Latest / Monetary Policy Explained with Fexingo: Central Banks, Money Supply, and Interest Rates / Why Central Banks Care About Climate Stress Tests
Transcript
- Lucas: So, the Federal Reserve ran its first ever climate stress test in 2023, and the results were quietly fascinating. They took six of the largest U.S. banks and ran them through two scenarios — a severe hurricane hitting the Northeast and a sudden drop in global demand for fossil fuels. Luna: I remember that. It felt like the Fed was finally catching up to what the Bank of England had been doing for years. But why would a central bank care about climate scenarios in the first place? Isn't that more of an environmental agency's job? Lucas: That's the natural question. And the answer comes down to their mandate, which is financial stability. If a severe weather event or a disorderly transition to a low-carbon economy can knock out a big chunk of the banking system, that's a monetary policy problem. It affects lending, credit conditions, and eventually the real economy. Luna: So it's like a stress test for the environment hitting the banking sector. I get that. But how do they even simulate something like a hurricane or a carbon tax? It's not like a typical recession scenario. Lucas: Right, it's messy. And honestly, this is where the episode gets interesting. Let's look at the Bank of England's 2021 exercise, which was the first big one. They designed three scenarios: one where the world acts early and smoothly, one where action is delayed, and one with no action — what they called 'no additional action.' Each scenario had a bunch of assumptions about carbon prices, energy efficiency, and land use. Luna: And what did they find? Did the banks pass? Lucas: Well, they didn't pass or fail. That's a key point. These aren't pass-fail exams. The Bank of England was clear that it was a learning exercise. They published the results, but there was no capital requirement tied to it. The goal was to get banks to think about the risks and to give the central bank a sense of the range of exposures across the system. Luna: So it's more like a diagnostic, not a test. That makes sense. But then what did the Fed's pilot do differently? Lucas: The Fed's approach was slightly more targeted. They focused on the six largest banks and used two scenarios — a hurricane that hits the Northeast and a transition scenario where there's a sudden drop in global demand for fossil fuels. They looked at the direct impact on loan portfolios — mortgages, commercial real estate, corporate loans — and also the indirect effects through things like higher energy costs or lower property values. Luna: And did they find anything surprising? I mean, aside from the obvious that a hurricane is bad for mortgages. Lucas: One of the more interesting findings was that the losses were not huge in aggregate — they estimated a combined loss of around one point two trillion dollars in the hurricane scenario, but that was spread over a decade and across the whole system. The point wasn't the total; it was the concentration. Some banks had outsized exposure to coastal real estate or to high-carbon industries. That kind of concentration is what keeps supervisors up at night. Luna: Exactly. It's not that the whole system blows up from a single storm. It's that a few banks could be really hurt, and that could ripple through the payment system or the interbank market. That's the systemic risk angle. Lucas: And that's where the ECB's exercise took it a step further. In 2022, they ran a whole-economy stress test, not just for banks but for the entire financial system. They modeled the impact of a carbon tax and a green investment push, and they looked at how different sectors would be affected — energy, transport, manufacturing. They found that the transition scenario could actually boost GDP over the long run, but in the short run, some sectors would face significant losses. Luna: So it's a bit of a double-edged sword. Good for the economy in the long term, but painful for specific industries and the banks that lend to them right now. That must create some interesting tension for the central bank, because they're supposed to be neutral. Lucas: And that's the heart of the debate. On one side, you have people saying central banks shouldn't be picking winners and losers — that by modeling these scenarios, they're essentially deciding which industries should survive. On the other side, the argument is that ignoring climate risk is itself a decision — it's a decision to be blind to a real threat to price stability and financial stability. Luna: And when you put it like that, it feels like the 'do nothing' option is a bit naive. But let's talk about the actual mechanics. How do you even start modeling something like a carbon tax? I imagine it involves a lot of assumptions. Lucas: It's a massive exercise in assumptions. For the ECB's test, they used something called a 'dynamic stochastic general equilibrium' model — you're right, it's a mouthful — but essentially they plug in a carbon price trajectory and watch how firms and households change their behavior. The tricky part is calibrating the pass-through to energy prices, which depends on a whole range of factors like energy intensity, trade exposure, and the elasticity of demand. Luna: So there's a lot of uncertainty in these models. I mean, we're talking about 30-year time horizons, and nobody really knows what a carbon price will be in 2050. So how much stock should we put in these results? Lucas: That's the million-dollar question. The central banks themselves are careful to say these are not predictions. They're more like 'if-then' exercises. The Bank of England called it 'exploring the implications of different pathways.' But critics argue that the assumptions are so broad that they could be manipulated to get any result you want. There's a real risk that these tests become more about scoring political points than about risk management. Luna: And that's a fair criticism. But I see a lot of value in just getting the conversations started. If