In my last post I wrote about the hazards of projecting costs and benefits of large scale infrastructure projects. Here I want to write about some academic research on the topic. It turns out that there is a pattern of underestimating costs, and overstating benefits.
Bent Flyvbjerg (Professor of Economic Geography at Oxford University) is a leading researcher in the area of planning for large scale infrastructure projects. With his colleagues, he assembled a big database of large scale transportation projects. He finds 90% of projects went way over budget (ie underestimated costs), and a similar % significantly over-predicted demand (mainly traffic flow). These systematic biases have persisted for decades, and it appears that the lessons are not being learned: the biases are still there in more recent projects.
So why do so-called experts consistently overestimate benefits and underestimate costs?
Flyvbjerg suggests 3 possible reasons:
1. Technical forecasting errors - experts use complex models to try and project into the future, and with much uncertainty, there is always going to be some error. Unforeseen circumstances always arise.
2. Optimism bias - psychologists argue that often in situations of uncertainty, planners and politicians err on the optimistic side, understating costs and overstating benefits.
3. Political incentives - often those who are developing the plans and proposals have an interest in seeing the project supported and receive funding. Consultants earn future work, politicians get a legacy, public servants get achievements next to their resumes. This gives all an incentive to exaggerate their project's benefits and understate costs.
Looking at the evidence, there are certainly cases where all three possible explanations apply, but the third seems to be most prominent. The first two reasons are possible in particular cases, but implausible across so many projects over a long period of time. Why would experts consistently get it wrong? If planning was a purely technical exercise, surely they would learn from previous mistakes and over time, forecasts would improve. Systematically biased forecasts, with no sign of learning from this, are unlikely.
How does political incentives thwart the objective nature of these cost-benefit analyses? In many ways, but imagine a scenario like this: Development Advisers encourage the government to modernise their infrastructure, especially those that provide the public face of the country, like the main international airport. Government leaders are persuaded by the arguments, but due diligence requires employing an international consultant to undertake a feasibility study. The consultant knows the mood of the government is favourable to the project, so makes assumptions which err on the side of delivering the message they know the client wants to hear - that way their report will get a much easier run, and a favourable report may well lead to more work in future!
Acknowledging the inherently political nature of cost-benefit analyses in large scale projects, what can be done to avoid these problems? There are many suggestions in the literature.
Here are a few that stand out to me, as being relevant to Timor-Leste:
* Transparency: providing as much information as possible to the public about the rationale, the models and assumptions, etc, and allowing these to be challenged. No outside consultant knows the specific situation in Timor-Leste as well as the collective voice of the people.
* Peer review: don't just listen to one consultant or adviser's advice: get other experts (independent) to review an analysis or recommendation.
* Ask for a 'reality check' on projected costs and benefits by examples of similar completed projects in other countries, where actual costs and benefits are documented (this is a simplified version of Reference-class forecasting).
* Design Public-Private Partnerships to ensure significant risk lies with the private partners. There is much more to say about this PPP topic, for another time, but the key point here is that partnerships with shared risk can be a good way to ensure the projections are realistic. Private investors who are putting their own money at risk tend to be much more careful with questioning and challenging the forecasts, because their profit is at stake if the numbers are wrong!
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