Knocking on Heaven's Door - Lisa Randall [93]
Regulators attended to conventional safety issues (to some extent) concerning the soundness of individual institutions, but they didn’t assess the system as a whole, or the interconnected risks built into it. More complex systems with overlapping debts and obligations call for a better understanding of these interconnections and a more comprehensive way of evaluating, comparing, and deciding risks and the tradeoffs for possible benefits.42 This challenge applies to most any large system—as does the time frame that is deemed relevant.
This brings us to a further factor that makes calculating and dealing with risk difficult: our psyches and our market and political systems apply different logic to long-term risks and short-term ones—sometimes sensibly, but often greedily, so. Most economists and some in the financial markets understood that market bubbles don’t continue indefinitely. The risk wasn’t that the bubble would burst—did anyone really think that housing prices would continue doubling within short time frames forever?—but that the bubble would burst in the imminent future. Riding or inflating a bubble, even one that you know is unsustainable, isn’t necessarily shortsighted if you are prepared at any point to take your profits (or bonuses) and close up shop.
In the case of climate change, we don’t actually know how to assign a number to the melting of the Greenland ice cap. The probabilities are even less certain if we ask for the likelihood that it will begin to melt within a definite time frame—say in the next hundred years. But not knowing the numbers is no reason to bury our head in the ice—or the proto-cold water.
We have trouble finding consensus on the risks from climate change and how and when to avert them when the possible environmental consequences arise relatively slowly. And we don’t know how to estimate the cost of action or inaction. Were there to be a dramatic climate-driven event, we would be much more likely to take action immediately. Of course, no matter how fast we were, at that point it would be too late. This means that non-cataclysmic climate changes are worth attending to as well.
Even when we do know the likelihood of certain outcomes, we tend to apply different standards to low-probability events with catastrophic outcomes than to high-probability events with less dramatic results. We hear a lot more about airplane crashes and terrorist attacks than we do about car accidents, even though car accidents kill far more people every year. People talked about black holes even without understanding probabilities because the consequences of the disaster scenario seemed so dire. On the other hand, many small (and not so small) probabilities are neglected altogether when their low visibility keeps them under the radar. Even offshore drilling was considered completely safe by many until the Gulf of Mexico disaster actually occurred.43
A related problem is that sometimes the greatest benefits or costs arise from the tails of distributions—the events that are the least likely and that we know least well.44 Ideally, we‘d like our calculations to be objectively determined by midrange estimates or averages of preexisting related situations. But we don’t have these data if nothing similar ever occurred or if we ignore the possibility altogether. If the costs or benefits are sufficiently high at these tail ends, they dominate the predictions—assuming that you know in advance what they are in the first place. In any case, traditional statistical methods don’t apply when the rates are too low for averages to be meaningful.
The financial crisis happened because of events that were outside the range of what the experts had taken into account. Lots of people made money based on the predictable