Transportation Spending by Low-Income California Households ...

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Table 5.1 Mode Choice and Vehicle Access Measures for the Bay Area, by Income Group Low- Income Higher- Income Poor From PUMS Commute mode choice (%) Drove alone 51 53 70 Carpool 16 17 12 Bus or trolley bus 12 12 5 Streetcar or trolley car 0 0 0 Subway or elevated 2 2 3 Railroad 0 0 1 Ferryboat 0 0 0 Bicycle 2 2 1 Walked 8 7 3 Taxicab 0 0 0 Motorcycle 1 0 0 Other method 1 1 1 Worked at home 5 4 4 Commute mode choice for those who take public transit (%) Bus or trolley bus 78 77 52 Streetcar or trolley car 3 3 5 Subway or elevated 15 17 35 Railroad 3 3 7 Ferryboat 0 1 2 % of households with access to vehicle 70 73 94 Average number of vehicles per household 1.09 1.18 1.88 Average number of vehicles per working age adult in household (ages 18 to 64) 0.71 0.75 1.05 From BATS % of employed persons with driver’s license (a) 85 96 SOURCES: Census 2000 Public Use Microdata Sample and 2000 Bay Area Travel Survey. aNot reported because of small sample sizes. 64
We also looked at mode choice using the BATS dataset, and we arrived at qualitatively similar conclusions. 3 In addition, the BATS dataset allowed us to investigate the difference in mode choice between work-related and nonwork-related trips. The main difference that was found between work-related travel and nonwork-related travel was that for nonwork trips, both low-income and higher-income groups were less likely to use transit and more likely to walk. Closely related to findings regarding mode choice, one prominent difference across income groups in the Bay Area pertains to the share of households with access to a vehicle. Ninety-four percent of households in the higher-income group report having access to a vehicle, but only 73 percent of low-income households and 70 percent of poor households report having access (Table 5.1). The average number of vehicles in a household is 1.88 for higherincome households, 1.18 for low-income households, and 1.09 for poor households. However, the average number of vehicles per working-age adult may be a better measure of an individual’s access to a vehicle because it reflects the possibility of competition for use of vehicles within the household. The average number of vehicles per potential driver (that is, vehicles per working age adult) is 0.71 for the poor group, 0.75 for the low-income group, and 1.05 for the higher-income group. Ninetysix percent of higher-income workers have driver’s licenses, compared to 85 percent of low-income workers. For the higher-income group, the percentage of workers with driver’s licenses is roughly the same as the percentage of households with access to a vehicle. For the low-income group, however, there is a gap of 12 percentage points between the two measures: Eighty-five percent of low-income workers have driver’s licenses, but only 73 percent of low-income households report having access to a vehicle. On average, low-income workers spend about a minute less than higher-income workers on their commutes (Table 5.2). Although the difference is small, it is statistically significant. There is more of a _____________ 3 However, the differences among the income groups in terms of the percentage who walk and the percentage who use a private vehicle were less pronounced in the BATS data. 65
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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
Page 35 and 36: 3. Transportation Expenditures in M
Page 37 and 38: Table 3.2 Vehicle Use, Vehicle Owne
Page 39 and 40: Components of Vehicle-Related Expen
Page 41 and 42: inspection, and auto club membershi
Page 43 and 44: income households and the higher-in
Page 45 and 46: eport looks primarily at cost and n
Page 47 and 48: The results from Table 3.5 indicate
Page 49 and 50: variation in transportation costs w
Page 51 and 52: overall household expenditures for
Page 53 and 54: 31 Table 3.9 Transportation Expendi
Page 55 and 56: Table 3.10 Comparison of California
Page 57 and 58: Table 3.11 Comparison of the San Fr
Page 59 and 60: Table 3.10 have lower expenditure f
Page 61 and 62: 4. Costs of Illustrative Bay Area C
Page 63 and 64: 0-300 301-600 601-1100 1101-6813 Ba
Page 65 and 66: Table 4.2 Place of Work Comparison
Page 67 and 68: Concord CONTRA COSTA SAN FRANCISCO
Page 69 and 70: Administration (FHWA) mileage rate
Page 71 and 72: 49 Table 4.3 Costs of Illustrative
Page 73 and 74: participants who took transit or ca
Page 75 and 76: Table 4.4 Costs of Illustrative Wit
Page 81 and 82: commutes is $4,240, whereas the hig
Page 83 and 84: The results from this chapter seem
Page 85: 5. Commute Behavior in the Bay Area
Page 89 and 90: longer for higher-income workers if
Page 91 and 92: Table 5.3 (continued) Low- Income H
Page 93 and 94: Table 5.5 depicts the share of the
Page 95 and 96: 73 Table 5.6 Mode Choice and Vehicl
Page 97 and 98: 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
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hours for late night and graveyard
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credit ratings, assisting with insu
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would have paid with traditional au
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citizens. Rather, the question shou
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Facilitating Bicycling or Walking A
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transportation hubs may be another
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allowing flexibility at the local l
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services, health care, drug treatme
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costs. Efforts to incorporate infor
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are differences) and by looking at
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Dataset Poor Low-Income Higher-Inco
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income, problems common to most hou
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or the Bay Area specifically. We us
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Appendix B Information on Specific
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We also excluded expenditures on bi
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Atlanta: Atlanta, GA MSA Miami: Mia
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147 Table B.1 (continued) CES Metro
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Appendix C Sensitivity Analysis for
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151 Table C.1 (continued) Poor Low-
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transportation expenditures constit
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Appendix D Methods Used for the Exa
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Bibliography American Automobile As
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Implications of Welfare Reform for
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Lucas, M., and C. Nicholson, “Sub
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Progressive Casualty Insurance Comp
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About the Author LORIEN RICE Lorien
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