On December 19, 2019, the U.S. Census Bureau released the five-year estimates from the American Community Survey (ACS) conducted from January 1, 2014 to December 31, 2018. The five-year estimates are available for all census geographies, regardless of population, and draw upon a much larger sample of respondents than the one-year estimates, and thus have smaller margins of error. While the five-year estimates are more statistically reliable (particularly for smaller geographic areas), they are also less current and may mask short-term changes from one year to another.[1]
An October analysis of the 2017 and 2018 one-year estimates (released September 26, 2019) that appeared in ETW found that teleworking continued an upward trend nationwide, while the share of commuters driving alone to work ticked down in several cities. In particular, Seattle, San Francisco, San Diego, Philadelphia, and Detroit saw substantial drops in the share of workers driving alone to work, while transit use remained mostly stable, fluctuating by less than 1% in most cities. Seattle and San Francisco both also experienced notable increases in the share of commuters biking or walking to work.
While the October overview shed light on notable changes in commuting over a one-year period, this analysis provides a glimpse into longer-term changes in commute patterns over a 10-year period by comparing the 2014-18 ACS with the 2009-13 ACS.
Table 1. Change in Mode Share to Work for Urbanized Area and City Limits for Top 15 Cities (2009-13 to 2014-18)
| City | Drive Alone | Carpool | Transit | Bike | Walk | Home |
| Atlanta (region) | -0.4% | -0.9% | -0.1% | 0.0% | -0.1% | 1.3% |
| Atlanta (city) | -0.3% | -1.5% | 0.2% | 0.2% | 0.2% | 0.8% |
| Boston (region) | -2.1% | -0.5% | 1.2% | 0.2% | 0.0% | 0.7% |
| Boston (city) | 0.5% | -1.1% | 0.1% | 0.4% | -0.5% | -0.4% |
| Chicago (region) | -1.0% | -0.8% | 0.9% | 0.1% | -0.1% | 0.8% |
| Chicago (city) | -1.3% | -1.5% | 1.6% | 0.4% | -0.1% | 0.5% |
| Dallas (region) | -0.6% | 0.0% | 0.0% | 0.0% | 0.1% | 0.7% |
| Dallas (city) | -0.9% | 0.3% | 0.1% | 0.0% | 0.0% | 0.6% |
| Detroit (region) | -0.2% | -0.2% | -0.3% | 0.0% | 0.1% | 0.5% |
| Detroit (city) | -0.9% | 1.0% | -1.5% | 0.4% | 0.4% | 0.7% |
| Houston (region) | 1.0% | -1.1% | -0.3% | -0.1% | -0.1% | 0.6% |
| Houston (city) | 1.5% | -1.4% | -0.5% | -0.1% | -0.2% | 0.4% |
| Los Angeles (region) | 1.4% | -0.9% | -1.0% | -0.1% | -0.2% | 0.5% |
| Los Angeles (city) | 2.4% | -1.3% | -1.6% | 0.0% | -0.2% | 0.5% |
| Miami (region) | 0.0% | -0.7% | -0.2% | 0.0% | -0.2% | 0.9% |
| Miami (city) | 1.0% | -1.8% | -1.3% | 0.1% | -0.5% | 1.4% |
| New York (region) | -0.7% | -0.4% | 0.8% | 0.1% | -0.2% | 0.4% |
| New York (city) | -0.1% | -0.4% | 0.4% | 0.3% | -0.3% | 0.2% |
| Philadelphia (region) | -0.8% | -0.3% | 0.0% | 0.0% | -0.1% | 1.0% |
| Philadelphia (city) | 0.5% | -0.6% | -1.1% | 0.1% | -0.1% | 0.8% |
| Phoenix (region) | 0.0% | -0.5% | -0.3% | 0.0% | -0.1% | 0.8% |
| Phoenix (city) | -0.5% | 0.3% | -0.3% | 0.0% | -0.3% | 0.7% |
| San Diego (region) | 0.3% | -1.3% | -0.2% | 0.0% | 0.1% | 0.6% |
| San Diego (city) | 0.0% | -0.6% | -0.2% | 0.0% | 0.0% | 0.4% |
| San Francisco (region) | -3.4% | -0.6% | 2.3% | 0.3% | 0.5% | 0.4% |
| San Francisco (city) | -4.1% | -0.2% | 1.6% | 0.5% | 1.4% | -0.5% |
| Seattle (region) | -2.0% | -0.5% | 1.4% | 0.1% | 0.4% | 0.6% |
| Seattle (city) | -4.0% | -1.5% | 2.6% | 0.1% | 1.9% | 0.7% |
| Washington, DC (region) | -0.3% | -0.7% | -0.7% | 0.2% | 0.1% | 0.9% |
| Washington, DC | 0.3% | -0.6% | -3.5% | 0.9% | 0.9% | 1.3% |
Source: 2009-13 and 2014-18 ACS Five-Year Estimates
