Confront the Climate-Change Emergency Rationally

This is an edited excerpt of the conversation held October 27, 2021, at a Future of Capitalism event sponsored by Chicago Booth and Booth’s Rustandy Center for Social Sector Innovation. Impact investment pioneer Ronald Cohen, Imperial College London’s Mili Fomicov, and University of Chicago’s Lars Peter Hansen, a Nobel laureate as well as a Booth professor, discussed how to confront the effects of climate change on economies around the world. Booth’s Randall S. Kroszner moderated.

Randall S. Kroszner: There’s an enormous amount of uncertainty when it comes to climate models. We can try to estimate it as well as we can, but in making policy and practical decisions on investment, we need to be aware of what we know and what we don’t know. Lars, what are some of the key issues that you see in climate economics that pose these uncertainty challenges? Where are the key issues of uncertainty in climate economics?

Lars Peter Hansen: I’m all in that climate change is important and challenging. My research has to do with trying to figure out how to confront uncertainty in sensible ways. A starting point is the fact that policy makers tend to want to project conclusions with great confidence, and scientific evidence doesn’t always bear that out. How do we stay true to the scientific evidence and still come up with sensible policies? Economics has had a lot to say about that.

A concern of policy makers is that once you announce, “Well, we don’t really fully understand things,” there will be arguments that we don’t do anything now and wait. But in the case of climate change, delaying can make the problem bigger and costlier. It may be better to adjust now, even in the presence of uncertainty. That’s the type of trade-off that I’m trying to wrestle with.

Of the uncertainties that show up in our work, one is that we’re interested in emissions and how they translate into environmental changes like temperature changes. As you try to trace through the impact of emissions on temperature over 10, 20, and up to 100 years, there’s substantial uncertainty. Now factor in conjectures that once you cross certain thresholds of temperature or other environmental indicators, there will be more dramatic consequences for the climate and the overall environment. Those type of threshold effects are possibilities, but they are challenging to quantify meaningfully.

The other piece is economic damages. Once we do damage to the environment, what are the economic consequences of that? Because people will adapt, and there will be modifications, how do we really measure those potential damages? As scholars, we love evidence, but we’re talking about moving world economies to places they haven’t experienced historically. We have to think about it conceptually and make smart guesses about the nature of the uncertainties. These components of uncertainties interact, and it’s important to think about them simultaneously rather than distinctly.

Kroszner: How do you use the framework of decision-making uncertainty to think about these kinds of trade-offs?

Hansen: Imagine you’ve got a world in which we’re not sure about the extent of damages, but once we start damaging the economy, it might become more evident. It’s a trade-off. We could wait until we learn about that damage curvature, but there may be very, very steep consequences—or maybe the consequences will not be as dramatic as we feared.

To confront these types of trade-offs, we perform policy-relevant calculations, like computing the so-called social cost of carbon. From an asset pricing perspective, a social cost of carbon is just like an asset that you value with a dividend stream. Emissions go into the atmosphere, and they have social consequences tomorrow, the next day, and way off in the future. How do we produce meaningful measures of factors such as the social cost of carbon, and then figure out what sensible emissions policies might progress from that?

In response to these trade-offs, it makes sense to be initially cautious, and down the road you learn more. At that point in time, you will continue with caution, or you might decide to be bolder. Those are the types of trade-offs we’re trying to confront.

What’s really important is the fact that you think about these outside the usual risk frameworks that we’re often taught in economics classes. Traditional risk analysis applies to situations in which we know probabilities but not outcomes—coin flips, rolls of the dice, and the like. If only uncertainties were that simple. So the first question has to do with, what’s the right model, the right view of the world?

And then, in the models we use, our view of the world is simplified. The world is complex, and how do we use models that take those simplified lenses and use them in sensible ways? It’s important to conceptualize the uncertainties in this more general framework.

Kroszner: What are some of your findings of how you deal with this uncertainty?

Hansen: I saw the use of models play out in real time over the pandemic, although of course the pandemic’s modeling and implications played out on a much faster time scale than climate change. You saw these model predictions reported that were distinct in important ways. Sometimes the predictions were best guesses, and other times they conveyed adverse things that could happen. And sometimes when people use models, they’re not clear about how they’re using them. Key here is the trade-off between your best guesses of the future versus your concerns about what bad might happen going forward. Decision theory offers nice conceptualizations for this.

