Wednesday, June 2, 2010

Eco-nomics: Incentives, Innovation and Catastrophe

Ken Rogoff, Harvard professor and former chief economist at the IMF, has an excellent piece in Project Syndicate on the problem of regulating complex new technologies. This was true in the case of exotic financial instruments that caused the financial crisis and is now true in the case of deep water drilling. Here is Rogoff on the Gulf of Mexico disaster:

The disaster, however, poses a much deeper challenge to how modern societies deal with regulating complex technologies. The accelerating speed of innovation seems to be outstripping government regulators’ capacity to deal with risks, much less anticipate them.

The parallels between the oil spill and the recent financial crisis are all too painful: the promise of innovation, unfathomable complexity, and lack of transparency (scientists estimate that we know only a very small fraction of what goes on at the oceans’ depths.) Wealthy and politically powerful lobbies put enormous pressure on even the most robust governance structures. It is a huge embarrassment for US President Barack Obama that he proposed – admittedly under pressure from the Republican opposition – to expand offshore oil drilling greatly just before the BP catastrophe struck.

The oil technology story, like the one for exotic financial instruments, was very compelling and seductive. Oil executives bragged that they could drill a couple of kilometers down, then a kilometer across, and hit their target within a few meters. Suddenly, instead of a world of “peak oil” with ever-depleting resources, technology offered the promise of extending supplies for another generation.


The basic problem of complexity, technology, and regulation extends to many other areas of modern life. Nanotechnology and innovation in developing artificial organisms offer a huge potential boon to mankind, promising development of new materials, medicines, and treatment techniques. Yet, with all of these exciting technologies, it is extremely difficult to strike a balance between managing “tail risk” – a very small risk of a very large disaster – and supporting innovation.


If ever there were a wake-up call for Western society to rethink its dependence on ever-accelerating technological innovation for ever-expanding fuel consumption, surely the BP oil spill should be it. Even China, with its “boom now, deal with the environment later” strategy should be taking a hard look at the Gulf of Mexico.

Economics teaches us that when there is huge uncertainty about catastrophic risks, it is dangerous to rely too much on the price mechanism to get incentives right. Unfortunately, economists know much less about how to adapt regulation over time to complex systems with constantly evolving risks, much less how to design regulatory resilient institutions. Until these problems are better understood, we may be doomed to a world of regulation that perpetually overshoots or undershoots its goals.

The finance industry already is warning that new regulation may overshoot – that is, have the unintended effect of sharply impeding growth. Now, we may soon face the same concerns over energy policy, and not just for oil.

Given the huge financial stakes involved, achieving global consensus will be difficult, as the Copenhagen climate-change fiasco proved. The advanced countries, which can best afford to restrain long-term growth, must lead by example. The balance of technology, complexity, and regulation is without doubt one of the greatest challenges that the world must face in twenty-first century. We can ill afford to keep getting it wrong.

I would add only that the political economy of regulating against activities with uncertain risks but with fairly demonstrable gains is hugely difficult. But it seems to me that the scale of disaster whether it is the almost comical inability to stop a massive man-made fissure in the earth crust from gushing toxic oil or the potentially devastating effects of global climate change suggests we need to change our calculus. In our risk models the worst-case scenarios are turing out to be orders of magnitude worse than we thought and so our probabilistic models of expected benefit and expected cost need to be fairly radically adjusted.

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