Worst-Case Risks vs. Least-Cost Solutions

By Frank Ackerman | March/April 2019

This article is from Dollars & Sense: Real World Economics, available at http://www.dollarsandsense.org

This article is from the
March/April 2019 issue.

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The damages expected from climate change seem to get worse with each new study. Reports from the Intergovernmental Panel on Climate Change (IPCC) and the U.S. Global Change Research Program, and a multi-author review article in Science, all published in late 2018, are among the recent bearers of bad news. Even more signs of danger continue to arrive in a swarm of research articles, too numerous to list here. And most of these reports are now talking about not-so-long-term damages. Dramatic climate disruption and massive economic losses are coming in just a few decades, not centuries, if we continue along our present path of inaction.

It’s almost enough to make you support an emergency program to reduce emissions and switch to a path of abrupt decarbonization: Something like the Green New Deal, the emerging proposal that would rapidly replace fossil fuels with massive investment in energy efficiency and clean energy, combined with high wages and standards, and fairness in the distribution of jobs and opportunities.

But wait: Isn’t there something about economics we need to figure out first? Would drastic emission reductions pass a cost-benefit test? How do we know that the Green New Deal wouldn’t require spending too much on climate policy? In fact, a crash program to decarbonize the economy is obviously the right answer. There are just a few things you need to know about the economics of climate policy in order to confirm that Adam Smith and his intellectual heirs have not overturned common sense on this issue.

Worst-Case Risks: Why We Need Insurance

For uncertain, extreme risks, policy should be based on the credible worst-case outcome, not the expected or most likely value. This is the way people think about insurance against disasters. The odds that your house won’t burn down next year are better than 99%—but if you own a home, you probably have fire insurance anyway. Likewise, young parents have more than a 99% chance of surviving the coming year, but often buy life insurance to protect their children if the worst should occur.

Real uncertainty, of course, has nothing to do with the fake uncertainty of climate denial. In insurance terms, real uncertainty consists of not knowing when a house fire might occur; fake uncertainty is the (obviously wrong) claim that houses never catch fire. See my book Worst-Case Economics for a more detailed exploration of worst cases and (real) uncertainty, in both climate and finance.

For climate risks, worst cases are much too dreadful to ignore. What we know is that climate change could be very bad for us; but no one knows exactly how bad it will be or when it will arrive. How likely are we to reach tipping points into an irreversibly worse climate, and when will these tipping points occur? As the careful qualifications in the IPCC and other reports remind us, climate change could be very bad surprisingly soon, but almost no one is willing to put a precise number or date on the expected losses.

One group does rush in where scientists fear to tread, guessing about the precise magnitude and timing of future climate damages: economists engaged in cost-benefit analysis (CBA). Rarely used before the 1990s, CBA has become the default, “common sense” approach to policy evaluation, particularly in environmental policy. In CBA-world, you begin by measuring and monetizing the benefits and the costs of a policy—and then “buy” the policy if, and only if, the monetary value of the benefits exceeds the costs.

There are numerous problems with CBA, such as the need to (literally) make up monetary prices for priceless values of human life, health, and the natural environment. In practice, CBA often trivializes the value of life and nature. Climate policy raises yet another problem: CBA requires a single number, such as a most likely outcome, best guess, or weighted average, for every element of costs (e.g., future costs of clean energy) and benefits (e.g., monetary value of future damages avoided by clean energy expenditures). There is no simple way to incorporate a wide range of uncertainty about such values into CBA.

Costs of Emission Reduction Are Dropping Fast

The insurance analogy is suggestive, but not a perfect fit for climate policy. There is no intergalactic insurance agency that can offer us a loaner planet to use while ours is towed back to the shop for repairs. Instead, we will have to “self-insure” against climate risks—the equivalent of spending money on fireproofing your house rather than relying on an insurance policy.

Climate self-insurance consists largely of reducing carbon emissions, in order to reduce future losses. (Adaptation, or expenditure to reduce vulnerability to climate damages, is also important but may not be effective beyond the early stages of warming. And some adaptation costs are required to cope with warming that can no longer be avoided—that is, they have become sunk costs, not present or future policy choices.) The one piece of unalloyed good news in climate policy today is the plummeting cost of clean energy. In the windiest and sunniest parts of the world (and the United States), new wind and solar power installations now produce electricity at costs equal to or lower than fossil fuel-burning plants.