Now, as an economist, I can’t tell policy makers how averse they ought to be to these bad outcomes. But how averse society should be to uncertainty or how averse businesses should be to uncertainty has to do with preferences.

Kroszner: We have elected officials in some sense to make these social-choice trade-offs. How do you help the policy maker to think through these issues? We have a certain amount of risk aversion, but how do we turn that into policy choices?

Hansen: We use models to report which components of uncertainty should be of the most concern for alternative specifications of uncertainty aversion and what the prudent course of action should be. It is a highly structured sensitivity analysis. By inspecting our modeling outputs in this way, policy advisors can ask what magnitude of uncertainty aversion is reasonable.

Kroszner: Whether it’s the time-scale issues, or broader risk issues of interactions between climate and financial risk, do you have a thought on what you would focus on? What are the issues that you tell the policy makers to focus on?

Hansen: We focus much more on the fundamental uncertainties that are out there, and all the ways for potential new technologies to help us out. I think about this in the context of central-bank policy too, since central banks are also concerned about issues on climate change. But one of the things that firms have to face is policy uncertainty. When it comes to climate change, things like weather patterns are important, but in the private sector, they’re also having to speculate what policy changes will be coming down the road. Sometimes I think central banks are stuck in this position, worried about the types of uncertainties that are potentially induced elsewhere by governmental activities. Both these transitional issues as well as policy uncertainty are important to both private-sector and central-bank policy.

Kroszner: What would you say is your bottom line? If you were advising a policy maker on how to allocate a large sum of money related to the climate, where would you focus it?

Hansen: Two places come to mind, and right now we’re trying to figure out the trade-offs between such alternative policies.

One is how much social investment we want to make in developing new green technologies. Governments can take resources allocated for this purpose and start reshifting in an unproductive direction, so as we think about allocating resources toward developing new green technologies, we also have to do this in a way in which we have sensible decision makers making the call on the productive types of investments to be made there.

Second, making policies that change people’s incentives, like taxation policies connected to carbon emissions, can be important. Big political issues show up, and you have to think hard about what you’re going to do with the revenues and the distributional consequences. The policy challenge doesn’t end with merely introducing carbon taxes. Those are the two types of activities that I find potentially most useful.

Kroszner: Mili, you’ve done a lot of work on thinking about the allocation of capital and what the implications of all of this uncertainty are for strategic capital allocation. If you were to allocate $1 billion a year related to the climate, what framework would you use?

Mili Fomicov: As an investor, you need to think about certain implications on macroeconomic variables such as GDP, interest rates, and inflation, but it will be path dependent. A temperature change of 2 degrees could lead to radically different growth or decline rates. Some institutions are forecasting, for example, that Canada will be a net beneficiary, while some are showing that it will see a 3–4 percent GDP decline. Also, carbon pricing can have inflationary or deflationary effects, depending on different responses.

The capital-market assumptions that most investors use when they think about their strategic allocation rely on a single scenario. A lot of practitioners are trying to model the climate risks and opportunities by simply adjusting returns and volatility expectations by stressing certain macro variables. That can go really wrong.

Climate financial scenarios must combine transition scenarios and financial risk models. Then investors can choose between different scenarios and select pathways that meet their own implementation capabilities. We provide training to investment managers and frequently talk about Lars’s work and the need to formalize that uncertainty and to be more comprehensive.

Finally, diversification becomes even more important. Investors can expand their tool kits and invest in new asset classes that are part of the solution. For example, given that there’s a lot of uncertainty around carbon pricing, you can own carbon allowances and then potentially mitigate some of the losses. You can also invest in adaptation and mitigation, nature-based solutions, renewable infrastructure in emerging markets, and asset classes that were not investible before. This way you’re really investing in climate solutions, turning some risks into opportunities, and diversifying in this radically uncertain world.

Kroszner: We can’t translate the framework that Lars and Mili were talking about into something practical without data. Sir Ronald, how have you approached the issue of getting data about impact?

Sir Ronald: Impact measurement is the lever to shift our economies from risk-return to risk-return-impact, and it is one of three major forces driving this shift. The first force is a massive change of values. Young people refuse to purchase the products of “bad” companies and refuse to work for them. This hasn’t been lost on investors, who now channel $40 trillion-plus of ESG [environmental, social, and governance] investment to achieve impact as well as profit. This is half of all assets in asset management firms.

