气候冲击:经济学与科学之间的鸿沟
2021年是自然灾害频发的一年。那一年,巴基斯坦的洪水夺走了1700人的生命,欧洲则开始了500年来最严重的干旱。
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2021 was a bad year for natural disasters. That was the year that floods killed 1,700 people in Pakistan and Europe began what would be the worst drought in 500 years.
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And that was the year one of my clients turned to me and said, "Is it really worth solving climate change?"
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Well, look, he was an investor. What he wanted to understand was the economic return on the trillions of dollars we have to spend to get to net zero.
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So that's a good question, right? And there's a good answer. But I also found a problem.
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You see, there's a huge gap between the science and the economics.
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The science is scary, and it’s really detailed.
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The science tells us that we're leaving 12,000 years of climate stability behind us.
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Those floods and those droughts are going to get more frequent and more intense.
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Crops may fail. Fisheries collapse.
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But then when you turn to the economics, all that turbulence and that kind of disruption just seems to get lost in translation.
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You find yourself looking at graphs with suspiciously smooth curves: rising temperatures, steadily declining growth.
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Now those graphs do tell us something really important.
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There really is a connection between global warming and our ability to build things and make things and just get things done, and the damages from that get really big, really quickly.
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But when I turned that analysis into my first quadrillion-dollar slide for my client, it left him cold.
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You see, the problem with the economics is that it's robust, but it doesn't actually do a very good job of explaining how, in practice, climate change will impact businesses and households in the real economy.
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And that's why all that turbulence and disruption you expect to see, that you actually need to see if you want to prepare, seems to disappear.
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So that's what I want to talk to you all about today.
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Imagine we had as good an understanding of the impact of climate change on the economy as we have of climate change itself. Just as convincing and just as useful.
超越直接损失:追踪金融涟漪效应
让我们从自然灾害开始。大型保险公司估计,自然灾害每年造成约2000亿至3000亿美元的直接损失。
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So let's start with natural disasters. The big insurers estimate that natural disasters cause about 200 to 300 billion dollar's worth of damages, direct damages, every year.
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And these numbers are certainly more tangible. You know, you can see the collapsed bridges and the flooded mines in the data.
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But they're also incomplete.
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Where are the lost revenues for the factories that relied on that mine, or the lost income for the workers that needed that bridge to get to work?
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In fact, if we compare those numbers with that quadrillion-dollar slide, we can see we're missing about 80 percent of the problem.
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So this is what we need to do. We need to take a bit of a step back and then we need to focus on the commercial relationships, the financial mechanisms that actually link companies together and transmit climate impacts around the economy.
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So now, instead of chasing hurricanes as they rampage through the physical infrastructure, we're going to trace them as they reverberate through the financial infrastructure.
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And I know chasing hurricanes sounds more fun, but honestly, this is when you're going to start seeing some of that turbulence and that disruption that we're looking for.
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So take the American southeast. We all know that hurricanes regularly cause billions of dollars of damage along the coast.
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But it doesn't stop there or then.
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Insurance premiums are rising as a result across the region.
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And many households, particularly those on low income, many of whom are actually inland, can't keep up.
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So now we see rising mortgage defaults and credit card delinquency.
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And this is causing problems for another set of financial institutions.
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Or take the coffee industry. In 2021, again, it was a bad year.
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A major frost and drought caused coffee production in Brazil to fall by 20 percent.
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But prices went up 30 percent globally, in just one week. And then they kept on rising.
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Why? Why this kind of overreaction?
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Well it started when many farmers walked away from their forward contracts.
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And forward contracts are actually there to provide price stability between coffee farmers, coffee buyers.
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But when some farmers saw higher profits available on the open market, they left their buyers in the lurch.
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And so now the buyers can't meet their own onward commitments into the futures market.
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So they're scrambling to find cash to keep those positions open. They're scrambling to find new coffee supplies to meet them.
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And it's driving the price up higher and higher.
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So these are just two disparate examples of how climate change causes turbulence in our financial infrastructure.
金融基础设施的临界点与崩溃风险
真正令人担忧的是,金融基础设施本身可能会在日益增长的压力下崩溃。
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But the real worry is that the financial infrastructure itself will break under rising pressure.
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Because we're going to see more extreme weather in the next 10 years than we saw in the last 10 years.
