Congestion fees have recently been presented as the tool to solve all urban problems. Economists vouch for it, city leaders praise it, and only the general public dislike it.
“The general public is dumb”, say some economists. “They don’t know what’s good for them”.
“It will only improve the lives of people who live in the periphery”, say economists living in the center of metropolitan areas.
“You are suspicious for nothing”, they conclude after considering data from other economists living in central cities like London, Stockholm or Singapore.
Well, are they right?
Road congestion tolls can be used for several purposes—to simply collect taxes, reduce air pollution or to reduce traffic congestion in cities. However, can congestion fees really make traffic jams disappear, or is it just another tax we’ll get used to: Something similar to the gas tax and parking fees? What is the difference between doubling the price of fuel or doubling the price of parking and issuing congestion fees at the city entrance? These are the things I attempt to explain in this article.
This article is based on the simple theory explained here: A Unified Theory of Transportation. It is based on the distinction between Static hassle and Dynamic hassle. In a nutshell, comparing travel options requires us to assess the hassle needed in each option: This hassle is comprised of static hassle and dynamic hassle.
Static Hassle: This hassle is a one-time issue and is not related to the trip distance. For example, the need to find parking, payment for parking, the need to wait for a bus at the station, and so on. The price of parking, for example, will be the same if you arrive from a nearby neighborhood or from beyond the Mountains of Darkness.
Dynamic Hassle: This term refers to the hassle of traveling one mile. For example, the price of fuel, traffic jams or the fear of taking the wrong road in an unfamiliar place.
The general hassle for a particular trip equals the static hassle plus the dynamic hassle per mile, multiplied by the number of miles traveled:
TripHassle = StaticHassle + (DynamicHassle * MilesTraveled)
Consider, for example, the hassle of traveling to the city in your private car. This is shown in the following graph as the baseline. We see that for the specific journey there is a certain static hassle (the need to go to a car parked in the street nearby before starting the journey or the need to find parking at the end), and there is also a constant dynamic hassle along the journey that accumulates with each additional mile.
Two other alternatives also appear in the graph:
1) increasing the price of parking—Base + Parking. This graph demonstrates an increase in static hassle relative to the baseline but does not affect the dynamic hassle at all.
2) raising the price of fuel—Base + Fuel. This graph demonstrates an increase in hassle per mile (the dynamic hassle) but does not affect the static hassle at all.
It is easy to see that someone who lives nearby and needs to travel only a short distance will prefer a raise in the price of fuel over a raise in the price of parking, while those who live farther away will prefer a raise in the price of parking and not in fuel. The intersection between the two graphs represents the balancing point.
Our question now is this: What do congestion fees represent? Is it a change of the static hassle (such as parking) or dynamic hassle (such as fuel)?
Well, the truth is that congestion fees aim to change both.
To understand what congestion fees are, we need to start by understanding that traffic congestion is not related linearly to the number of cars on the road. The graph below shows the basic ratio between the number of cars (on the X-axis) and the travel time required (on the Y-axis).
In the example, we see that when there are 1,000 cars an hour, the travel time is at a certain value, and all those cars travel at high speed. We can increase the number of cars to 2,000, 3,000, 5,000, 8,000, and so on: The road is wide enough and open. With more cars, there is a bit more congestion, but the road still allows for a relatively short ride.
With 9,000 to 10,000 cars, things begin to change. At 11,000 cars, traffic suddenly slows because the distances between them are no longer as large as before. For 12,000 cars, the density is too high and the speed drops sharply. For 13,000 cars, the road becomes clogged—a traffic jam of thousands of cars slowed down to a crawl. We all know and have seen it if we live in a big city.
When we include the hassle of a certain journey according to the number of cars on the road, the results look like the following graph:
Ignoring the dotted line for a moment, let us start by examining the three graphs. In all of them, the static hassle is identical, and the reason why is clear. Regardless of the number of cars packed at the city gate, the hassle of finding parking and the need to walk from the parking area to the house remains the same. The difference in dynamic hassle is the interesting part here, and we see that when there are up to 10,000 cars on the road, the hassle per mile is low. With 11,000 cars, the speed is slower; the time for the trip gets longer, and the graph, therefore, is steeper. At 12,000 cars, the required dynamic hassle per mile is very high, and everybody hates driving then.
The dotted line demonstrates what the economists claim will be a congestion fee—a tax paid at the entrance of the city that will succeed (presumably) in lowering the number of cars. On the one hand, since the tax is paid per entrance, regardless of the distance you drive to reach the city, it is an increase in the static hassle, just like parking. On the other hand, since we assume that it succeeds, it lowers the dynamic hassle as the number of cars entering the city goes down.
We will continue to examine this subject using this assumption: namely, that the congestion fees do actually reduce the number of cars on the road during rush hour. Furthermore, we will examine who will be affected by it and how.
Shifting passengers from traveling at rush hours to earlier hours
Take Jane whose circumstances are represented in the graph below. Jane prefers to travel at peak hour, and we try to set a congestion fee that would make her leave for work an hour earlier. The first question to answer is the following: Why isn’t Jane leaving for work earlier? Let us examine Jane’s considerations in the graph and ignore the dotted line for now.
Jane can travel at peak time. In this alternative, Jane has a high dynamic hassle, and to understand why Jane prefers it, we need to look at the static hassle of that alternative against earlier commutes. For Jane, an earlier commute would require less dynamic hassle but higher static hassle. She might simply not like getting up early in the morning. Perhaps she might be a teacher, and getting to school before it opens will just make her wait at the gate. For her, it is better to drive 40 min in slow traffic than 25 min on an open road and arriving work too early. The static hassle is simply too great.
