CONGRESS OF THE UNITED STATES

CONGRESSIONAL BUDGET OFFICE

A

CBO

PAPER

JANUARY 2005

Uncertainty in

Analyzing

Climate Change:

Policy

Implications

© Photostogo

The Congress of the United States O Congressional Budget Office

CBO

Uncertainty in Analyzing Climate Change: 

Policy Implications

January 2005

A

PAPER
Note

Unless otherwise stated, prices are in current dollars.
Preface

In addressing climate change, researchers and policymakers face various sources of uncertainty. The potential stakes in making policy choices are high: although emissions restrictions 

could impose significant costs, many experts believe that, if left unchecked, emissions could 

ultimately lead to costly damages. 

This Congressional Budget Office (CBO) paper—prepared at the request of the Ranking 

Member of the Senate Committee on Environment and Public Works—provides an overview 

of the sources of uncertainty that limit the understanding of climate change and complicate 

the assessment of policies to address it. The paper provides examples of the different ways that 

analysts have addressed those uncertainties in formulating policy recommendations, illustrates 

the practical difficulties in doing so, and demonstrates the sensitivity of policy results to variations in assumptions about uncertain elements. Finally, it discusses the implications of uncertainty for three different types of policy responses: research and development, mitigation of 

greenhouse gas emissions, and adaptation to a warmer climate. In keeping with CBO’s mandate to provide objective, nonpartisan analysis, this paper makes no recommendations.

Terry Dinan and Robert Shackleton, Jr., wrote the paper under the direction of Roger Hitchner and Robert A. Dennis. Douglas Hamilton, Arlene Holen, Mark Lasky, Angelo Mascaro, 

Chad Newcomb, and Elizabeth Robinson of CBO provided valuable comments, as did Peter 

J. Wilcoxen of Syracuse University, Henry Jacoby of the Massachusetts Institute of Technology, and William Pizer of Resources for the Future. (The assistance of external reviewers 

implies no responsibility for the final product, which rests solely with CBO.)

Christine Bogusz edited the paper, and John Skeen proofread it. Maureen Costantino prepared the paper for publication and designed the cover, Lenny Skutnik printed the initial copies, and Annette Kalicki and Simone Thomas produced the electronic versions for CBO’s 

Web site (www.cbo.gov). 

Douglas Holtz-Eakin

Director

January 2005

Summary vii

1 Background and Introduction 1

2 Scientific and Economic Sources of Uncertainty 5

Uncertainty Affecting Costs 5

Uncertainty Affecting Benefits 7

3 Problems in Valuation 13

Agriculture: Data Gaps Remain 14

Health: Questions About Valuing Lives Saved 15

Human Settlements and Ecosystems: Valuing Damages to Nonmarketed

Goods and Services 16

Catastrophic Damages: Expert Opinions Vary Widely 16

The Usefulness of Subjective Estimates 17

4 Problems in Aggregation 19

Problems in Comparing Present Costs and Future Damages 19

Problems in Determining the Appropriate Level of Risk Reduction 22

Problems in Aggregating Costs and Benefits Across Regions 22

5 Policy Implications 25

Research and Development 25

Mitigation 26

Adaptation 36

CONTENTS
vi UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

Table

5-1. An Example of the Advantage of Using a Tax, Rather Than a Cap,

to Reduce Carbon Emissions 29

Figures

4-1. The Present Discounted Value of $1,000 20

5-1. Projected Change in Temperature in 2100 from a Specific Policy 34

Boxes

S-1. Price- Versus Quantity-Based Economic Incentives xi

1-1. Uncertainty and Natural Variability 2

2-1. Scientific Understanding About Abrupt Climate Change 10

5-1. International Cooperation on Climate Policy 33
Summary

Since the 19th century, scientists have known that 

concentrations of carbon dioxide and other greenhouse 

gases in the atmosphere affect the Earth’s climate.1

 Human activities—mainly deforestation and the burning of 

fossil fuels—are releasing large quantities of those gases. 

Because those gases, once emitted, affect atmospheric 

concentrations for centuries, researchers and policymakers are concerned about the impact of those emissions on the climate. 

In assessing the potential risks from climate change and 

the costs of averting it, however, researchers and policymakers encounter pervasive uncertainty. That uncertainty contributes to great differences of opinion as to the 

appropriate policy response, with some experts seeing little or no threat and others finding cause for immediate, 

extensive action. Policymakers are thus confronted with a 

wide range of recommendations about how to address the 

risks posed by a changing climate—in particular, 

whether, how, and how much to limit emissions of 

greenhouse gases.

This Congressional Budget Office paper provides policymakers with an overview of the sources of uncertainty 

that limit the understanding and complicate the assessment of climate policies. It provides examples of the different ways that analysts have addressed those uncertainties in formulating policy recommendations, illustrates 

the practical difficulties in doing so, and demonstrates 

the sensitivity of policy results to variations in assumptions about uncertain elements. In addition, it discusses 

the implications of uncertainty for three different types of 

policy responses: research and development, mitigation 

of greenhouse gas emissions, and adaptation to a warmer 

climate. This paper primarily focuses on mitigation.

Because climate change is a global phenomenon—emissions from anywhere in the world mix in the atmosphere 

and affect regional climates everywhere—effective policies will require international cooperation and coordination. This paper discusses several different analyses that 

are based on the proposition that policies should maximize global net benefits—that is, expected global benefits 

minus expected global costs. Such analyses typically recommend policies that would motivate individuals and 

firms to make increasingly costly reductions in emissions 

up to the point at which the expected cost of the last reduction would be equal to its expected benefit. (Beyond 

that point, costs would exceed benefits, so additional reductions would not be worth the cost.) That approach 

provides a useful framework for assessing alternative policies. However, conducting such analyses in the face of 

uncertainties about both costs and benefits raises many issues. 

Scientific and Economic Sources of 

Uncertainty

Researchers who assess the costs and benefits of various 

policies to reduce greenhouse gas emissions must grapple 

with numerous gaps in scientists’ understanding of the 

natural world as well as inherent difficulties in forecasting 

natural variability and human behavior. The uncertainties affecting benefits—that is, the future damages that 

would be avoided by limiting emissions today—are particularly large and pervasive. 

