In the first decade and a half of the twenty-first century, the San Francisco Bay Area experienced rapid job growth (17% from 2002 to 2015). Employment growth greatly exceeded housing production, resulting in rising housing prices. The mismatch between jobs and housing potentially contributed to an increase in commute distance, as workers relocated to outlying neighborhoods in search of affordable housing. In this paper, the authors analyze changes in commute distance over time, with a focus on the spatial location of employment and, in particular, downtown job growth. They find that commute distance increased slightly between 2002 and 2015 throughout the Bay Area (from 17.2 to 17.8 mi.), with the greatest increase among workers in job centers located in outlying parts of the region (from 19.1 to 20.8 mi.). Increases in census tract jobs was by far the strongest predictor of commute distance increase, though this overall relationship in the region was likely moderated by the increase in employment in downtown San Francisco (44%) where, all else being equal, workers travel shorter distances (14.4 mi. in 2002 and 15.4 mi. in 2015) relative to other workers. This relationship may be due to the demographic composition of San Francisco residents: high-wage, young, single workers who are able to afford high-priced housing close to downtown. A better balance between jobs and housing would allow workers the option of self-selecting into neighborhoods closer to their jobs, underscoring the importance of policies to spur housing production in high-cost metropolitan areas.

Most U.S. metropolitan areas developed alongside the automobile, producing neighborhoods of relatively low density. Consequently, access to opportunities in these neighborhoods is predicated on having an automobile, yet many households do not have the resources to purchase one outright, relying on automobile loans to spread out the purchase price. While automobile loans can enable automobile ownership, they also significantly increase the vehicle purchase price, particularly for non-white consumers subject to discriminatory lending practices.In this study, we rely on data from the University of California Consumer Credit Panel from Experian to examine the determinants and geography of automobile debt and its consequences in California, testing whether various automobile debt measures disproportionately affect non-white neighborhoods.We find that, controlling for other factors associated with automobile lending including income, Black and Latino/a neighborhoods have higher total automobile debt, debt burdens (debt relative to income), and automobile loan delinquency rates. In particular, Latino/a neighborhoods shoulder significant automobile debt, while borrowers in Black neighborhoods have the highest delinquency rates. Factors associated with lower total automobile debt and automobile debt burden include better credit ratings, higher residential densities, urban locations, and proximity to rail stations.The findings underscore the importance of policies to offset the costs of automobile ownership and access. As part of this, policymakers should adopt and enforce fair lending rules to combat discriminatory and predatory practices and facilitate access to high-quality financial institutions and products in communities of color.

Problem, research strategy, and findingsCovid-19 significantly altered work, out-of-home activity participation, and travel, with much activity time being moved into the home. If these patterns hold, they could imply significant long-term changes for homes, businesses, cities, and transportation. We examined data for 34,000 respondents to the American Time Use Survey from 2019 (the pre-pandemic period), 2021 (the pandemic period), and 2022 and 2023 (the post-pandemic period). We used ordinary least squares (OLS) regressions to study participation in 12 out-of-home activities, travel (by auto, transit, and walking), and 16 in-home activities. We observed sharp declines in overall out-of-home activity, travel by all modes, and 10 of the 12 specific out-of-home activities in 2021 compared with 2019, whereas time spent on 13 of the 16 in-home activities rose during that period. By 2023, most of these changes persisted: Time spent out-of-home, traveling by all modes, and on six out-of-home activities remained notably lower in 2023 than in 2019, whereas time spent on nine in-home activities remained higher. The trend away from out-of-home activities and travel appears to be persisting.Takeaways for practiceFirst, given elevated remote work and shopping, planners should consider repurposing some office and retail land uses. Second, with fewer office workers, center cities may have to capitalize on other strengths such as recreational and residential desirability for some market segments, such as young people or others who prefer urban living. Third, more time at home may increase demand for more spacious and affordable housing, perhaps in lower-cost outlying suburbs of large metros and in smaller metropolitan areas. Finally, an end to ever-rising personal travel may lessen the need for costly interventions to increase the capacity of highway and transportation systems.

COVID-19 altered travel patterns in the U.S. Studies have analyzed the effect of the pandemic on travel mode, including working from home, but few have focused on automobile ownership—a relationship with potentially long-term consequences for accessibility, household budgets and debt, and policy efforts to meet climate goals.To understand the association between the pandemic and automobile ownership, we rely on a unique credit panel dataset from Experian and examine three different automobile loan-related outcome measures: annualized growth rate of new automobile loan balances, average new loan size, and the number of new loans. We focus specifically on changes across loans in neighborhoods by race/ethnicity, hypothesizing larger increases in automobile debt in Black and Latino/a neighborhoods, where workers are less likely to be able to telework. The annualized growth rate of new automobile loans increased during the pandemic across all neighborhoods by race/ethnicity, increasing most rapidly in Latino/a neighborhoods. Controlling for other factors, loan size increased similarly across neighborhoods by race/ethnicity. The increase in automobile lending in Latino/a neighborhoods, therefore, likely was explained by a significant uptick in the number of new loans.The growth in automobile lending during the pandemic was potentially prompted by pandemic-induced changes in the need for automobiles and facilitated by an expanded social safety net. As the pandemic and its various forms of public financial assistance recede, the findings underscore the importance of ongoing assistance in enabling automobile ownership or shared access among households with limited means whose livelihoods depend on the access that vehicles provide.