a bank has to sit down and think about its exposure to a flood zone or a coal mine, that's a good exercise in itself, even if the model is rough. Lucas: And that's exactly what the Fed's pilot was trying to do. They were very explicit that the results wouldn't be used for capital requirements — this was about building capacity. The next step, and this is a big deal, is that the Fed is now considering whether to incorporate climate risk into its regular supervisory exams. That would be a real shift. Luna: So we might see climate risk become a standard part of the annual stress test, alongside the more traditional recession and unemployment scenarios. That feels like a natural evolution, but it's also a big change for banks that have to prepare for it. Lucas: And the banks are already preparing. Some of the largest U.S. banks have hired climate risk officers and are developing their own internal models. They know it's coming. The question is how quickly and how strictly the regulators will apply it. Luna: Before we get too deep into the future, let's go back to the actual numbers for a second. In that Fed pilot, the hurricane scenario — how did they define the 'severe' hurricane? I'm curious about the level of detail. Lucas: They modeled a Category 4 storm hitting the Northeast, with wind speeds of about 130 miles per hour, and a storm surge that would flood parts of Manhattan and Long Island. They also assumed a secondary shock — a rise in insurance costs, which would affect home values and mortgage defaults. The banks had to estimate losses on their residential and commercial real estate portfolios, as well as on corporate loans to companies in the affected region. Luna: That's incredibly specific. And I bet the results varied a lot depending on the bank's portfolio mix. A bank with a big coastal mortgage book would obviously be hit harder than one with a more diversified loan book. Lucas: Exactly. And that's the whole point of the exercise — to identify those vulnerabilities. The Fed didn't publish the bank-by-bank results, but they said that the losses were 'moderate' in the aggregate — a few percent of tier-one capital for the most exposed banks. But again, the point wasn't the number itself; it was the variation. Luna: So we're seeing a shift from 'we don't have a good enough model' to 'let's use the best model we have and improve it over time.' That's a pragmatic approach. Lucas: And it's not just the big central banks. The Bank for International Settlements, or the b i s, has been pushing for climate scenario analysis across its member central banks. They've published a framework that many smaller countries are adopting. So this is becoming a global standard, not just a few rich-country initiatives. Luna: That's an interesting point. If you're a small island nation, climate risk is existential, not just a financial stability issue. So it makes sense that the b i s would want to harmonize the approach. Lucas: And that's why we're seeing central banks in places like Fiji, the Philippines, and even Paraguay starting to run their own exercises. They're not just copying the Fed or the ECB — they're adapting the scenarios to their specific risks, like cyclones, sea-level rise, or drought. Luna: So what's the biggest challenge you see in making these climate stress tests truly effective? Is it the data, the modeling, or something else? Lucas: I think the biggest challenge is the feedback loop. In a traditional stress test, you assume the shock happens and the banks react. But with climate, the shock is not just external — the banks' own actions can affect the severity. If a bank cuts off lending to a high-carbon industry, that might accelerate the transition and reduce transition risk. But it could also trigger a disorderly collapse of that industry, which creates new risks. Capturing that two-way interaction is really hard. Luna: So it's a dynamic system, not a static shock. That's a lot harder to model. And it also requires central banks to coordinate with fiscal policy and other regulators, which is never easy. Lucas: Right. And that's why some critics say these stress tests are more about signaling than about actual risk management. But I'd argue that signaling is itself a tool. If the Fed's pilot sends a message to banks that climate risk is a supervisory priority, that changes behavior long before any capital requirement is set. Luna: That's a good point. It's like the old adage that the existence of a stress test makes the system safer because banks know it's coming and they prepare for it. Even if the test itself is imperfect. Lucas: Exactly. And that's really the bottom line. We're not at the point where climate stress tests will determine a bank's capital ratio tomorrow. But we are at the point where they're becoming a standard part of the supervisory toolkit. And that's a big deal. Luna: So for our listeners who might be at a bank or investing in financials, what should they watch for in the next few years? Lucas: I'd watch for two things. First, whether the Fed decides to incorporate climate risk into its regular stress tests — that's a likely next step, and it would have a direct impact on bank capital planning. Second, how the rest of the world, especially emerging markets, adopt these frameworks. If you're a global bank, you'll need to run these exercises across multiple jurisdictions, and that's a significant operational challenge. Luna: It's definitely a space to keep an eye on. And on that note, I think we've covered a lot of ground today. Thanks for breaking it down, Lucas. Lucas: Thanks, Luna. And thanks to everyone listening. If this episode made you think about central banks in a new light, you might enjoy supporting the show. We keep it ad-free, and listener support is what keeps it that way. If you're able, you can buy us a coffee at buy me a coffee dot com slash fexingo. It's a simple way to say thanks and help us keep making these deep dives. Now, next time we'll look at how central banks are thinking about the rise of digital currencies in emerging markets.