Uncertainty Affecting Benefits 

Major scientific uncertainties complicate any assessment 

of the benefits of policies to reduce climate change. Those 

uncertainties include the following:

B How greenhouse gas emissions will accumulate in the 

atmosphere and how the resulting change in concentrations will affect the average global temperature;

1. For more background information on climate change, see Congressional Budget Office, The Economics of Climate Change: A 

Primer (April 2003). 
viii UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

B How changes in global temperature will be distributed 

across seasons and regions and how they will affect 

other variable characteristics of climate, such as rainfall, severity of storms, and sea level;

B How those changes in regional climates will affect natural and human systems, such as agricultural crops, 

property, species, and human health; and

B How short-term impacts will differ from the longterm impacts that will remain after natural and human 

systems have had time to adapt to the new climate. 

One area of relatively recent concern is the potential for 

abrupt climate change—the possibility that the gradual 

buildup of greenhouse gases in the atmosphere could 

push the global climate system over a threshold, triggering an abrupt change to a new climate equilibrium. Scientists now realize that abrupt changes have occurred in 

the past (for example, a cold, dry, windy period lasting 

1,600 years abruptly began about 12,800 years ago), and 

they have started to speculate whether human-induced 

changes in climate could trigger such changes in the future. An abrupt, unexpected shift—currently considered 

possible but very unlikely over the next century—could 

prove much more difficult for people and ecosystems to 

adapt to than a gradual change would be and, therefore, 

much more costly.

Uncertainty Affecting Costs 

The costs of policies to control greenhouse gas emissions 

will depend on the magnitude of future emissions: the 

lower emissions are in the absence of policy initiatives, 

the easier it will be to meet a given target (be it for temperature, emissions, or atmospheric concentrations) and 

the lower the cost will be. Yet future trends in emissions 

are uncertain—they depend on the pace of population 

and economic growth, the development and diffusion of 

technologies, and the demand for fossil fuels.

Furthermore, the cost of reducing emissions depends in 

large part on the efficiency of the policies that motivate 

those reductions. Provided that they are implemented effectively, policies that give individuals and firms an economic incentive to reduce emissions would probably 

achieve reductions at a lower cost than would commandand-control-style regulations that dictated specific methods for emissions reductions, locations for emissions reductions, or both. 

Finally, the cost of reducing emissions is most accurately 

measured by the resulting price increases paid by consumers, the lower short-term profits made by producers, 

and the reduction in consumers’ welfare that would result 

from changes in their purchasing patterns or behavior 

(for example, choosing to carpool). Focusing only on the 

cost of emissions-reduction technologies could considerably understate the total cost of adopting them. Even 

when the cost of emissions-reduction technologies is well 

understood, the challenges involved in estimating those 

broader economic impacts contribute to uncertainty 

about aggregate costs. 

Problems in Valuing Damages from 

Climate Change

In addition to the numerous scientific and economic uncertainties involved in determining climate-related damages, there are major questions about how those damages 

should be valued. Although there are many possible ways 

to define and measure value, economic analysis focuses 

on the value that individuals place on a particular good or 

service, as reflected in their willingness to forgo other 

goods and services to obtain it. For many goods, those individual valuations are reflected in market prices, which 

provide a standard of comparison across goods. When 

possible, economic analyses of climate policies use market 

prices to estimate the value people place on the damages 

that such policies would avoid.

Many of the damages from climate change, such as harm 

to ecosystems and adverse health effects for humans, 

would fall on entities, goods, and services that are not exchanged in markets. In the absence of market prices for 

certain goods and services, analysts face serious challenges 

in determining what people are willing to pay for them, 

adding another layer of uncertainty to policy analysis.

An additional problem is that many of the nonmarket 

damages—loss of species and ecosystems, for example—

are to public goods, which are available to everyone for 

free. The value of a public good is the total of everyone’s 

individual valuation. Researchers must therefore try to assess valuations for a large number of people to estimate 

the economic value lost when public goods are damaged.

Faced with those difficulties, analysts sometimes use arbitrary and controversial rules of thumb to estimate people’s willingness to pay. One study, for instance, assumed 

that individuals in each region of the world would be 
SUMMARY ix

willing to pay twice their annual income to avoid a premature loss of one year of life from an increase in disease 

resulting from a warmer climate. Some people object to 

such measures because they assign lower values to the adverse health effects or loss of life that are expected to occur in low-income countries than they apply to equivalent damages in high-income countries. That problem 

has no simple solution, however. Using a uniform global 

value for all lives saved (based on average global income) 

would result in a large disparity between the value placed 

on lives saved in low-income countries via climate change 

policies and the value (determined on the basis of countries’ local economic resources) placed on lives saved via 

other policies, such as providing clean water or basic 

health care.

Based on such arbitrary and controversial valuations, the 

available damage estimates—and the policy prescriptions 

resulting from their use—should not be viewed as precise 

measures. Nevertheless, those valuations can provide a 

general sense of the magnitude of the damages from climate change and the relative benefits of alternative policies.

Problems in Aggregating Costs and 

Benefits

Deciding on appropriate policies to address climate 

change is further complicated by the uneven distribution 

of costs and benefits across regions and over time.

Controversy About the Weight to Attach to Future 

Damages 

Even though the costs of policies to avoid climate-related 

damages would be incurred in the near term, the bulk of 

any damages from current emissions are expected to occur a century or more in the future. Analysts conventionally compare present costs and future benefits through 

present-value calculations, which discount future benefits 

at the market rate of interest. (That approach is based on 

the fact that the alternative to devoting resources to the 

policy being evaluated would be to invest them, allow the 

investment to compound over time, and derive significantly more income in the future.)

In the case of climate change, the choice of a discount 

rate is crucial because the very long time horizons involved make the results of cost-benefit analyses extremely 

sensitive to the discount rate that is used in the analysis. 

Different rates can lead to very different conclusions 

about the appropriate policy response, and that fact has 

led to a great deal of controversy about what rate

to use.

Many analysts argue that the discount rate used in climate change analyses should reflect observed rates of return on long-term investments, adjusted for inflation and 

risk. According to that view, such returns represent the 

opportunities given up by investing resources in avoiding 

damages from climate change, as well as the opportunity 

to set aside resources today to compensate future generations for damages they may experience. Adjustment for 

uncertainty leads to a lower implicit discount rate, the 

farther in the future the benefits are expected to occur.

Some analysts, however, argue that distortions in saving 

and investment behavior resulting from taxes cause observed rates of return to be higher than they would be 

otherwise. According to that view, a lower rate of return 

would better reflect people’s actual preferences between 

present and future costs and benefits. Applying a lower 

discount rate to the benefits of climate change policies 

would result in dedicating more resources to those policies.