A 2017 report from the International Renewable Energy Agency (IRENA) projects that this will soon be true worldwide: global average renewable energy costs will be within the range of fossil fuel-fired costs by 2020, with on-shore wind and solar photovoltaic panels at the low end of the range. Despite low costs for clean energy, many utilities will still propose to build fossil fuel plants, reflecting the inertia of traditional energy planning and the once-prudent wisdom of the cheap-fuel, pre-climate change era. Super-low costs for renewables, which would have seemed like fantasies ten years ago, are now driving the economics and the feasibility of plans for decarbonization. The Green New Deal may not be free, but it’s not nearly as expensive today as it would have been just a little while ago.

Robert Pollin, an economist who has studied Green New Deal options, estimates that annual investment of about 1.5% of GDP would be needed. That’s about $300 billion a year for the United States, and four times as much, $1.2 trillion a year, for the world economy. Those numbers may sound large, but so are the fossil fuel subsidies and investments that the Green New Deal would eliminate.

In a 2015 study, my colleagues and I calculated that 80% of U.S. greenhouse gas emissions could be eliminated by 2050, with no net increase in energy or transportation costs. Since that time, renewables have only gotten cheaper. (Our result does not necessarily contradict Pollin’s estimate, since the last 20% of emissions will be the hardest and most expensive to eliminate.)

These projections of future costs are inevitably uncertain, because the future has not happened yet. The risks, however, do not appear dangerous or burdensome. So far, the surprises on the cost side have been unexpectedly rapid decreases in renewable energy prices. These are not the risks that require rethinking our approach to climate policy. The disastrous worst-case risks are all on the benefits, or avoided climate damages, side of the ledger. The scientific uncertainties about climate change concern the timing and extent of damages. Therefore, the urgency of avoiding these damages, or conversely the cost of not avoiding them, is intrinsically uncertain, and could be disastrously large.

Climate Damages: Uncertain but Ominous, or $51 per Ton?

It has become common, among economists, to estimate the “social cost of carbon” (SCC), defined as the monetary value of the present and future climate damages per ton of carbon dioxide or equivalent. This is where the pick-a-number imperative of cost-benefit analysis introduces the greatest distortion: huge uncertainties in damages should naturally translate into huge uncertainties in the SCC, not a single point estimate. According to scientists, climate damages are deeply uncertain, but could be ominously large. Alternatively, according to the best-known economic calculation, lifetime damages caused by emissions in 2020 will be worth $51 per metric ton of carbon dioxide, in 2018 prices. These two rival views can’t both be right. In fact, the $51 estimate comes from an awkward and oversimplified calculation; while it yields a better estimate than zero, it still threatens to obscure the meaning of deep uncertainty about the true value of climate damages. The federal government’s calculation of the SCC began under the Obama administration, which assembled an Interagency Working Group to address the question. In the Working Group’s final (August 2016) revision of the numbers, the most widely used variant of the SCC was $42 per metric ton of carbon dioxide emitted in 2020, expressed in 2007 dollars—equivalent to $51 in 2018 dollars. Numbers like this were used in Obama-era cost-benefit analyses of new regulations, placing a dollar value on the reduction in carbon emissions from, say, vehicle fuel-efficiency standards.

To create these numbers, the Working Group averaged the results from three well-known models. These do not provide more detailed or in-depth analysis than other models. On the contrary, two of them stand out for being simpler and easier to use than other models. They are, however, the most frequently cited models in climate economics. They are famous for being famous, the Kardashians of climate models.

The Dynamic Integrated Climate-Economy (DICE) model, developed by William Nordhaus at Yale University, offers a skeletal simplicity: it represents the dynamics of the world economy, the climate, and the interactions between the two with only 19 equations. This (plus Nordhaus’ free distribution of the software) has made it by far the most widely used model, valuable for classroom teaching, initial sketches of climate impacts, and researchers (at times including myself) who lack the funding to acquire and use more complicated models. Yet no one thinks that DICE represents the frontier of knowledge about the world economy or the environment. DICE estimates aggregate global climate damages as a quadratic function of temperature increases (i.e., damages as a percentage of world output are assumed to depend on the square of temperature increases), rising only gradually as the world warms.

The Policy Analysis of the Greenhouse Effect (PAGE) model, developed by Chris Hope at Cambridge University, resembles DICE in its level of complexity, and has been used in many European analyses. It is the only one of the three models to include any explicit treatment of uncertain climate risks, assuming the threat of an abrupt, mid-size economic loss (beyond the “predictable” damages) that becomes both more likely and more severe as temperatures rise. Perhaps for this reason, PAGE consistently produces the highest SCC estimates among the three models.