The second force is leaps in technology. Artificial intelligence, machine learning, augmented reality, blockchain, and the coming together of the human genome are enabling us to deliver impact globally in ways humanity could never previously contemplate.

And the third major force is impact transparency. Huge computing power and the availability of big data enable us to measure in a granular way the impacts companies create on climate, the planet, and people.

It occurred to me a few years ago that if we don’t have reliable data that businesses and investors can use in their decision-making, we are not going to achieve the goal of shifting our economies to risk-return-impact. I helped establish the Impact Weighted Accounts Initiative (IWAI) at Harvard Business School. The IWAI has published, in monetary terms, the environmental impacts of 3,000 public companies across the world. It has used available metrics, and defined paths to value them.

Out of these 3,000 companies, 450 deliver more environmental damage in a year than they do profit. A thousand deliver environmental damage equivalent to a quarter or more of their profits. Together they deliver $4 trillion worth of environmental damage in a single year. And most interestingly, within many sectors, you now see a correlation between higher pollution and lower stock market valuation. The weight of ESG money is tilting the value of companies.

The crucial step now is for governments to mandate impact transparency through generally accepted impact principles, paralleling what the Roosevelt administration did in 1933 and ’34, when investors had little transparency on profit because there were no accepted accounting principles. We are at a similar crossroads today.

Kroszner: Lars, you’ve thought about this issue of trying to encompass the externalities. How do you see what Sir Ronald just spoke about in terms of a way to be helpful in trying to address some of the issues that you have raised?

Hansen: The work that I’ve been doing has been focused more on the so-called social cost of carbon. It used to be that, before Donald Trump became president, the EPA [US Environmental Protection Agency] would post numbers about the social cost of carbon to be used in policy making. During the Trump administration, these numbers got pulled down, and now they’re being put back up again. It’s pretty frustrating to see how they were produced—and in many cases, they were kind of rushed out. Most of those measurements treated uncertainty in casual and sloppy ways.

Going from data to useful quantifications is an important task, and we’ve got a ways to go. I get nervous when I see numbers posted that are just not well thought out. So I hope that, going forward, we can put a lot more effort into thinking through how to do this in open and appealing ways. I’m all in favor of getting better and richer data. And I think it’s important that we open the hood on how these social metrics are constructed.

This has spun all the way over into central-bank policy. They’re putting out these deterministic, statically specified climate scenarios and asking financial institutions to do something with them. As Mili indicated, it’s really important to take those static notion scenarios and make them dynamic and in some sense probabilistic.

Kroszner: How were the markets pricing in the different climate scenarios, and how are they taking into account these externalities now, if they are?

Fomicov: The market already started to reprice quite substantially. The International Energy Agency (IEA) and I are working on four reports looking at the power sector and how it is repricing based on certain climate and macroeconomic variables. Renewables have significantly outperformed fossil fuels in the past five years, and the past 10 years, and even during certain periods when their fundamental metrics were not really favorable. They have showed a striking degree of resilience during the pandemic, despite the fact they’re lower market cap, high leverage, and low profitability. Everyone who worked on these reports was surprised by this response.

The market is not just repricing fossil fuels and renewables; it’s also starting to price certain externalities. Certain companies within utilities or chemicals are already seeing significant dispersion. The market is starting to reprice companies that are both obvious and less obvious beneficiaries from the energy transition.

Kroszner: That’s interesting because the usual concern with externalities is that the market doesn’t price them and that you need to have intervention in order to get the pricing right.

Thinking about incentives, how do we get the right incentives for getting the right disclosure and then using that in a systematic way to get to good policy outcomes?

Sir Ronald: It seems to me when you get this transparency on impacts, you shift to a fair tax system. We’re already beginning to talk of the carbon tax, but we will be able to do that for other social issues like diversity and so on if governments choose. So one incentive can be taxation, but transparency provides a massive incentive. If indeed there’s a correlation between impact performance and company valuation, as Mili was illustrating, the transparency itself would create a race to the top.

Fomicov: No firm wants to be the dirtiest on the block. And when you have consistent metrics across sectors and then create proper benchmarking, the role of competition can be extremely powerful. And one of the things that we are advising is that every company needs to show its breakdown of capital expenditures and all metrics that are relevant for each specific sector. Then the market will price them accordingly.