Still other analysts argue that because costs and benefits 

are incurred by different generations, the valuation of future benefits should be viewed primarily as an equity decision (similar to providing foreign aid to developing 

countries) rather than as a traditional investment decision. According to that view, a discount rate can be 

thought of simply as a gauge of current generations’ willingness to provide benefits to future ones—a willingness 

that need not be consistent with people’s personal investment decisions. In general, proponents of such a view 

argue for discount rates that are lower than the rates of return on long-term investments.

Problems in Determining the Appropriate Level of 

Risk Reduction 

The choice of how stringent a policy to adopt is similar to 

a choice about insurance coverage: higher prices for emissions impose greater costs on households and businesses 

today but provide more protection against unpleasant 

surprises from damages in the future. People who are 

more averse to risk may prefer to implement a more stringent policy to control emissions (paying more up front in 

order to avoid or minimize risk in the future), whereas 

those who are less averse to risk may prefer a less stringent 

policy (paying less up front and incurring greater risk in 
x UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

the future). Such differences in risk aversion may contribute to differences of opinion over the appropriate level of 

policy stringency.

Complications in Aggregating Benefits and Costs 

That Occur in Different Parts of the Globe

Determining the appropriate level of policy stringency is 

complicated by two other factors. First, some countries 

and regions could benefit from climate change while others would be worse off. For example, some researchers 

predict that India would experience a loss equal to about 

5 percent of its total output if the global temperature rose 

by 2.5° Celsius, whereas Russia would benefit by an 

amount equal to about 0.65 percent of its total output. 

Because effects are aggregated, Russia’s gains would offset 

India’s losses, resulting in a less stringent policy than 

would be called for if only India’s losses were taken into 

consideration. Second, countries that would bear a relatively large share of the costs of climate policies are not 

necessarily those that would receive a large share of the 

benefits. For example, under a policy determined by a 

global cost-benefit analysis, the United States would incur a substantial share of the costs but would receive a 

disproportionately small share of the benefits. Developing countries, in contrast, would incur a relatively small 

share of the costs but would receive a disproportionately 

large share of the benefits. 

Under conventional methods of calculating net benefits, 

the gains by countries that would benefit from climate 

change policies would be deducted from the costs borne 

by countries that would be harmed. For policies whose 

benefits outweighed the costs, winners could compensate 

losers and still be better off. Given that such compensation is unlikely to occur, however, some observers find 

that logic unpersuasive.

Policy Implications

The pervasive uncertainty inherent in many aspects of climate change presents researchers and policymakers with a 

challenge in attempting to develop appropriate policies. 

The potential stakes in making policy choices are high: 

emissions restrictions could impose significant costs, but 

many experts believe that, if left unchecked, emissions 

could ultimately lead to costly damages. 

Although pursuing a strategy of waiting until uncertainties have been resolved and then implementing a single 

long-term “best” solution may sound appealing, uncertainty in the assessment of climate policy cannot be eliminated. Furthermore, greenhouse gas emissions that are 

released today will affect atmospheric concentrations for 

hundreds of years, potentially leading to damages that 

would only gradually appear and continue far into the future. 

A more pragmatic climate policy will probably involve a 

sequence of decisions based on the gradual accumulation 

of information and the resolution of uncertainties. For 

such an approach, policies that can be easily modified 

over time would offer advantages. A flexible approach to 

dealing with climate change could include three different 

policy strategies:

B Researching the problem and developing technologies 

to address it, 

B Restricting greenhouse gas emissions (mitigation), and 

B Adapting to a warmer climate. 

Determining the appropriate extent to which each of 

those strategies should be implemented and the balance 

among them is beyond the scope of this analysis. Instead, 

for each strategy, this analysis examines implications 

about policy design that can be drawn from an understanding of the uncertainties described above. This analysis primarily focuses on mitigation—the area for which 

existing research offers the most useful insights.

Research and Development

Research is an essential part of any comprehensive strategy to address potential changes in the climate. Research 

is likely to provide benefits by helping to resolve uncertainties (including uncertainties about the physical damages that might result from climate change as well as the 

substantial uncertainties about how to evaluate those 

damages) and by leading to the development of technologies to make those cuts in emissions that prove advisable 

and to adapt to any climate changes that occur. If potential damages from climate change turned out to be large, 

such technologies could help reduce the cost of restricting 

greenhouse gas emissions and adapting to a warmer climate. If potential damages turned out to be relatively minor, the technologies need not be deployed.

Mitigation

Analysts generally agree that economic incentives could 

limit several types of greenhouse gas emissions (including 
SUMMARY xi

carbon dioxide emissions) more cost-effectively than 

command-and-control strategies could. Whereas 

command-and-control strategies specify where and how 

emissions should be reduced, economic incentives specify 

more-general restrictions and leave the where-and-how 

decisions to the market. Policymakers can choose between two general types of economic incentives: ones that 

set a price for emissions, such as emissions taxes, or ones 

that specify an aggregate limit or cap, such as cap-andtrade programs (see Summary Box 1). 

Given Current Uncertainties, Pricing Policies Have More 

Advantages Than Caps. If policymakers had complete and 

accurate information on both the costs and benefits of 

various levels of emissions reductions, they could achieve 

the level of reductions that best balanced costs and benefits using either an emissions price or an emissions cap. 

With full information, policymakers could set the price 

or cap to the level at which the cost of the last reduction 

was equal to the benefit from that reduction. 

However, neither the costs nor the benefits of restricting 

greenhouse gas emissions are known with certainty. For 

that reason, the best that policymakers can do is to 

choose the policy instrument that is most likely to minimize the cost of choosing the “wrong” level of control. 

Choosing policies that are too stringent (by setting too 

high a price or too tight a cap) would result in excess costs 

that are not justified by their benefits. Alternatively, 

choosing policies that are too lenient (by setting too low a 

price or too loose a cap) would result in forgone benefits 

that would have outweighed the cost of obtaining them.

Analysts generally conclude that under uncertainty, price 

instruments are much more efficient than quantity instruments for restricting carbon dioxide emissions—that 

is, they are much more likely to minimize the cost of getSummary Box 1.

Price- Versus Quantity-Based Economic Incentives

Economic incentives can be either price-based or 

quantity-based. A price-based economic incentive—

such as a tax on emissions—would raise the cost of 

emitting greenhouse gases, thereby encouraging 

households and firms to cut their emissions as long 

as the cost of doing so was less than the tax. That approach would set an upper limit on the cost of emissions reductions (at the level of the tax) but would 

not ensure that any particular emissions target was 

met. 