And, finally, the Framework for Uncertainty, Negotiation, and Distribution (FUND) model, developed by Richard Tol and David Anthoff, is more detailed than DICE or PAGE, with separate treatment of more than a dozen damage categories. Yet the development of these damages estimates has been idiosyncratic, in some cases (such as agriculture) relying on relatively optimistic research from 20 years ago rather than more troubling, recent findings on climate impacts. Even in later versions, after many small updates, FUND still estimates that many of its damage categories are too small to matter; in some FUND scenarios, the largest cost of warming is the increased expenditure on air conditioning.

Much has been written about what’s wrong with relying on these three models. The definitive critique is the National Academy of Sciences study, which reviews the shortcomings of the three models in detail and suggests ways to build a better model for estimating the SCC. (Released just days before the Trump inauguration, the study was doomed to be ignored.)

Embracing Uncertainty

Expected climate damages are uncertain over a wide range, including the possibility of disastrously large impacts. The SCC is a monetary valuation of expected damages per ton of carbon dioxide. Therefore, SCC values should be uncertain over a wide range, including the possibility of disastrously high values. Yet the Working Group’s methodology all but obscures the role of uncertainty in climate science.

A broader review of climate economics yields results consistent with the expected pattern. Look beyond the three-model calculation, and the range of possible SCC values is extremely wide, including very high upper bounds. Many studies have adopted DICE or another model as a base, then demonstrated that minor, reasonable changes in assumptions lead to huge changes in the SCC.

To cite a few examples: A meta-analysis of SCC values found that, in order to reflect major climate risks, the SCC needs to be at least $125.

A study by Simon Dietz and Nicholas Stern found a range of optimal carbon prices (i.e., SCC values), depending on key climate uncertainties, ranging from $45 to $160 for emissions in 2025, and from $111 to $394 for emissions in 2055 (in 2018 dollars per ton of carbon dioxide). In my own research, co-authored with Liz Stanton, we found that a few major uncertainties lead to an extremely wide range of possible SCC values, from $34 to $1,079 for emissions in 2010, and from $77 to $1,875 for 2050 emissions (again converted to 2018 dollars).

Martin Weitzman has written several articles emphasizing that the SCC depends heavily on the unknown shape of the damage function—that is, the details of the assumed relationship between rising temperatures and rising damages. His “Dismal Theorem” article argues that the marginal value of reducing emissions—the SCC—is literally infinite, since catastrophes that would cause human extinction remain too plausible to ignore (although they are not the most likely outcomes).

Whether or not the SCC is infinite, many researchers have found that it is uncertain, with the broad range of plausible values including dangerously high estimates. This is the appropriate economic reflection of scientific uncertainty about the timing and extent of climate damages.

The Low Price of Self-Insurance

As explained above, deep uncertainty about the magnitude and timing of risks stymies the use of cost-benefit analysis for climate policy. Rather, policy should be set in an insurance-like framework, focused on credible worst-case losses rather than most likely outcomes. Given the magnitude of the global problem, this means “self-insurance”—investing in measures that make worst cases less likely.

How much does climate “self-insurance”—greenhouse gas emission reduction—cost? Several early (2008 to 2010) studies of deep decarbonization, pushing the envelope of what was technically feasible at the time, came up with mid-century carbon prices of roughly $150–$500 per ton of carbon dioxide abated. (Prices were reported in 2005 dollars; multiply by 1.29 to convert to 2018 dollars.) Since then, renewable energy has experienced rapid progress and declining prices, undoubtedly lowering the cost of a maximum feasible reduction scenario.

Even a decade ago, at $150 to $500 per ton, the cost of abatement was comparable to or lower than many of the worst-case estimates of the SCC, or climate damages per ton. In short, we already know, and have known for a while, that doing everything on the least-cost emission reduction path will cost less, per ton of carbon dioxide, than worst-case climate damages. That’s it: the end of the economic story about evaluating climate policy. We don’t need more exact, accurate SCC estimates; they will not be forthcoming in time to shape policy, due to the uncertainties involved. Since estimated worst-case damages are rising over time, while abatement costs (such as the costs of renewables) are falling, the balance is tipping farther and farther toward “do everything you can to reduce emissions, now.” That was already the correct answer some years ago, and only becomes more correct over time.

FRANK ACKERMAN is principal economist at Synapse Energy Economics in Cambridge, Mass., and one of the founders of Dollars & Sense.

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