Between 2009-13 and 2014-18, 10 of the 15 regions and 8 of the 15 core cities profiled experienced drops in the share of workers driving alone to work. Some of the same cities that saw notable decreases in the share of commuters driving alone to work between 2017 and 2018 also experienced substantial drops between 2009-13 and 2014-18, particularly San Francisco (-3.4% regionally, -4.1% citywide) and Seattle (-2% regionally, -4.0% citywide). Both cities also had the largest increases in transit mode share from 2009-13 and 2014-18, suggesting that these changes could be part of a broader shift towards transit, walking, and biking. In the case of Seattle, the declining share of workers driving alone and rise in transit use, walking, and biking has been noted in reporting and local surveys over the past two years as a reflection of the region’s investment in transit and pedestrian-bicycle infrastructure.
While many cities saw decreases in workers driving alone, this mode share increased over the 10-year period in 7 cities, most notably in Los Angeles (2.4% in the city, 1.4% regionally), Houston (1.5% in the city, 1.0% regionally), and Miami (1.0% in the city). Boston saw a drop in driving alone regionwide (-2.1%) but an increase within the city (0.5%), consistent with the divergent pattern seen during the 2017-18 period, suggesting that the one year data was indicative of a larger trend.
The divergence between the short term and long term commuting patterns grows starker with transit mode shares. Between 2009-13 and 2014-18, transit mode share increased substantially in San Francisco (2.3% regionally, 1.6% citywide), Chicago (1.6% citywide), Seattle (1.4% regionally, 2.6% citywide), and Boston (1.2%, regionally, 0.1% citywide). With the exception of Seattle and Chicago, these cities experienced notable declines in transit mode share between 2017 and 2018 (-1.2% in San Francisco proper and -2.8% in Boston proper). In San Francisco and Boston, the long-term increase and short-term drop in transit mode share could reflect a shift from transit to active transportation (walking and biking increased in San Francisco as transit use decreased in 2018), short-term volatility in response to service changes, or other mixed changes in commuting patterns (walking, driving alone, and telework cumulatively increased by nearly the same amount as the drop in transit mode share in Boston in 2018).
On the other hand, Washington D.C. and Philadelphia saw short-term increases in transit mode share (1.8% in DC proper and 2.5% in Philadelphia proper), but a long-term decrease in Washington (-0.7% regionally and -3.5% in the district) and Philadelphia (-1.1%). The remaining cities with significant drops in transit mode share (-1.5% in Detroit proper, -1.6% in Los Angeles proper, -1.3% in Miami proper) also experienced drops between 2017 and 2018. In the case of Washington and Philadelphia, the long-term dip in transit use in contrast to the short-term increases could reflect early signs of successful efforts to expand/improve transit service or encourage ridership.
The changes in the share of workers walking over the 10-year period mostly occurred in Seattle (+ 1.9% citywide), San Francisco (+ 1.4% citywide), and Washington (+ 0.9% citywide), all of which also experienced a rise in active transportation between 2017 and 2018.
Comparing the 2009-2013 and the 2014-2018 ACS estimates show that commuting patterns in many cities are fairly stable, with driving alone ticking down in several cities and transit use ticking up in a few cities (Seattle, San Francisco, and Boston). Few cities apart from Seattle, Washington, and San Francisco saw any major change in biking and walking, while most cities experienced a small but consistent uptick in telework. In cases like Seattle, the short and long-term commute trends suggest the region’s efforts to boost transit use, biking, and walking are succeeding. Data collected and released in 2020 and beyond will provide researchers and policymakers in regions across the country with a better sense of whether converging or diverging short and long-term trends are an early sign of broader changes in commuting patterns, and whether these changes reflect the success or shortcoming of their local transportation plans.
