Transportation Spending by Low-Income California Households ...

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• Solano to Contra Costa: Although car use rates are over 95 percent for both groups, low-income workers are still more likely to take the bus, and they also use the railroad more often than the higher-income group. • Sonoma to Marin: This commute has results similar to the commute between Napa and Contra Costa in that virtually everyone takes a car for this commute, although here there is less difference in the distribution between driving alone and carpooling. There are no statistically significant differences for transit usage between the income groups. In sum, we cannot conclude either that the different income groups always make the same mode choices when faced with the same commute or that mode choices will always be quite different. Some counties had very similar mode choice distributions across income levels, whereas other counties showed very disparate mode choice distributions. In general, the least densely populated counties had very similar distributions for lowand higher-income commuters because virtually everyone drives. However, it should be noted that Alameda and Contra Costa have fairly similar mode choice distributions across income levels as well. Interactions Between Mode Choice and Commute Duration The relatively long commute times in Alameda, Marin, and San Francisco Counties (25 minutes, 30 minutes, and 30 minutes, respectively) might be attributable to higher rates of public transit use and lower rates of private vehicle use than in other counties (Table 5.3). However, Contra Costa also has a 30 minute median commute time, but has a car commute rate and public transit commute rate that are closer to that in San Mateo than to Alameda, Marin, and San Francisco. Table 5.10 illustrates some of the counterbalancing forces that affect the relative commute times between low-income and higher-income workers. Among public transit takers, higher-income workers often have ______________________________________________________________ reflects the respondent’s understanding of which of the listed modes best matches the transit provider that he or she uses. 82
Table 5.10 Median Commute Durations by County and Income Group, Controlling for Mode and Time of Day (in minutes) Low- Income Higher- Income Commuters using car, truck, or van between 7 a.m. and 9 a.m. Alameda 20 20 Contra Costa 20 20 Marin 25 25 Napa 15 15 San Francisco 25 25 San Mateo 20 20 Santa Clara 20 20 Solano 20 20 Sonoma 18 20 Commuters using public transit between 7 a.m. and 9 a.m. Alameda 40 45 Contra Costa 45 50 Marin 60 60 Napa 40 35 San Francisco 30 30 San Mateo 30 45 Santa Clara 40 45 Solano 45 60 Sonoma 45 45 SOURCE: Census 2000 Public Use Microdata Sample (Bay Area subsample). longer commute times. But those who commute by private vehicle have much shorter commute times than public transit takers, and higherincome workers are more likely to commute by private vehicle. Table 5.10 limits the analysis just to those who commute during peak commute times, to control for differences in commute duration stemming from differing traffic levels at different times of the day. The results in the top panel show that, for each county, low-income drivers and higher-income drivers have the same commute times. However, the bottom panel illustrates that low-income public transit takers have commute durations that are on average about five minutes shorter than commute times for higher-income transit takers. 83
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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
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 and 86: 5. Commute Behavior in the Bay Area
Page 87 and 88: We also looked at mode choice using
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: • Marin to San Francisco: As with
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 150 and 151: services, health care, drug treatme
Page 152 and 153: 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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