A Closer Look: Urban Transit Systems
Labor Productivity for Urban Transit Systems
On April 30, 2021, the Bureau of Labor Statistics (BLS) updated measures of productivity and costs through 2019 for urban transit systems (NAICS 4851). These measures were originally introduced on August 22, 2018. More information can be found in an article written by BLS economists in the Monthly Labor Review (MLR). The current data reference period for these data series lag other service industries, including those in the transportation sector, by one year. BLS cannot publish urban transit systems productivity series until all source data based on the latest fully closed report year are available.
Urban transit systems is a passenger transportation industry primarily operated by state and local governments. There are various modes of transportation included in this industry, including buses, subways, and light rail systems. These systems are of vital importance to the well-being of America’s urban population, as they provide access to jobs, education, health-care, and recreation for millions of people each day. In 2019, urban transit systems employed 419,500 workers, close to as many as the air transportation industry (about 494,400).
In order to measure how efficiently transportation services are provided, the BLS productivity program has developed a measure of labor productivity for urban transit systems. Underlying this measure are series of both output and hours worked. These series make use of data from the Federal Transportation Administration’s National Transit Database (NTD) and from the American Public Transportation Association (APTA).
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Chart 1 shows that labor productivity growth in urban transit systems was modestly positive from 2007 to 2013, growing by an average annual rate of 1.4 percent. Over that period, the average annual growth of output outpaced that of hours worked, 1.5 percent to 0.1 percent. However, between 2013 and 2019, the trends in output and hours worked reversed, with output declining by an annual average of 1.0 percent while hours worked grew by an average of 2.5 percent. Consequently, in 2019, labor productivity for urban transit systems was lower than in 2007.
Urban transit systems include various transportation modes (see the FAQ section below for a full list of these modes). Let’s take a closer look at how transit modes have contributed to industry output growth since 2007.
Table 1 shows that surface rail, which includes both light rail and streetcar, has seen the greatest increase in passenger miles traveled (PMT) over the period studied. Surface rail PMT increased from 1.9 billion in 2007 to 2.6 billion in 2019 – an average rate of 2.5 percent annually. The next fastest growing transit mode was regional rail, which increased PMT from 11.1 billion to 12.8 billion over the same period (an average annual rate of 1.2 percent). While passenger ridership increases may result from new service or greater intensity of passenger use on existing infrastructure, new routes and systems can also contribute to the growth. One new regional rail system opened during 2019, the TEXRail commuter line based in Fort Worth, TX. Also, two new surface rail systems opened: the Oklahoma City Streetcar and the El Paso (TX) Streetcar.
On the other hand, passenger miles traveled on buses have fallen between 2007 and 2019, by an annual average of 0.7 percent. The one-year decline of bus PMT contributed the most to the decline of output in 2019. In 2018, there were 21 city bus systems that had PMT of more than 200 million. Of these largest 21 systems, only 8 increased PMT from 2018 to 2019 (Philadelphia, Houston, Oakland, Baltimore, Las Vegas, Pittsburgh, San Francisco, and Washington, DC). PMT declines were widespread in cities across the nation. Newark and Miami had the greatest declines, with each shedding over 60 million PMT from 2018 to 2019.
The greatest gain in transit PMT by mode in 2019 occurred in heavy rail. The New York City Subway is the largest heavy rail system by far. In 2019, PMT in the New York City Subway rose by 4.7 percent, reversing its ridership decline in 2017 and 2018. The 2019 gain of about 470 million PMT in the New York City Subway was much more significant than all other subways put together, which collectively decreased PMT by about 22 million.
Chart 2 compares the productivity trend of urban transit systems with three other transportation industries for which BLS publishes productivity measures. (Both predominantly passenger- and freight-carrying industries are included here.) Productivity growth in urban transit systems was about the median for these industries between 2007 and 2013. However, urban transit systems’ decline in labor productivity from 2013 to 2019 was unique among the illustrated industries.