A quantity-based incentive—such as a cap-and-trade 

program—would set an overall limit on the level of 

greenhouse gas emissions but leave the decisions of 

where and how the necessary reductions should take 

place to households and firms. Under that approach, 

policymakers would establish an overall cap on emissions but allow regulated firms to trade rights to 

those emissions, called allowances. That trading 

would permit firms that could reduce their emissions 

most cheaply to sell some of their allowances to firms 

that faced higher costs to reduce their emissions. 

Such an approach would limit the overall level of 

emissions and achieve the emissions target at the 

lowest possible cost. It would not place any explicit 

limit on the cost of individual emissions reductions, 

however. 

A third approach—a cap-and-trade program with a 

safety valve—would combine an overall cap on emissions with an upper price for allowances. Under that 

hybrid approach, policymakers would establish an 

overall cap and allow firms to trade allowances; in 

addition, they would determine an upper price—referred to as the safety-valve price—for allowances. If 

the price of allowances rose to the safety-valve price, 

the government would sell as many allowances as 

was necessary to maintain that price. Thus, if the 

safety valve was triggered, the actual level of emissions would exceed the cap. The cap would be met 

only if the allowance price never rose above the 

safety-valve price. (Another hybrid approach, involving a “circuit breaker” instead of a safety valve, 

would freeze a gradually declining cap on emissions 

if the allowance price rose above a predetermined 

level. Such a policy would not necessarily limit allowances to the trigger price, though.)
xii UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

ting it wrong. That conclusion follows from two observations: first, the expected benefits created by each additional reduction in emissions in a given year would 

probably be fairly constant; second, the costs would probably rise—perhaps steeply—with more abatement.2

Thus, setting an emissions price equal to the expected 

benefits would result in the least-costly balancing of expected costs and benefits. If actual costs were greater 

than, or less than, anticipated, people would limit emissions less than, or more than, policymakers projected; yet 

emissions would be reduced up to the point at which the 

cost of doing so was equal to the expected benefits (as reflected in the emissions price). In contrast, a strict cap on 

emissions could result in actual costs that were far greater 

(or less) than expected—and that therefore exceeded or 

fell below the expected benefits. 

Some observers have questioned the robustness of that 

logic, however, in light of recent evidence indicating that 

the buildup of greenhouse gases could push the climate 

system over a threshold, triggering an abrupt and costly 

shift to a new equilibrium. Current research suggests that 

the potential for catastrophic damages can indeed tilt the 

balance in favor of quantity controls, but only under restrictive conditions that do not currently exist: first, damages must be projected to rise very rapidly once a particular threshold (that is, a certain level of greenhouse gas 

concentrations or temperature) is reached; second, the 

level of the threshold must be known; and third, current 

emissions must be pushing the climate close enough to 

that threshold that policymakers would want to make 

very large cuts in current emissions in order to quickly 

stabilize the atmospheric stock of greenhouse gases. Currently, there is no consensus about whether such a threshold exists or where it lies. Under those circumstances, 

price instruments appear to be more cost-effective than 

quantity instruments for controlling emissions while 

minimizing the adverse consequences of choosing the 

wrong level of control.

The superiority of price instruments could be reversed if 

accumulating information revealed a trigger temperature 

(or atmospheric concentration) that must be avoided and 

a level of emissions that would raise temperatures above 

the trigger. If so, policymakers might decide to switch to 

a quantity instrument as the potential for catastrophic effects became clearer. A hybrid policy, such as a cap-andtrade program with a safety-valve price (see Summary 

Box 1), would provide such flexibility. The safety valve 

would set an upper limit on the current cost of incremental emissions reductions. In effect, the hybrid policy 

would function as a tax if the safety valve was triggered. 

Should circumstances change, however, the safety valve 

could be phased out or eliminated altogether, transforming the trading program into one with a fixed cap on 

overall emissions.

The Best Emissions Price Is Unclear. If researchers conclude that current emissions will result in future damages 

and that the present value of those damages (after they 

are discounted) is greater than zero, then it is appropriate 

to set an emissions price that is greater than zero. However, given all the uncertainties associated with evaluating 

the costs and benefits of climate change policies, as well 

as the problems associated with aggregating them, accurately determining what price would best balance those 

costs and benefits is probably not a realistic goal. Even if 

scientists resolved uncertainties about physical damages, 

people would probably differ in their valuation of those 

damages, in the weight they attached to future effects, 

and in the level of risk they were willing to accept. Those 

differences would all result in differences of opinion as to 

the appropriate level of stringency in controlling emissions—and thus the best price to charge for emissions. 

Researchers agree, however, that the costs of such a pricing policy could be moderated by phasing in prices gradually, allowing the economy time to replace the existing 

fossil-fuel-burning capital stock at the lowest cost. 

International Coordination Could Greatly Reduce

Costs. Because the causes and consequences of climate 

change are global, the most cost-effective mitigation policies would require a coordinated international effort. The 

nature of the climate problem will make international 

agreement difficult to reach, however. The distribution of 

likely costs and benefits leaves countries and regions with 

considerably divergent interests. Furthermore, developing 

countries, which contributed a relatively small share of 

historical emissions but are expected to contribute a 

growing share of future ones, may object to having their 

2. Expected benefits are thought to be constant over the range of 

potential emissions reductions in a single year because those 

reductions will have only a small effect on the total stock of greenhouse gases in the atmosphere, and damages are a function of the 

size of that total stock. (Total emissions in a single year represent 

less than 1 percent of atmospheric emissions, so the reduction in 

emissions in a given year is likely to be a small fraction of 1 percent of atmospheric emissions.)
SUMMARY xiii

development impeded by emissions restrictions. Finally, 

the challenges associated with enforcing a global solution 

may make some nations reluctant to participate, adding a 

source of uncertainty about how cost-effective the policies will be.

Information on Underlying Uncertainties and Disaggregated Benefits Could Highlight Policy Trade-Offs. While 

policymakers may derive important insights from assessments that attach monetary values to benefits and aggregate the expected costs and benefits of different mitigation policies, they may also profit from additional, 

more-detailed information, such as the following:

B Information that describes ranges of plausible outcomes for specific policies, measures of the probability 

that a given policy will achieve its objective, and acknowledgment of lingering uncertainties that cannot 

be quantified. That information may allow policymakers to more clearly see the risks associated with alternative policies. 

B Information about important nonmarket benefits—

such as health benefits or species preservation—in a 

disaggregated, nonmonetized form (for example, the 

decrease in number of species lost). That information 

would also allow policymakers to make their own 

judgments about people’s willingness to pay for damages that are difficult to monetize.