Looking at the graph, we can see that the two alternatives for people like Jane meet at a certain distance from the city. Beyond this point, the distance is too big, and despite the desire to avoid the unnecessary static hassle, the dynamic hassle is very high. If someone lives farther from the destination, that person would prefer to travel an hour or so with light traffic, avoiding a two-hour slow crawl, even if it means arriving very early to the office.
So, who will be influenced and how high should the fee be?
Let’s look at the dotted line representing a successful congestion fee now. To get Jane to avoid rush hour, we need to have a fee higher than the static hassle of driving early. As we assume that the congestion fee is successful and lowers the number of cars during peak hour, it will be equal (parallel) to the static hassle of the early morning hour.
The impact of the fee is limited.
1) As we have seen before, those that live farther away come early even before the toll.
2) If the static hassle of early departure is too high for any person, he or she will not change their traveling time despite the fee.
Say for example, that Jane needs to take her kid to school before going to work. The static hassle involved in having the child at school an hour and a half before opening is so high that the fee cannot influence the decision to travel at peak hours. If the toll is raised even higher, Jane will simply have no choice but to change her place of work or her place of residence. Such a constraint is related to neither the road nor the number of cars; it is simply a different kind of constraint altogether.
Shifting passengers from riding their car at rush hours to taking a train
In this scenario (as displayed in the graph below ), we will attempt to examine the congestion fee that will cause John to transfer from a car ride during peak hours to a train ride (or any other public transportation for that matter). Let us start again by examining the two graphs marking his current options and ignoring the dotted line.
John has two alternatives. The first is to drive by car during peak hours. In the example on this graph, I assumed that John has private parking both at home and work; therefore, the static hassle of this alternative is almost zero, while the dynamic hassle rises steeply due to traffic jams.
The second alternative is to travel by train. Here, the dynamic hassle is very low, but the static hassle is high. John has to drive to the station, park there, wait for the train. Later, he has to walk from the designated train stop to the office, and it is the same on the way back. The static hassle is, therefore, very high.
Notice the intersection of these two graphs. There is of course a distance where people like John would prefer to take the train. If the alternative is a two-hour of go-break-go-break in crawling traffic versus spending half an hour to the train station for a quick half-hour ride to the destination, the train ride would be prioritized. It appears clear that there is a point beyond which people will prefer a train, while for short-range distances, they would prefer using their cars.
Let’s try to set a congestion fee that will shift John’s preference to the train at the dotted graph. This line represents John driving his private car after the congestion fee. Now he has a static hassle created by the fee, but since we assume that it reduces traffic, there is also a lower dynamic hassle.
The chart shows that there is a limited area that will be affected by the fee. Two observations can be made:
1) For anyone living beyond this area, they would have been using the train even before the congestion fee was imposed.
2) For those living closer to the city, even with the toll, they would still prefer to drive a car.
I draw your attention to the fact that the graph was drawn in a very specific way as if the toll is high but the traffic load on the road is not really falling. If the traffic load will change much, as some economists suggest, the area of impact of the congestion fee would be very small. In fact, it would be ineffective for passengers shifting to public transportation unless the fee was extremely high.
In all cities where congestion fees were claimed, these fees were often accompanied by a significant improvement in public transportation infrastructure. In fact, this infrastructure improvement is much more responsible for changing travel patterns than the fee. The congestion fee in those cities only served as a psychological catalyst. It is easy to support this claim by reviewing recent studies examining the effect of doubling the congestion fee—it had virtually no effect. Claiming that the fee is the main drive makes little sense.
The reverse effect of a successful congestion fee
A successful congestion fee could undermine its own success. The basic assumption is that there is a price at which people will refrain from traveling to the city at peak hours. It treats all people as if they were identical in their preferences, but is that really the case? The graph below can help us answer that question. It features a person that prefers not to work in the city due to the terrible traffic.
Comparing the two hassle graphs—with a fee and without a fee—we can see that when the congestion fee really reduces the dynamic hassle, the two graphs intersect. It is obvious that there is a point beyond which the congestion fee actually reduces the overall hassle.
For John, our example in this graph, the hassle required before imposing the congestion fee is simply too high. Once the congestion charge reduces traffic during peak hours, he will definitely prefer to work in the big city. John is an example of a typical high-tech worker. His time is limited and expensive; however, the cost of the congestion fee constitutes a very small part of his salary and may even be covered by his employer.
We see that there is a range in which people “just wait” for any solution that will reduce the hassle in order to enter the city (and raise the hassle again). This is the induced demand: the very same reason that adding more lanes to the road doesn’t solve the congestion. This same effect could be demonstrated for a person who currently travels by train or who travels early in the morning to avoid driving at peak hour. Some will now prefer switching to driving their cars despite the cost of the fee if traffic is reduced and time is saved.
The congestion fees have a hidden mechanism that contradicts its original purpose, which enables only limited real effect on traffic. For it to actually work, it needs to be extremely high to discourage even people for whom time is generally more costly than money.
As we saw in the last graph, congestion fees create a situation in which we replace some of the passengers at peak hours. If they are high and effective, they preserve the right of way to those for whom time is more expensive than money; that is, the rich. Quite clearly, high-income people will be able to continue to live in the suburbs, and the poor will have to choose between living in the city or finding work in the suburbs.
Delayed effects of the congestion fee
Changing one’s place of residence or workplace is one of the delayed effects of a truly high fee. Total avoidance of traveling to the city center can reduce the congestion as long as the toll remains out of reach for many people. In my next post, I will discuss the delayed effects of the congestion fee that results in people and businesses reconsidering their location.