Climate Change Will Cost Us Even More Than We ThinkRoundup
tags: economic history, history of science, climate change, global warming
Dr. Oreskes is a professor of the history of science at Harvard. Professor Stern is chair of the Grantham Research Institute on Climate Change and the Environment.
For some time now it has been clear that the effects of climate change are appearing faster than scientists anticipated. Now it turns out that there is another form of underestimation as bad or worse than the scientific one: the underestimating by economists of the costs.
The result of this failure by economists is that world leaders understand neither the magnitude of the risks to lives and livelihoods, nor the urgency of action. How and why this has occurred is explained in a recent report by scientists and economists at the London School of Economics and Political Science, the Potsdam Institute for Climate Impact Research and the Earth Institute at Columbia University.
One reason is obvious: Since climate scientists have been underestimating the rate of climate change and the severity of its effects, then economists will necessarily underestimate their costs.
But it’s worse than that. A set of assumptions and practices in economics has led economists both to underestimate the economic impact of many climate risks and to miss some of them entirely. That is a problem because, as the report notes, these “missing risks” could have “drastic and potentially catastrophic impacts on citizens, communities and companies.”
One problem involves the nature of risk in a climate-altered world. Right now, carbon dioxide is at its highest concentration in the atmosphere in three million years (and still climbing). The last time levels were this high, the world was about five degrees Fahrenheit warmer and sea level 32 to 65 feet higher. Humans have no experience weathering sustained conditions of this type.
Typically, our estimates of the value or cost of something, whether it is a pair of shoes, a loaf of bread or the impact of a hurricane, are based on experience. Statisticians call this “stationarity.” But when conditions change so much that experience is no longer a reliable guide to the future — when stationarity no longer applies — then estimates become more and more uncertain.
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