 and 137: hours for late night and graveyard
Page 138 and 139: credit ratings, assisting with insu
Page 140 and 141: would have paid with traditional au
Page 142 and 143: citizens. Rather, the question shou
Page 144 and 145: Facilitating Bicycling or Walking A
Page 146 and 147: transportation hubs may be another
Page 148 and 149: allowing flexibility at the local l
Page 152 and 153: costs. Efforts to incorporate infor
Page 154 and 155: are differences) and by looking at
Page 156 and 157: Dataset Poor Low-Income Higher-Inco
Page 158 and 159: income, problems common to most hou
Page 160 and 161: or the Bay Area specifically. We us
Page 163 and 164: Appendix B Information on Specific
Page 165 and 166: We also excluded expenditures on bi
Page 167 and 168: Atlanta: Atlanta, GA MSA Miami: Mia
Page 169 and 170: 147 Table B.1 (continued) CES Metro
Page 171 and 172: Appendix C Sensitivity Analysis for
Page 173 and 174: 151 Table C.1 (continued) Poor Low-
Page 175 and 176: transportation expenditures constit
Page 177 and 178: Appendix D Methods Used for the Exa
Page 179 and 180: Bibliography American Automobile As
Page 181 and 182: Implications of Welfare Reform for
Page 183 and 184: Lucas, M., and C. Nicholson, “Sub
Page 185 and 186: Progressive Casualty Insurance Comp
Page 187: About the Author LORIEN RICE Lorien
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