Daily vehicle travel collapsed with the onset of the COVID-19 pandemic in early 2020 but largely bounced back by late 2021. The pandemic caused dramatic changes to working, schooling, shopping, and leisure activities, and to the travel associated with them. Several of these changes have so far proven enduring. So, while overall vehicle travel had largely returned to pre-pandemic levels by late 2021, the underlying drivers of this travel have likely changed.To examine one element of this issue, we analyzed whether patterns of daily trip-making shifted temporally between the fall of 2019 and 2021 in the Greater Los Angeles megaregion. We used location-based service data to examine vehicle trip originations for each hour of the day at the U.S. census block group level in October 2019 and October 2021. We observed notable shifts in the timing of post-pandemic PM peak travel, so we examined changes in the ratio of mid-week trips originating in the early afternoon (12–3:59 PM) and the late afternoon/early evening (4–7:59 PM).We found a clear shift in the temporal distribution of PM trip-making, with relatively more late PM peak period trip-making prior to the pandemic, and more early PM peak trip-making in 2021. The peak afternoon/evening trip-making hour shifted from 5–5:59 PM to 3–3:59 PM. We also found that afternoon/evening trip-making in each year is largely explained by three workplace-area/school-area factors: (1) the number of schoolchildren in a block group (earlier); (2) block groups with large shares of potential remote workers (earlier), and (3) block groups with large shares of low-wage jobs and workers of color (later, except for Black workers in 2021). We found the earlier shift in PM peak travel between pre- and late-pandemic periods to be explained most by (1) higher shares of potential remote workers and (2) higher shares of low-wage jobs and workers of color. These findings suggest that the rise of working from home has likely led to a shift in PM peak travel earlier in the afternoon when school chauffeuring trips are most common. This is especially true for low-income workers and workers of color.

This report lays out principles to help California policymakers identify an optimal rate structure for a road-user charge (RUC). The rate structure is different from the rate itself. The rate is the price a driver pays, while the structure is the set of principles that govern how that price is set. We drew on existing research on rate setting in transportation, public utilities, and behavioral economics to develop a set of conceptual principles that can be used to evaluate rate structures, and then applied these principles to a set of mileage fee rate structure options. Key findings include that transportation system users already pay for driving using a wide array of rate structures, including some that charge rate structured based on vehicle characteristics, user characteristics, and time or location of driving. We also conclude that the principal advantage of RUCs is not their ability to raise revenue but rather to variably allocate charges among various types of users and travelers. To obtain those benefits, policymakers need to proactively design rate structures to advance important state policy goals and/or improve administrative and political feasibility.

The inexorable rise in personal travel in the 20th century has given way to stagnation in the 21st, a phenomenon some call "peak travel." We use 2003–2019 data from the American Time Use Survey to explore whether and why personal travel per capita has stopped growing. We show that time spent on personal travel has been dropping consistently over these years, and suggest that one important cause is likely a dramatic and ongoing decline in the time Americans spend on out-of-home activities. We find significant changes in time spent on many of the 34 activities conducted inside and outside of the home that we examine. Many of these changes appear related to advances in information and communications technology (ICT), as this period saw the quality of in-home ICT continually rising and its real cost falling, resulting in ever-improving gaming, surfing, watching, and streaming options. For example, our data suggest that out-of-home work and shopping time fell significantly during our study period, while in-home time spent on work and education rose. Game playing (presumably mostly computer games) and TV watching in the home both increased dramatically, while attendance at live entertainment, arts, and sports activities fell. Reading and writing fell substantially both inside and outside the home, perhaps replaced by electronic communication. Our findings suggest that increased in-home ICT use may have been associated with 25–30% of the reduction of out-of-home time. We also find a significant increase in sleeping, and a decrease in time spent eating and drinking both inside and outside of the home. Although we deliberately chose to examine time use and travel prior to the COVID-19 pandemic, we suspect that, even as the pandemic fades, the trend toward more time at home and less time spent traveling may well increase further.

