The US National Transit Database (NTD) is out for 2008! (Yes, a one year lag counts as fast in this business.) For those of you who aren’t compulsively drawn to spreadsheets, Cap’n Transit tries to get to the bottom of farebox recovery, the percentage of operating costs paid by fares.
Farebox Recovery Ratio Agencies 70-200% Lincoln Tunnel buses, inclined planes, Hudson River ferries, SEPTA [Philadelphia] trolleybuses 40-69% Big city rail, college town buses 30-39% Big city bus and light rail 0.1-29% Small and medium city bus and light rail, plus assorted boondoggles 0 Free services
Farebox recovery is not, of course, the only thing that matters. The ratio combines three separable factors that have completely different significance, and that can be explored separately in the database:
- Operating cost per hour of service, which is mostly about labor rates and management efficiency.
- Riders per hour of service, which is about the efficiency with which the system attracts ridership.
- Average fare revenue per rider, which is about fare levels, fare structure, and fare enforcement.
(The farebox return ratio (fare revenue / operating cost) is the product of the latter two factors, divided by the first.)
My own frustration with the National Transit Database is that it assumes that technology is the most important distinction between transit services. This is not an ideological statement on the government’s part, more just an effect of the way transit agencies tend to keep data. A big transit agency has separate operating divisions for rail, trolleybus, standard bus, etc, so it’s easy to report data in those terms.
But the “bus” category combines a whole bunch of totally unrelated things that happen to be done with the same versatile vehicle, including:
- Frequent Networks. Frequent, all day service on major lines, carrying passengers both ways all day. Justified by ridership goals.
- Peak Express. One-way services running only during the rush hour, running full one direction and usually empty out-of-service the other.
- Local Coverage services. Infrequent services wandering around in low-density areas, carrying few people most of the time. This is every agency’s lowest-ridership service. It is never justified by ridership goals, but rather by social needs or expectations of equity, or what the Brits and Aussies call “social inclusion.”
In most networks I look at, at least 80% of the service falls clearly into one of these categories. The largest gray area is between Frequent Networks and Local Coverage services. Sometimes a line is a Frequent Network spine with Coverage branches, or sometimes a line is just on the edge where it might be grown in to a Frequent Network route or might be shrunk into a Coverage service. In my experience, good network planning has the effect of increasing the separation between these two types of service, and thus increasing the clarity of the agency’s thought about the conflicting purposes that they represent.
So the regular “bus” category is a mixture of very unlike things. On the other hand, the Philadelphia trolleybuses jump out in Cap’n Transit’s table because they are all Frequent Network services. The infrastructure that trolleybuses require is cost-effective only if you use it intensively, so there are not many low-frequency trolleybus lines in the world. The Philadelphia trolleybuses are an especially small group of routes very focused on high demand areas. But the ridership outcomes don’t have anything to do with the fact that these are trolleybuses. It’s just that trolleybuses have to run frequent services, and are thus a subset of Frequent Networks, which attract high patronage. Most Frequent Network services are run by standard buses, but the standard bus can be used in so many other ways that the NTD category “bus” lumps them all together and thus obscures this crucial distinction.
In fact, the Cap’n’s table, and the NTD in general, are great for throwing up spurious statistics about the performance of different technologies. Trolleybus manufacturers can say: Look how productive trolleybuses are! This is another great example of the statistician’s warning: ‘Correlation is not causation!‘ Trolleybuses can only be used in high-ridership places, so they tend to end up with high ridership if you look at them in isolation. But that doesn’t mean you need the trolleybus to get the ridership. What matters is where the service runs, how frequently, how fast, and how reliably.