B Information about the regional distribution of costs 

and benefits. That information could help policymakers understand the strength of other countries’ 

and regions’ interests in international negotiations.

Adaptation

Although it has received relatively little attention from 

analysts and policymakers, adaptation is likely to be an 

important element of an effective climate strategy. Unlike 

mitigation policy, which could be implemented largely 

with a single instrument—for instance, a single emissions 

price or an aggregate emissions cap—efforts to promote 

adaptation are likely to be more diffuse, involving numerous policies in many different areas. Those policies could 

include the following:

B Promoting the efficient use of water resources (which 

are likely to become scarcer in some regions) through 

prices that reflect scarcity or through the establishment of markets for water;

B Encouraging the development of low-cost technologies for desalinating seawater;

B Encouraging the preservation of green corridors that 

would allow plant and animal species to migrate as 

their habitat changed;

B Facilitating the relocation of people living in low-lying 

areas of counties prone to increased flooding; and

B Encouraging the development and use of droughtresistant crops. 

As the above list illustrates, many policies that could facilitate adaptation to a changing climate are likely to yield 

benefits even if climate change proved to be relatively benign.

1

Background and Introduction

The Earth’s climate is driven mainly by solar radiation, which is absorbed into the atmosphere, ocean, and 

land and ultimately radiated back into space. Some of 

that outgoing radiation is trapped by naturally occurring 

greenhouse gases in the atmosphere and radiated back toward the surface, however, keeping it about 60o Fahrenheit (F), or 33o Celsius (C), warmer, on average, than it 

would be otherwise.1

Since the onset of the industrial revolution more than 

two centuries ago, people have released large and growing 

quantities of greenhouse gases into the atmosphere, raising the prospect of a gradual warming of the Earth’s climate. Those emissions are associated primarily with the 

burning of fossil fuels—crude oil, coal, and natural gas—

the world economy’s primary source of energy. Measured 

in terms of warming potential, carbon dioxide from fossil 

fuels currently accounts for about 60 percent of greenhouse gas emissions. Carbon dioxide from deforestation 

accounts for another 15 percent or so, and the rest of the 

emissions are composed of a number of other greenhouse 

gases, largely methane from a wide variety of mainly agricultural sources.

Developed countries account for the bulk of emissions, 

especially those from fossil fuels. In 2000, for instance, 63 

percent of carbon dioxide emissions from fossil fuels 

came from developed countries, even though those countries account for only 22 percent of the global population. Developing countries, with 78 percent of the population, were responsible for only 37 percent of fossil-fuel 

emissions. Over the next 20 years, developing countries 

are expected to account for roughly two-thirds of the 

growth in emissions as their populations and economies 

expand rapidly. Nevertheless, on a per-person basis, developing countries’ emissions will remain far below those 

of developed countries. The typical developing country 

emits about 0.5 metric ton of carbon (mtc) per person every year; the typical developed country emits about 3 mtc 

per person, and the United States emits about 5.5 mtc 

per person.

Emissions have raised the atmospheric concentration of 

carbon dioxide by roughly one-third in the past two centuries and are currently raising it by about 0.4 percent per 

year. Concentrations of other greenhouse gases are increasing as well. Because the degree of warming depends 

on the total stock in the atmosphere rather than the flow 

of emissions alone, greenhouse gases are sometimes referred to as “stock pollutants.” 

The average surface temperature of the Earth has already 

risen by between 0.7oF and 1.4oF (0.4oC and 0.8oC) 

since the mid-19th century, with the warming trend most 

pronounced during the past decade and at higher latitudes. Scientists generally conclude that the warming 

trend is probably largely the result of human activities, although they cannot rule out the possibility that other 

natural forces may be playing a significant role.2

 Despite 

that uncertainty, scientists also expect emissions that have 

already occurred to gradually warm the climate further. 

Moreover, the accelerating pace of emissions is expected 

to contribute to a continuing warming trend, with highly 

uncertain but potentially serious and costly effects in at 

least some regions of the world.

CHAPTER

1. For further background information on climate change, see Congressional Budget Office, The Economics of Climate Change: A 

Primer (April 2003). 

2. The National Research Council concludes: “The changes 

observed over the last several decades are likely mostly due to 

human activities, but we cannot rule out that some significant 

part of these changes is also a reflection of natural variability.” See 

National Research Council, Committee on the Science of Climate 

Change, Climate Change Science: An Analysis of Some Key Questions (Washington, D.C.: National Academy Press, 2001).
2 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

Much of the research to assess the potential processes and 

impacts of climate change (and policies to address it) 

makes use of numerical models. Those models represent 

complex entities (such as the atmosphere, the world’s 

population, or total energy consumption) with relatively 

simple data and summarize complex interactions (such as 

the exchange of heat between the atmosphere and the 

ocean or the effect of a change in average global temperature on regional agriculture) with numerical relations 

called parameters. Because much of the information is of 

poor quality and many of the interactions are imperfectly 

understood, they can be modeled with only limited certainty. 

In some cases, uncertainty results from a lack of information or knowledge that, in principle, could be overcome 

with further research. In other cases, however, it stems 

from inherent, natural variability that renders the processes being studied only roughly predictable, as with 

fluctuating weather patterns (see Box 1-1). In yet other 

cases—as with technological breakthroughs—uncertainty 

stems from processes that are essentially unpredictable. 

Levels of uncertainty can range from statistical uncertainty (when researchers can attach probabilities to different outcomes) to scenario uncertainty (when researchers 

can characterize a variety of plausible outcomes but do 

not understand the underlying processes well enough to 

provide probabilities) to recognized ignorance (when researchers lack sufficient understanding to develop plausible scenarios). 

This Congressional Budget Office paper provides policymakers with an overview of the sources of uncertainty 

that limit the understanding and complicate the assessment of climate policies. It provides examples of the different ways that analysts have addressed those uncertainties in formulating policy recommendations, illustrates 

the practical difficulties in doing so, and demonstrates 

the sensitivity of policy results to variations in assumptions about uncertain elements. Finally, it discusses the 

implications of uncertainty for three different policy 

strategies:

B Research to resolve uncertainties about potential damages and to develop technologies that might cut the 

cost of reducing emissions or ease the adaptation to a 

warmer climate,

B Economic incentives to encourage low-cost emissions 

reductions today, with the expectation that more extensive reductions may be needed in the future, and

B Policies to help people adapt to any warming that does 

occur.