In the United States, roughly one-third of students in public and private K-12 schools ride a school bus to school; in Georgia, that share is even higher (46%). But policy differences between and within states complicate explanations of school trip mode choice. To address this and create a consistent choice set, this article uses the 2017 National Household Travel Survey Georgia Add-On to construct a statewide analysis of school trip mode choice among school-bus-eligible students, as Georgia state law requires students receive a bus service if they live 1.5 mi or more from school, creating a consistent choice set. I use a binary logistic regression model and marginal effects to determine factors predicting school bus use on morning trips to school in Georgia among a suite of trip, individual, household, and environmental characteristics. I find that Black students, older students, and students in greater Atlanta are more likely to use a school bus, while students who live further from school, girls, students who have at least one parent with a college degree, and students who have at least one parent with a flexible work schedule are less likely to do so. Additionally, for those who are age-eligible, possessing a driver's license strongly predicts not using a school bus. Notably, neither family income nor family structure are significant predictors of school bus use. Ultimately, these findings have implications for state school bus policy in Georgia and help elucidate who uses this important service so that resources can be directed appropriately.

The COVID-19 pandemic occasioned significant financial distress and uncertainty for many U.S. transit operators. In the face of this crisis, the federal government provided substantial supplemental operating support. To understand how this fiscal turmoil and relief have affected U.S. transit systems, we conducted two nationwide surveys of transit agency staff in 2020 and 2021-2022. While pandemic-induced financial shortfalls affected service in 2020, with capital projects delayed too, these effects became much more muted by 2021/2022. Most systems reported moderate to substantial increases in federal funding during the pandemic, more so than other funding categories. However, nearly half foresee financial shortfalls once federal relief funding expires. Agencies with higher pre-pandemic ridership and farebox recovery are particularly affected by fare revenue losses and more likely to anticipate shortfalls. In the near term, difficulty hiring and retaining front-line workers was a pressing concern, while very few had plans to maintain pandemic fare suspensions.

This study used data from the 2017 National Household Travel Survey California Add-On sample to explore how replacing the current state vehicle fuel tax with a flat-per-mile-rate road-user charge (RUC) would affect costs for different kinds of households. We first estimated how household vehicle fuel efficiency, mileage, and fuel tax expenditures vary by geography (rural vs. urban) and by income. These findings were then used to estimate how much different types of households pay in the current per-gallon state fuel tax, what they would pay if the state were to replace fuel taxes with a flat-rate road-usage charge (RUC) that would generate revenues similar to the current state fuel tax (2.52¢ per mile driven), and the difference in household expenditures between the fuel tax and RUC. We find that rural households tend to drive more miles and own less fuel-efficient vehicles than urban ones, so they pay comparatively more in fuel tax and would pay more with the RUC as well. However, this rural/urban variation is less for the RUC than the fuel tax, so moving to a flat-rate RUC would redistribute some of the overall tax burden from rural households (that drive more miles in fuel-thirsty vehicles) to urban households (that drive fewer miles in more fuel-efficient vehicles). Transitioning from the fuel tax to RUC would also generally shift the fuel tax burden from lower-income to higher-income households, with one exception: expenditures would rise for low-income urban households. However, the variation in the tax incidence between the gas tax and RUC is quite modest, amounting to less than one dollar per week for both urban and rural households at all income levels.

While the COVID-19 pandemic in some way affected every person and enterprise on the planet, the temporary hollowing out of concentrated economic, political, and cultural agglomerations in cities dealt a devastating and potentially enduring blow to the public transit systems that depend on them for so many of their customers. This chapter draws on a survey of 72 U.S. public transit systems and semi-structured interviews with 12 transit agency staff, both conducted in the late summer and early fall of 2020, to consider how the pandemic shocked the transit industry at the outset, and how the industry adapted to deliver transit services. We find that: transit agencies adapted quickly, and many of their changes are now standard operating procedure; the pandemic tended to affect large and small transit agencies differently; transit’s role as a social service provider took on increased visibility and importance; and financial collapse has been averted, but funding shortfalls may become a pressing issue in the years ahead when federal emergency funding runs out. We conclude that while transit systems have adapted remarkably to dramatic change and that federal funding has largely forestalled fiscal crises, the longer term future of public transit in the U.S. remains very uncertain.

The COVID-19 crisis elevated the importance of private vehicles. The pandemic drove riders off public transit and spawned additional car-based activities such as drive-through testing and vaccinations and curbside pick-ups. Yet millions of low-income and non-white households do not own vehicles. This chapter draws on a unique credit panel dataset to examine automobile debt and delinquency in California. In particular, we examine whether automobile debt patterns during the pandemic differed from those during and coming out of the Great Recession (December 2007–June 2009). We also analyze the response to the COVID-19 recession across neighborhoods by income and race. Similar to the situation during the Great Recession, we find that the number of automobile loans per borrower declined. While the automobile debt burden (the ratio between total automobile debt and aggregate income) also declined, it fell far less during the pandemic than during the Great Recession. Moreover, automobile loan delinquencies spiked during the Great Recession but instead continued to drop during the pandemic. Finally, the COVID-19 crisis affected consumers differently by both race and income. Automobile debt burden rose in low-income, Latino/a, and Black neighborhoods, a pattern that preceded but continued unabated during the pandemic. The findings suggest that COVID-19 relief may have helped some families manage their automobile-related expenditures. However, other factors, such as increasing automobile prices, likely contributed to growing debt burdens, a potential source of financial distress.