A Closer Look: Urban Transit Systems


Labor Productivity for Urban Transit Systems

On May 28, 2019, the Bureau of Labor Statistics (BLS) updated measures of productivity and costs through 2017 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).

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 2017, urban transit systems employed 404,000 workers, nearly as many as the air transportation industry (about 468,000).

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 2017, the trends in output and hours worked reversed, with output declining by an annual average of 0.9 percent while hours worked grew by an average of 2.6 percent. Consequently, in 2017, labor productivity for urban transit systems was lower than in 2007.

Chart 1. Urban transit systems indexes of labor productivity

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. Urban transit systems by major mode, passenger miles traveled (in millions), 200717
YearTotal bus (1)Regional rail (2)Heavy railSurface rail (3)

2007

20,42411,13716,1381,930

2008

21,20411,03216,8502,081

2009

21,10511,12916,8052,196

2010

20,57410,77416,4072,173

2011

20,70911,38417,3172,294

2012

21,42311,19417,5162,415

2013

21,55311,81918,0052,481

2014

21,73211,69118,3392,583

2015

21,20311,78218,2832,532

2016

20,82211,85618,3572,667

2017

19,62712,33617,5912,690

Average rate of change, 200717

−0.4%1.0%0.9%3.4%
Footnotes:

Notes:

(1) This includes bus, commuter bus, and bus rapid transit.

(2) This includes commuter rail and hybrid rail.

(3) This includes light rail and streetcar.

Source: U.S. Bureau of Labor Statistics.


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 2.7 billion in 2017 an average rate of 3.4 percent annually. The next fastest growing transit mode was regional rail, which increased PMT from 11.1 billion to 12.3 billion over the same period (an average annual rate of 1.0 percent). On the other hand, passenger miles traveled on buses have fallen between 2007 and 2017, by an annual average of 0.4 percent.

The one-year decline of bus PMT contributed the most to the decline of output in 2017. Because bus systems are in use in cities nationwide, and many of them had declines in 2017, it is hard to pinpoint causes of the decline.

The other large decline in transit PMT by mode in 2017 was in heavy rail, which reversed a gain in the previous year. This decline is easier to analyze because there are fewer operators, and one dominates the mode by volume: the New York City Subway. In 2017 the New York City Subway contributed 42 percent of the net heavy rail PMT decline. Year-on-year PMT for the system fell by 3.0 percent, following a 1.3 percent increase in 2016.

One culprit is service disruptions. Chart 2 shows that average annual on-time performance was already falling prior to 2017.[1] However, operational challenges reached an inflection point in summer 2017, and were widely reported in the national news media. This could have been a factor in the decline in ridership as passengers found the service to be less reliable. (The Washington [DC] Metro was the second largest contributor to the net decline in 2017, and suffered similar service disruptions during the year.)

Chart 2 On-time performance of the New York City Subway

Chart 3 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 2017 was unique among the illustrated industries.

Chart 3 Labor productivity indexes, selected transportation 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.[2] The Census Bureau’s 5-year American Community Survey provides data on commuting modes.[3] From the 2009 release (2005-09 data) through the 2017 release (2013-17 data), the share of Americans who commute to work using public transportation reported by the ACS has remained stable at about five percent. 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.[4] 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.


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. This data comes from the NTD and is 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 is the superior data for measuring labor productivity. This is because PMT best captures 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 is used because it includes 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 provides employee hours worked for all modes (albeit only for directly operated transit systems).

 

Related resources

Productivity in transit: a new measure of labor productivity for urban transit systems

Industries at a Glance: Transit and Ground Passenger Transportation

Overview of BLS Productivity Statistics

 

Notes

[4] 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: May 28, 2019