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Those shocks are going to grow, and the gaps between them are going to shrink.
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And we can already see some of the warning signs.
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Now in Florida, several insurers have now gone bankrupt or they've pulled out.
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And now the state is the single largest provider of home insurance in Florida, putting pressure on its budget.
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In California, climate risks are driving up the cost of borrowing for many of the local authorities that actually need to invest in preventing those risks.
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So we may be heading towards a tipping point, at which point the financial infrastructure can't manage climate risk anymore.
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And this isn't academic, because if we can't manage climate risk, we can't do a lot of things.
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Imagine trying to get a mortgage on a house that you can't insure. You can't.
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Or sell one that's become uninsurable, for that matter.
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You know, at scale, this is major disruption.
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And this isn't the normal, you know, boom and bust cycle. This is just bust, bust, broken.
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So ... This may all sound a bit melodramatic to some of you. You know, that extreme. And that's fair enough.
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There's a very real debate right now between a growing set of voices that are worrying about these kinds of tipping points and those that say, don't worry, the financial system as a whole will be able to manage climate risk for many decades to come.
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But I think for our purposes, in a way it doesn't matter, because there's huge benefit in being able to better anticipate the turbulence ahead, either way.
复杂性经济学与模拟:预测未来的新工具
我认为,更好地预测未来的第一步是认识到我们传统上依赖的许多工具和技术并没有足够的想象力来做到这一点。
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And I think the first step in being able to better anticipate the future is recognizing that many of the kind of tools and techniques that we've traditionally relied on don't really have the imagination to do so.
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You know, they're really rooted in the status quo, historical data, past trends.
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So what we need to do is look to other complex dynamic systems and the way those are studied, like evolutionary biology or thermodynamics.
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Ironically, environmental science, energy networks.
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And the field of complexity economics does exactly this, right?
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It borrows tools and techniques from those other areas of study and uses them to better anticipate how shocks and trends can reshape economies.
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Of course, climate change is both of those things, right? Because you've got falling productivity, rising risk, punctuated by natural disasters.
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And one of the key tools that many of these fields use are simulations.
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And in this context, you should be thinking of them as digital twins of whatever system it is that you're studying.
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They're populated with thousands of virtual actors, each with their own rules of behavior and, critically, the connections between them.
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You set them up, and you let them run.
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You can test them against reality and calibrate them.
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And then you can run experiments.
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What would happen if we had a different setup? What will happen in future?
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So urban planners use simulations to prove that sometimes demolishing a major road can actually ease traffic congestion.
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Ecologists use simulations to show why fish stocks can collapse even after you've put fish quotas in place.
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The important thing about both of those results is that they're unexpected. They're not intuitive.
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And this is what we need, where global warming meets the global economy.
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From our systems thinkers, from our risk modelers, from our data scientists.
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We need models that surprise us before the future does.
构建韧性:应对未来挑战的双重投资案例
因为一旦我们做到了这一点,我们就可以做很多事情来更好地管理未来的破坏。
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Because once we've done that, there's a whole bunch of things that we can do to better manage the disruption ahead.
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I'll give you one quick example.
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Imagine insurance that just pays out to farmers as soon as they're hit by a natural disaster.
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They're back on their feet, minimal impact on their customers.
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Well this product exists, it's called parametric insurance.
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But the challenge is scaling it up because you've got to find terms that are going to work for thousands, tens of thousands of farmers, year after year, shock after shock.
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OK, but now imagine you've got a simulation of, say, the coffee industry, and you can test those terms against the shocks of the past and about potential futures.
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And that's just one of several innovations that could make the financial infrastructure of the coffee industry more resilient.
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And we need exactly that kind of innovation across the real economy.
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With the right tools, what felt like an impenetrable fog of uncertainty, starts to feel like a landscape ripe for opportunity.
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So what would I say to my client today?
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Well, firstly, the economic case for climate action is clear.
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We're talking about safeguarding maybe 25 percent of global GDP between now and 2100.
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But there's a second investment case. In building resilience to the financial turbulence that we're going to experience on the way.
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Because climate change is now inevitable, at least for the next 75 years.
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But the scale of the economic disruption is not.
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And what we build together, the models, the new products, the collaborations, will determine how much we spend clearing up the mess as we go and how much we can invest in actually solving the problem.
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Thank you so much for your time.
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(Applause)