In illustrating the sources and implications of uncertainty, the paper discusses a number of analyses that are 

based on the proposition that policies should maximize 

global net benefits—that is, expected global benefits minus expected global costs—by inducing individuals and 

firms to make increasingly costly reductions in emissions 

up to the point at which the expected cost of the last reBox 1-1.

Uncertainty and Natural Variability

The global climate is affected by long-term variations in the Earth’s orbit and in solar radiation (as 

well as other external influences, such as eruptions of 

volcanic material into the atmosphere). Most of the 

variation in climate, however, involves internal interactions among the Earth’s climate-related components: the atmosphere, oceans, glaciers, land surface, 

and biosphere. 

Those interactions are complex and nonlinear, 

meaning that there is often no simple proportional 

relationship between a cause and its effects. Complexity and nonlinearity make climate patterns very 

sensitive to small perturbations—in technical terms, 

dynamically unstable or chaotic. That sensitivity 

greatly limits scientists’ ability to accurately represent 

or predict the fluctuations of the climate system in 

great detail. Instead, climate forecasting is limited to 

estimating changes in the likelihood of different 

types of weather events, such as changes in average 

summer and winter temperatures or annual rainfall, 

or in the probability of different extremes of temperature or of severe storms or droughts in different 

parts of the world.
CHAPTER ONE BACKGROUND AND INTRODUCTION 3

duction would be equal to its expected benefit. That 

proposition involves a number of assumptions about how 

to aggregate costs and benefits across countries and over 

time—assumptions that are controversial. Moreover, because the causes and consequences of climate change are 

global, such policies would require international cooperation and coordination—itself an uncertain possibility. 

Those and related complications are addressed in the following chapters.

2

Scientific and Economic Sources of Uncertainty

Uncertainty permeates people’s understanding of 

the potential for and the consequences of climate change. 

This chapter provides an overview of the many sources of 

uncertainty that arise because of gaps in scientific understanding—how the climate functions, how species will 

respond to climate change, and so forth—and because of 

inherent difficulties in forecasting human behavior—for 

instance, how population growth and energy use will 

change over time. (Other important complications, discussed in the following chapters, have to do with valuation: how to value impacts, how to balance values over 

time, and how to aggregate values across individuals.)

Uncertainty Affecting Costs 

The costs of policies to reduce greenhouse gas emissions 

will depend in large part on the magnitude of those emissions: the lower that emissions are expected to be in the 

absence of policy changes—that is, in the “baseline”—the 

fewer reductions will be needed to meet a given target 

and the lower the costs will be. The magnitude of emissions will depend on driving forces such as population, 

the demand for energy, and the reliance on fossil fuels 

(which, in turn, will depend on the prices of alternative 

energy sources). Uncertainty about those forces compounds into a very wide range of uncertainty for emissions projections that grows larger as the time horizon 

lengthens. 

Despite such uncertainty, many assessments simply incorporate point estimates of key variables and relationships to produce “best guesses” of how human activity 

will affect the global climate. For example, a pair of related models, the Dynamic Integrated model of Climate 

and the Economy (DICE-99) and the Regional Dynamic 

Integrated model of Climate and the Economy (RICE99), project that in the absence of policies to restrict 

them, annual carbon dioxide emissions will rise by 

roughly a factor of two between 2000 and 2100 to approximately 13 billion metric tons of carbon.1 Some 

point estimates are considerably higher: the best-known 

emissions scenario from the early 1990s, referred to as 

IS92a, projects carbon dioxide emissions of nearly 20 billion mtc in 2100.2

Although the best-guess approach is relatively manageable, it fails to provide a sense of how likely a best-guess 

estimate actually is, how wide the range of plausible outcomes around it may be, or how robust recommended 

policies are likely to be in the face of the full range of possible outcomes. Those insights require an alternative approach that explicitly acknowledges the underlying uncertainties. 

One alternative—the scenario approach—provides a 

sense of the rate of possible outcomes by analyzing several 

different scenarios, each based on a different set of plausible guesses.3 In one such exercise, the International Panel 

on Climate Change (IPCC) developed six different 

groups of emissions scenarios, with each group incorporating a different set of assumptions about the forces that

CHAPTER

1. For a description of those models, see William D. Nordhaus and 

Joseph Boyer, Warming the World: Economic Models of Global 

Warming (Cambridge, Mass.: MIT Press, 2000), p. 5. Many analysts have used the models to examine policy options for climate 

change.

2. K.P. Shine and others, “Radiative Forcing of Climate,” in J.T. 

Houghton, G.J. Jenkins, and J.J. Ephraums, eds., Climate Change: 

The IPCC Scientific Assessment (Cambridge, England: Cambridge 

University Press, 1990), pp. 41-68.

3. A specialized type of scenario analysis—bounding analysis—

involves taking the largest and smallest plausible estimates of values and parameters, which produces the most optimistic and most 

pessimistic plausible outcomes.
6 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

drive emissions.4 For 2100, projected annual emissions 

vary by roughly an order of magnitude, from less than

3 billion metric tons of carbon—less than half of today’s 

emissions—to 35 billion metric tons.5

By allowing policymakers to consider a range of possible 

cases, a scenario approach may help them develop robust 

policies that perform well under a range of outcomes. 

However, that approach does not provide a sense of how 

likely any particular scenario is or whether some scenarios 

are more likely than others. The experts who developed 

the IPCC scenarios felt that they lacked sufficient information to assess their relative probabilities.

Another approach—the Monte Carlo method—overcomes that limitation by incorporating probability distributions for model parameters. Researchers have developed estimates of the likelihood that parameters would 

take on different values and have used those estimates to 

undertake Monte Carlo analyses. That technique involves 

running a model many times with parameter values randomly drawn from their probability distributions.6 A 

large enough set of such simulations reveals the range of 

possible outcomes and the likelihood of those different 

outcomes. Applied to economic and climate models, the 

Monte Carlo method yields ranges of emissions that are 

similar to those of the IPCC but suggests that the highest 

and lowest emissions projections are relatively unlikely.7

The cost of reducing those projected emissions will depend not only on their magnitude but also on what (and 

when) alternative technologies become available, the cost 

of those technologies, and the potential for behavioral, 

institutional, cultural, and political barriers to impede the 

adoption of those technologies.8 Technologies that might 

be used to reduce emissions range from proven methods 

with reasonably well-known costs to others that are not 

likely to be developed for many years and whose costs can 

only be guessed. As an emissions-reduction target becomes more stringent, the number and cost of the technologies that may come into play increase—as does the 

uncertainty about that cost. Uncertainty about all of 

those factors feeds into uncertainty in the projection of 

mitigation costs.