Appendix: Mode Share to Work by Urbanized Area and City Limit: 2014-2018 ACS
| City | Drive Alone | Carpool | Transit | Bike | Walk | Home |
| Atlanta (region) | 76.8% | 9.4% | 3.4% | 0.2% | 1.4% | 7.1% |
| Atlanta (city) | 67.6% | 6.5% | 10.5% | 1.0% | 4.9% | 7.8% |
| Boston (region) | 65.4% | 7.2% | 14.3% | 1.1% | 5.6% | 5.0% |
| Boston (city) | 38.8% | 5.9% | 33.4% | 2.2% | 14.7% | 3.3% |
| Chicago (region) | 68.8% | 7.8% | 13.1% | 0.7% | 3.2% | 5.0% |
| Chicago (city) | 49.0% | 7.8% | 28.4% | 1.7% | 6.5% | 4.8% |
| Dallas (region) | 80.5% | 10.0% | 1.7% | 0.1% | 1.3% | 5.1% |
| Dallas (city) | 76.5% | 11.1% | 4.1% | 0.2% | 1.9% | 4.7% |
| Detroit (region) | 83.9% | 8.4% | 1.5% | 0.3% | 1.5% | 3.6% |
| Detroit (city) | 69.2% | 13.4% | 7.2% | 0.7% | 3.8% | 3.8% |
| Houston (region) | 80.4% | 10.3% | 2.3% | 0.3% | 1.3% | 4.0% |
| Houston (city) | 77.1% | 10.9% | 3.8% | 0.4% | 2.0% | 3.7% |
| Los Angeles (region) | 75.0% | 9.7% | 5.3% | 0.8% | 2.6% | 5.2% |
| Los Angeles (city) | 69.4% | 8.8% | 9.4% | 1.0% | 3.5% | 6.1% |
| Miami (region) | 78.2% | 9.1% | 3.5% | 0.6% | 1.6% | 5.4% |
| Miami (city) | 69.7% | 8.4% | 10.0% | 1.0% | 3.8% | 4.8% |
| New York (region) | 48.4% | 6.4% | 32.6% | 0.7% | 6.1% | 4.3% |
| New York (city) | 22.3% | 4.5% | 56.2% | 1.2% | 9.9% | 4.2% |
| Philadelphia (region) | 71.8% | 7.6% | 10.3% | 0.7% | 3.8% | 4.7% |
| Philadelphia (city) | 50.9% | 8.2% | 25.0% | 2.1% | 8.4% | 3.8% |
| Phoenix (region) | 76.2% | 11.1% | 2.2% | 0.9% | 1.5% | 6.5% |
| Phoenix (city) | 74.5% | 12.6% | 3.1% | 0.7% | 1.6% | 5.7% |
| San Diego (region) | 76.5% | 8.7% | 3.0% | 0.7% | 2.6% | 6.9% |
| San Diego (city) | 74.8% | 8.7% | 3.8% | 0.9% | 3.0% | 7.1% |
| San Francisco (region) | 54.4% | 9.6% | 19.6% | 2.4% | 5.6% | 6.3% |
| San Francisco (city) | 32.9% | 7.3% | 34.2% | 4.0% | 11.4% | 6.6% |
| Seattle (region) | 66.9% | 9.9% | 10.6% | 1.2% | 4.2% | 6.0% |
| Seattle (city) | 47.6% | 7.3% | 21.8% | 3.6% | 11.0% | 7.2% |
| Washington, DC (region) | 63.4% | 9.3% | 15.7% | 1.0% | 3.6% | 5.5% |
| Washington, DC (city) | 34.3% | 5.3% | 34.8% | 4.5% | 13.1% | 6.1% |
[1] Margins of error vary for each estimate and geographic level. More information can be found here. Statistical significance of changes in means of commuting for work can be found for all geographies in the 2018 ACS Comparison Tables using the Census online data retrieval tool.
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