Because flat or declining output (ridership) has contributed to the poor productivity performance of transit systems, it can be instructive to look at potential riders’ alternative options. Commuting and other work-related purposes are the most important reason for using urban transit systems. The Census Bureau’s 5-year American Community Survey provides data on commuting modes. From the 2009 release (2005-09 data) through the 2019 release (2015-19 data), the share of Americans who commute to work using public transportation reported by the ACS has remained stable at about 5%. Given the increasing number of overall trips to and from work estimated by the ACS over time, this means more Americans than ever are using transit to commute to or from work.
How do we square this with the decline in overall transit ridership? Presumably, the decline has come from non-work related travel, such as shopping, errands, and social and recreational activities. These are activities where other options could substitute for transit use. Private driving is the most common mode of travel nationwide. Other substitutes can include ride-hailing services, on-line shopping, and social media. Notably, the steady decline in transit ridership nationally since 2014 coincides with the increasing popularity of these information technology-enabled trends.
Chart 3 decomposes the measure of hours worked for urban transit systems. From 2007 to 2013, a modest fall in employees’ average weekly hours (-0.6 percent per year) counteracted a similarly modest rise (0.6 percent per year) in industry employment. (Average weekly hours worked are equivalent to annual hours divided by 52.) As a result, total hours worked for the industry were about the same in 2013 as in 2007, increasing by an average 0.1 percent annually.
From 2013 to 2019, the average increase in employment averaged 1.9 percent per year, compared to a slight uptick in average hours worked per employee of 0.5 percent per year. Thus, industry hours worked jumped up by an average annual rate of 2.5 percent. Over the entire 2007-19 time period measured by BLS, growth in employment was responsible for all of the increase in total hours worked.
Frequently Asked Questions
Q: How is this industry defined?
A: Urban transit systems (NAICS 4851) include establishments that transport the general public over regular routes and on regular schedules within a metropolitan area and its adjacent nonurban areas. This definition encompasses various modes of transportation. Our measure of labor productivity includes city buses, commuter buses, bus rapid transit, trolley buses, heavy rail (i.e. subways), light rail, commuter rail, hybrid rail, streetcars, cable cars, and inclined planes.
Q: How is output defined for urban transit systems and what sources are used to calculate it?
A: The BLS productivity program frequently defines the output of transportation industries (such as air transportation and line-haul railroads) as the distance passengers or freight are carried. Urban transit systems conforms to this precedent. Annual output is defined as the total number of miles that passengers travel in revenue service. These data come from the NTD and are given the acronym PMT (passenger miles traveled).
It is important to distinguish PMT from other types of data used in some measures of efficiency or effectiveness. These include passenger trips, vehicle miles, or seats available. While these alternative metrics have their uses, PMT are the superior data for measuring labor productivity. This is because PMT best capture the total volume of service consumed by the public.
Q: How are passenger miles traveled (PMT) for different modes of transportation aggregated into an industry output index?
A: The total expenses (operating expenses and capital expenses) of the transit modes serve as weights in the aggregation of PMT. In our model, total expenses serve as a proxy for the quality of the transit modes. We assume that municipalities are willing to pay more to build and operate modes of transportation that provide benefits such as speed, reliability, or comfort. Other benefits may accrue to the community such as traffic abatement or pollution reduction. In summary, transportation modes with higher total expenses (such as light rail) are assumed to be of higher quality, and are therefore given more weight in the industry output index.
Q: What sources are used to determine hours worked?
A: Hours worked combines data from both NTD and APTA. APTA provides the count of total industry workers. APTA data are used because they include both directly operated employment (i.e. vehicles are operated directly by a transit agency’s own employees) as well as contracted employment. An adjustment is made to exclude the employment of transportation modes which fall outside the NAICS definition.
Hours worked are then calculated by multiplying the total employment by a measure of average employee hours. However, APTA does not report employee hours. Therefore, we use NTD data, which provide employee hours worked for all modes (albeit only for directly operated transit systems).
 The Department of Transportation’s National Household Transportation Survey measures the purposes of transit trips. However, the survey sample changed between the last two releases, in 2009 and 2017, to include more urban households and cell-phone-only households. This makes it difficult to compare survey results between the two releases.
Last Modified Date: April 30, 2021