In a recent post, Harriet questioned whether our business cases are being founded on a lie. That lie relates to the issue of travel time savings, which form the heart of the “cost benefit analysis process” that guides NZTA’s transport funding decisions.
At a simplistic level, travel time savings seem like an obvious benefit from a transport project.
- If I get from A to B quicker, there’s a benefit because I can now spend that time doing something else rather than travelling.
- Let’s say a new road or public transport project saves 5 minutes for 10,000 people a day, that’s over 800 hours of total savings per day – or 12,600 days of aggregate travel time savings per year.
- Even at a fairly low value of time, you can see how this could add up to a major benefit. Let’s say on average you value this time at $10 an hour (keeping in mind that most travel is for non-commercial purposes) you are creating around $3 million a year of benefit.
This type of benefit generally makes up the vast bulk of the economic justification for transport investment. NZTA themselves highlight that travel time savings dwarf other quantified benefits of investment like safety, environmental impacts and more:
Travel time savings account for the majority (typically around 80%) of ‘conventional’ economic benefits for most transport projects. Thus the unit value of time savings is one of the most important parameters in transport economics (for both demand forecasting and economic appraisal purposes).
So if our transport decision-making was solely guided by cost-benefit analysis, then basically all we would really be interested in is “for every dollar of spend on transport, how do we get the biggest travel time savings?” Or, put differently, how can we cheaply enable people to go faster? This is why projects like the proposed Lincoln Road upgrade, with its hugely wide intersections and horrific pedestrian environment, somehow ends up with a high cost-benefit ratio.
Obviously this immediately raises a bunch of issues, things like:
- What if “going faster” encourages more people to drive, which quickly means they’re no longer going faster?
- What if “going faster” undermines a whole pile of other outcomes we want from spending money on transport, like improved safety or encouraging more people to use sustainable transport options like walking, cycling and public transport?
As Harriet pointed out, these questions have been asked for a while and the data isn’t great in supporting travel time savings. Despite billions in investment largely justified by travel time savings, average travel times have actually stayed about the same.
This data makes the very large focus of cost-benefit analysis processes on travel time savings particularly problematic, as it seems these “savings” get quickly eliminated by what’s known as “induced demand”. We have been talking about induced demand since the very early days of this blog, highlighting how additional road capacity quickly gets filled up, and over time encourages a more dispersed urban form. This isn’t just because people might change the mode of transport they use, as in fact there are many different types of induced demand:
- Time-shift induced demand: This is when people may have previously taken their trip during an ‘off-peak’ or ‘shoulder-peak’ time, but shift to driving during peak hour because there is more capacity available and (at least initially) congestion during peak times has been reduced.
- Route-shift induced demand: This is when people may have previously taken a variety of different routes to get to their destination, but then shift to using the one that was previously congested. I do note that this type of induced demand is likely to benefit the roads that were previously being used, but it still contributes to more potentially unexpected traffic using the route in question.
- Mode-shift induced demand: This is when people who may have previously used public transport, or walked, or cycled the route switch to using their cars, because the reduced congestion has made that a more attractive option.
- Changed destination induced demand: This is a longer term effect, where people will potentially alter where they live or where they work to take advantage of the improvements to the corridor. They may not have previously used this road, but its initial benefits will attract people to locate their homes or jobs somewhere near that road.
- Change of trip frequency induced demand: This is when people might make trips along a certain corridor more often because of the improvements to that corridor. For example, someone may not worry about undertaking their necessary tasks in separate trips along an improved corridor, whereas previously they might have bundled them together into one trip.
Furthermore, such a big focus on travel time savings might actually be counter-productive – as discussed in this article (with a slightly awkward translation):
The experience shows that state-of-the-art practices on planning and project appraisal often result in contradictory conclusions when applied to sustainable mobility policies, particularly at the urban scale. Benefits associated with faster transport are central according to many standard cost-benefit guidelines, providing higher economic return than improving other social and environmental aspects of projects, which paradoxically have increasing social importance in more mature and advanced societies. Therefore, the time trap of standard CBA could support projects transferring public urban space from pedestrians back to car traffic, just because drivers could benefit from a few seconds of time savings. And this would happen despite the fact that European urban policies have decidedly and unanimously bet for car restrictions in city centres.
This fact results in great misunderstandings when CBA is used in public hearings and deliberations. Mobility and transport policies at both urban and interurban scales have today in Europe a comprehensive set of goals such as the improvement of accessibility, sustainability, liveability and affordability, well beyond achieving faster travel. The emergence of virtual technologies as well as the changing values of new generations makes evident the need to reconsider.
In short, focusing so much on travel time savings in the way we do cost-benefit analyses doesn’t really match up with the “broader outcomes” that most transport policies and strategies seek to achieve.
So how might we do things differently? In a way we already are, with cost-benefit analysis being generally less important than “results alignment” in NZTA’s investment assessment framework, which is used to rank projects for funding. This approach appears to be consistent with what happens throughout Europe, where Sustainable Urban Mobility Plans guide decision making. These are described here:
Partly in recognition of the problems with transport modelling, some European cities have changed the way the problem is framed – from meeting forecast travel demand, to achieving a number of social and economic objectives through transport investment. Through sustainable urban mobility plans, different types of projects are favoured. These include: better integrated bus networks, more bus lanes, safer cycling and walking routes, improved park and ride facilities, and traffic calming measures that redesign streetscapes and reduce speed limits to improve mobility for all road users.
Rather than facilitating the movement of motor vehicles, this process emphasises creating safe, reliable and affordable access with less travel and a reduced environmental footprint. It also requires that engineers, urban planners, economists and other specialists sit down with the business and community sectors to build a consensus on what needs to be done. This is in contrast to current engineering-dominated methods.
This doesn’t mean cost-benefit analyses for transport projects are irrelevant, but emphasises the need to do them better and to think about what we want the real, long-run benefits of transport expenditure to be. Is it really about shaving a few seconds off travel time? Is it about having more choice? Is it about safer streets? Less environmental impacts? How might we rank these different outcomes? Can we ever actually objectively put a dollar value on these wildly different outcomes?
While I don’t have all the answers to these questions (arguably it’s impossible for anyone to have all these answers as they obviously vary from person to person), next time you see a transport cost-benefit analysis have a think about the different components of the project’s benefits and how these might have been quantified, or the impacts that might not have been quantified. As we learned through the Regional Land Transport Plan, ultimately you simply can’t delegate transport decision-making to a computer.