The cost of reducing emissions also will depend on how 

efficient the policies are that motivate those reductions. 

In many cases, a given reduction in emissions can be obtained at a lower cost using economic incentives, which 

leave the specifics of where and how to reduce emissions 

to individuals and firms, rather than by command-andcontrol policies that specify where and how such reductions must take place. The feasibility of using economic 

incentives for controlling various greenhouse gases is discussed below.

Finally, the cost of reducing carbon emissions is appropriately measured not by the cost of emissions-reduction 

technologies alone—as is often done in engineering studies—but by the costs that society as a whole bears as a result of decreasing carbon emissions.9 Those costs include 

higher prices paid by consumers, lower short-run profits 

made by producers (both of which, in turn, depend on 

4. See Intergovernmental Panel on Climate Change, Emissions Scenarios (Cambridge, England: Cambridge University Press, 2000), 

p. 4, Box SPM-1. The scenarios differ in terms of the rapidity of 

economic growth in different regions as well as the rates at which 

different regions converge economically, their populations stabilize, various kinds of technology become available, and so forth.

5. Ibid., p. 7.

6. Ideally, those distributions are estimated using appropriate data 

and statistical tools, but if those are not available, researchers may 

develop distributions using expert opinion, rough guesses, or 

other techniques. Where appropriate, researchers may account for 

correlation among parameters. For example, analysis may suggest 

that slower population growth tends to be associated with more 

rapid productivity growth. In that case, very little weight would be 

placed on scenarios with rapid population and productivity 

growth. 

7. See, for example, Mort Webster and others, “Uncertainty Analysis 

of Climate Change and Policy Response,” Climatic Change, vol. 

61, no. 3 (December 2003), pp. 295-320. Analyses vary in the 

number of input parameters that are treated as uncertain: in some 

cases, researchers have characterized probability distributions for 

only a handful of variables and parameters; in other cases, they 

have introduced distributions for a relatively large number. An 

assessment may treat only growth rates and climate parameters as 

uncertain, while using point estimates for damages. Alternatively, 

it may treat growth rates and climate parameters as certain, but 

include a wide uncertainty range for damage estimates. No analyses have estimated the most appropriate policy given ranges of 

uncertainty for growth rates, emissions, climate responses, damage 

valuations, and mitigation costs.

8. See Intergovernmental Panel on Climate Change, Emissions Scenarios, p. 11.

9. For a discussion of the near-term costs of reducing emissions in 

the United States, see Mark Lasky, The Economic Costs of Reducing 

Emissions of Greenhouse Gases: A Survey of Economic Models, CBO 

Technical Paper No. 2003-03 (May 2003), available at www.cbo. 

gov/Tech.cfm.
CHAPTER TWO SCIENTIFIC AND ECONOMIC SOURCES OF UNCERTAINTY 7

the cost of technologies), and the reduction in consumers’ welfare that would result from changes in their purchasing patterns or behavior (for example, choosing to 

carpool).10 Even when the cost of emissions-reduction 

technologies is well-understood, the challenges involved 

in estimating the economic impacts of adopting those 

technologies contribute to uncertainty about aggregate 

costs.

Uncertainty Affecting Benefits 

The benefits of climate change policies—that is, the potential future damages avoided by reducing emissions today—are even more uncertain than the costs. Major scientific and economic uncertainties are involved in 

assessing the following factors:

B How greenhouse gas emissions will accumulate in the 

atmosphere and how the resulting change in concentrations will affect the average global temperature;

B How changes in global temperature will be distributed 

across seasons and regions and how those changes will 

affect other climate characteristics, such as rainfall, severity of storms, and sea level; and

B How any changes in regional climates will affect natural and human systems, such as agricultural crops, 

property, species, and human health.

Changes in Climate

Several scientific uncertainties complicate attempts to 

forecast the effects on global and regional climates of a 

change in atmospheric concentrations of greenhouse 

gases.11 Among the most important uncertainties are 

these:

B The role of the world’s oceans in absorbing heat and 

carbon dioxide from (and releasing them into) the atmosphere;

B The role of different types of aerosols, which in their 

pure form act as cooling agents but, when contaminated by soot, may also contribute to warming;

B The role of clouds, which have both warming and 

cooling effects, and which can have very different effects on projections of regional climate depending on 

how the clouds are modeled;

B The role of glaciers;

B The potential for unpredictability in the global 

weather system; and

B The potential for abrupt shifts in the global climate.

An Increase in the Average Global Temperature. Models 

based on the IPCC emissions scenarios have produced 

projections of increases in the average global temperature 

ranging from less than 1.5o

C to more than 5.5oC, depending on the model and the emissions scenario used as 

an input to the model—although without any estimate of 

the relative likelihoods of those outcomes.12 Using 

Monte Carlo simulations to characterize that uncertainty 

statistically, other researchers estimate that the increase in 

the mean global temperature between 1990 and 2100 

will most likely lie between 1o

C and roughly 4.9oC, with 

a mean increase of 2.4o

C, which is nearer to the low end

10. For a discussion of this point, see Paul R. Portney, “Applicability 

of Cost-Benefit Analysis to Climate Change,” in William D. Nordhaus, ed., Economics and Policy Issues in Climate Change (Washington, D.C.: Resources for the Future, 1998), pp. 121-122. In 

addition, by raising prices—and thus lowering real returns on capital and labor—carbon-reduction policies may exacerbate the discouraging effects that existing taxes on capital and labor have on 

economic activity—a connection known as the tax-interaction 

effect. A full accounting of the cost of carbon-reduction policies 

should take into account that potentially costly secondary effect. 

For a good survey of the literature on the tax-interaction effect, see 

A. Lans Bovenberg and Lawrence H. Goulder, “Environmental 

Taxation and Regulation,” in Alan Auerbach and Martin Feldstein, eds., Handbook of Public Economics, vol. 3 (Amsterdam: 

Elsevier/North-Holland, 2002), pp. 1471-1545. For a discussion 

of the tax-interaction effect in the context of a cap-and-trade policy for reducing carbon emissions, see Terry M. Dinan and Diane 

Lim Rogers, “Distributional Effects of Carbon Allowance Trading: How Government Decisions Determine Winners and Losers,” National Tax Journal, vol. 55, no. 2 (June 2002),

pp. 199-221.

