Breaking Down Farebox Recovery Ratios

In the last post I highlighted the agencies that had the highest farebox recovery ratios and showed that many of them are either rail-only agencies and/or are located in the Northeast. In the last post I included the table below showing the farebox recovery ratios of various agencies. This post will explore what goes into having a high farebox ratio and some of the tradeoffs that agencies make to get there.

Transit Agencies by Farebox Recovery2

The high performance of rail-only agencies is likely linked to the kinds of services that tend to be provided with rail and ones that tend to be provided by bus. Rail generally offers much greater capacity and usually faster speeds, which attracts more riders. Meanwhile, buses tend to be able to provide more coverage, making sure that more people in the region have access to the public transportation network.

While providing coverage is certainly not the only public policy goal that reduces cost-effectiveness, it provides a good example of how public transit is used to meet a variety of societal goals. That’s why cost-efficiency and farebox recovery ratios cannot be the only measured used to evaluate public transit.

With that said, the characteristics of rail networks lead them to focus on peak-hour, commuter-oriented services when there is the most amount of travel along major corridors (for example from suburban areas into a major city center). Meanwhile buses will often provide services to far-flung neighborhoods. In a future post, I will break down these numbers further and look at individual modes operated by these agencies. For now though, it’s sufficient to say that rail tends to have higher farebox recovery ratios than buses but that many agencies operate both.

Now let’s look in a bit more detail at what drives the farebox ratios for these agencies. To do that, we can break down both the operating costs and farebox revenue numbers in a bit more detail. The farebox recovery ratio is driven by a combination of the following three components:

  1. The cost per mile to run each vehicle (train car or bus)
  2. How many people ride in each vehicle (which can be calculated as the number of passenger miles divided by the number of vehicle miles)
  3. How much those people pay for their ride (the average fare or average fare/mile)[1]

The table below breaks down these three figures for each agency (all data is from the National Transit Database):

Breakdown of Farebox Recovery2

Perhaps the most striking part of the table above is just how important ridership is to these figures. At its most basic, having full trains and buses is a huge boost toward higher farebox recovery ratios. Out of the top 10 agencies, only one agency has, on average, fewer than 15 people per vehicle and out of the bottom 10 agencies, only one has at least 15 people.[2] The average for all agencies was 17 people/vehicle.

Many of the agencies with higher farebox recovery ratios also had higher average fares and fares per passenger mile meaning that they (generally) had more people riding and were (generally) charging them more for those rides. This can be seen with the example of the Port Authority Trans-Hudson Corporation (PATH), which has the highest operating cost/vehicle mile but is offset by having over 25 people per vehicle and the second highest fare per mile ($0.47/mile) resulting in the 9th highest farebox recovery ratio overall.

Take a look through the tables and leave a comment with what jumps out to you!



[1] There are many reasons why agencies choose not to charge the highest fares they could including wanting their services to be accessible to more people in the region served and those are policy decisions that many public transit agencies make around the country. So just as much as actual performance can drive farebox recovery ratios, so can public policy choices.

[2] As measured by the number of passenger miles per each vehicle mile.


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