Last week, I took a look at some new research from the Netherlands that estimated the benefits of public transport for car travel times based on data from 13 “natural experiments” – public transport strikes. The Dutch researchers found that PT provided significant congestion reduction benefits – around €95 million per annum, equal to 47% of PT fare subsidies.
While the data was specific to Rotterdam, I’d expect to find similar results in most other cities with half-decent public transport networks. The whole thing got me wondering: Is there any similar evidence from New Zealand?
Fortunately for PT users and drivers, but unfortunately for researchers, potential PT strikes have mostly been averted over the last few years. However, Wellington did experience a “natural experiment” of sorts back in June 2013, when a major storm washed out the Hutt Valley railway line:
The Hutt Valley rail line was out for six days, including four working days. During that period, things got pretty ugly on the roads, as the motorway into downtown Wellington didn’t have enough capacity to accommodate people who ordinarily commuted in by train.
The Ministry of Transport (among others) very cleverly observed that this was a great opportunity to learn something about the impact of PT networks on road congestion. During the rail outage, they surveyed around 1,000 Wellington commuters about their travel experiences. According to their report, they found that:
- The closure of the Hutt Valley rail line put significant pressure on the road network. Delays for commuters were most severe on the Monday following the storm. Traffic on State Highway 2 was severely congested, with morning peak hour conditions lasting two hours longer than usual
- 80 percent of Wellington commuters from the Hutt Valley and Wairarapa experienced a longer than usual trip
- 32 percent of them experienced delays of over an hour
- the severity of commuter delays lessened over the week, with the number of commuters from the Hutt Valley and Wairarapa experiencing delays of over an hour halving by Wednesday 26 June
Essentially, what happened was that a bunch of people who ordinarily caught the train from the Hutt Valley couldn’t do that due to the storm damage. A quick eyeballing of MoT’s graph of daily rail patronage suggests that around 4,000 people had to make other travel arrangements:
Almost half of the rail commuters from the Hutt Valley opted to drive instead, while the remainder chose to take replacement buses or to stay at home instead. This had a serious impact on motorway traffic, as shown on this graph of hourly southbound traffic volumes. On a normal day (the green or blue lines), traffic volumes peak at around 7-8am, and fall off sharply after that.
By contrast, on Monday 24 June, when the rail line was out, people were still travelling in (slowly) until almost 11am. That’s some serious congestion:
Based on survey data, MoT estimated that the storm damage increased average travel times during the morning peak by 0.329 hours (20 minutes) on Friday 21 June, 0.309 hours (18.5 minutes) on Monday 24 June, and 0.230 hours (14 minutes) on Wednesday 26 June. It then used those estimates of average delay for people travelling at peak time to estimate the added cost of congestion that arose as a result of the Hutt Valley rail line outage:
In short, a four-day breakdown in part of Wellington’s public transport network cost morning peak travellers around $2.66 million in lost time. If we assume that there was a similar level of delay during the afternoon peak, when people are commuting out of downtown Wellington, the total cost would be roughly double that – $5.32 million.
This can give us a rough estimate of the value of public transport for congestion relief in Wellington. Extrapolated out over a full year (i.e. 250 working days), these results suggest that the Hutt Valley rail line saves drivers the equivalent of around $330 million in travel time (i.e. $5.32m / 4 days * 250 working days).
That is a very large number. According to an Auckland Transport report comparing Auckland and Wellington rail performance, Wellington’s overall rail network only cost $81.2 million to operate in 2013. 56% of operating costs were covered by fares, meaning that the total public subsidy for the network is around $36 million per annum.
On the back of these figures, it looks like Wellington’s drivers are getting a fantastic return from using some fuel taxes to pay for PT rather than more roads. The travel time savings associated with the Hutt Valley line alone are nine times as large as the operating subsidy for the entire Wellington rail network.
There are two caveats worth applying to these figures, one practical and one methodological.
First, it’s likely that the value of rail for congestion relief is unusually high in Wellington due to the shape of the city. Here’s a map of Wellington’s population density and infrastructure in 2001 and 2013 (from my analysis of urban population density). Dormitory suburbs extend linearly up the Hutt Valley and towards Porirua and the Kapiti Coast. Everyone travelling from those places to downtown Wellington are funnelled through a single transport corridor running along the shoreline of the harbour:
In Wellington, losing the rail line means pushing everyone onto a single road. (Unlike Rotterdam, cycling isn’t especially viable due to the lack of safe infrastructure on this route.) In other cities, there tend to be a greater range of alternative routes, which spreads around the traffic impacts.
Second, these results aren’t as robust as the Rotterdam study, due to their use of survey data rather than quantitative measures of traffic flow and speed. They’re not likely to be totally wrong, but it’s likely that people over- or under-estimated commute times, or that the survey wasn’t representative of all travellers (which could invalidate MoT’s extrapolation to all morning peak travellers).
However, the increasing availability of real-time data on traffic speeds from GPS devices means that the next time this happens, it will be possible to measure the impacts in much greater detail and with greater precision. The Rotterdam study offers some good methodological insight into how best to do that – it looks at transport outcomes at specific locations over a long period of time, and controls for seasonal and weekday effects that may influence transport outcomes.
Lastly, it would be really interesting to see some similar analysis done for Auckland. I’m sure that there have been a number of full or partial rail network outages, either due to bad weather or scheduled track upgrades. Perhaps it would be worth taking a look at congestion on those days.