11. For more details on this subject, see Intergovernmental Panel on 

Climate Change, Climate Change 2001: The Scientific Basis (Cambridge, England: Cambridge University Press, 2001). Box 1 (on p. 

24) and Box 3 (on p. 48) are particularly helpful. 

12. Ibid., p. 555. Average global temperature is used as a summary 

statistic to describe climate developments and is often used as an 

input in rough calculations of the aggregate impacts of climate 

change. However, impacts would be determined mainly by 

regional changes in seasonal temperatures, which are related to 

global changes but are subject to much greater uncertainty.
8 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

of their range than to the high end.13 (In contrast, the 

DICE-99 model, incorporating a set of best-guess parameters, projects a 2.0oC increase in the average global temperature between 2000 and 2100.14)

A Rise in Sea Level. Warming of the earth’s atmosphere 

and oceans would cause a gradual but uncertain rise in 

sea level, mainly from thermal expansion of the oceans 

but also from the melting of sea ice.15 For the IPCC scenarios discussed previously, predictions of the average rise 

in sea level globally between 1990 and 2100 range from 

as little as 9 centimeters (cm) to as much as 88 cm, with a 

mean value of 48 cm (or about a foot and a half). That is 

two to four times the increase estimated to have occurred 

over the 20th century.16 Researchers from the Massachusetts Institute of Technology (MIT) project a similar 

range, but with a mean value slightly under 40 cm.17

Changes in Precipitation and Extremes in Weather and 

Climate. Scientists expect a warmer world to be a wetter 

one: on average, rising temperatures will lead to more 

evaporation, humidity, and rainfall. The IPCC predicts 

increases in climate extremes as well, with higher daily 

minimum temperatures, more hot days, and heat waves 

“more likely” (but fewer frost days and cold days “likely”) 

over nearly all land areas.18 However, the relationship between increases in average temperatures and changes in 

extreme weather events is very uncertain. Warming could 

also change the frequency of thunderstorms and tornados, but the IPCC considered the data insufficient to 

make even general projections of trends for those weather 

events.

Regional Differences in Effects. Climate change would 

not be uniform: some regional changes in climate are expected to be much more pronounced than changes in the 

global average, and others less so. For example, the IPCC 

predicts that winter warming for all high-latitude northern regions will exceed the global mean by more than 40 

percent.19 In addition, a recent report on the impact of 

climate change on the Arctic concluded that “the Arctic is 

now experiencing some of the most rapid and severe climate change on Earth.”20 Furthermore, the IPCC predicts that changes in rainfall will vary greatly around the 

world, with rainfall increasing in high-latitude regions 

but decreasing in Australia, Central America, and southern Africa. Even the rise in sea level is expected to vary 

across regions, with nearly all models projecting a greaterthan-average rise in the Arctic Ocean and a less-thanaverage rise in the Southern Ocean.21

The Potential for Abrupt Changes. One area of growing 

concern is the potential for the gradual buildup of greenhouse gases to push the global climate system over a 

threshold, producing an abrupt change to a different, stable, and irreversible equilibrium.22 Scientists realize that 

13. See Webster and others, “Uncertainty Analysis of Climate Change 

and Policy Response.” The authors estimate that there is only a 

1-in-20 chance that the temperature increase will lie outside that 

range.

14. That calculation comes from the spreadsheet version of the model.

15. For a more complete discussion, see Intergovernmental Panel on 

Climate Change, Climate Change 2001: The Scientific Basis, p. 31, 

Box 2. Sea level is also affected by various factors not related to climate change. Those factors include changes in terrestrial water 

storage (from factors such as the extraction of groundwater and 

building of reservoirs); vertical land movements caused by natural 

geological processes, such as slow movements in the Earth’s mantle and tectonic displacements of the crust; and changes in atmospheric and ocean dynamics.

16. Ibid., p. 75.

17. See Webster and others, “Uncertainty Analysis of Climate Change 

and Policy Response.”

18. See Intergovernmental Panel on Climate Change, Climate Change 

2001: The Scientific Basis, p. 72.

19. In summer, warming in excess of 40 percent of the mean change 

globally is predicted for central and northern Asia. Ibid., pp. 67 

and 69.

20. See the statement of Robert W. Corell, Chair, Arctic Climate 

Impact Assessment, before the Senate Committee on Commerce, 

Science, and Transportation, November 16, 2004, p. 3, available 

at www.acia.uaf.edu/PDFs/Testimony.pdf. 

21. A higher rise in the Arctic sea level may result from an increase in 

freshwater, which reduces salinity and density and requires a rise 

in sea level to maintain pressure gradient at depth. See Intergovernmental Panel on Climate Change, Climate Change 2001: The 

Scientific Basis, pp. 75 and 673-674. 

22. The National Research Council defines abrupt climate change as 

occurring when the climate system is forced to cross some threshold, triggering a transition to a new state at a rate determined by 

the climate system itself and faster than the cause. Chaotic processes in the climate system may allow the cause of such an abrupt 

climate change to be undetectably small. Because crossing the 

threshold pushes the system into a new equilibrium, the system 

does not return to its original state, even when the pressure on it is 

relieved. See National Research Council, Abrupt Climate Change: 

Inevitable Surprises (Washington, D.C.: National Academy Press, 

2002), pp. 13-14; and R.B. Alley and others, “Abrupt Climate 

Change,” Science, vol. 299 (March 28, 2003), pp. 2005-2010.
CHAPTER TWO SCIENTIFIC AND ECONOMIC SOURCES OF UNCERTAINTY 9

abrupt changes have occurred in the past, especially during periods when external forces (such as changes in the 

Earth’s orbit) were already causing relatively rapid 

changes in the climate system. Both the degree and the 

rapidity of warming are thought to affect the potential for 

an abrupt change in the climate.23 An abrupt, unexpected shift could prove much more difficult for people 

and ecosystems to adapt to and, therefore, much more 

costly.

Scientists do not currently understand the processes that 

cause abrupt changes well enough to quantify the likelihood of such changes. (See Box 2-1 for a discussion of 

the scientific understanding of abrupt climate change.) 

The National Research Council has placed a high priority 

on obtaining rational estimates of the likelihood of 

abrupt shifts that may be of low probability but that 

could have very significant impacts.24

Damages to Natural and Human Systems from

Climate Change

To estimate the benefits of averting any changes in climate, analysts must determine how predicted patterns of 

change might affect natural and human systems—and, 

furthermore, how those effects would be mitigated by 

policies that reduced the magnitude and rate of climate 

change. Effects could include the initial transient impacts 

that would occur as the world first experienced the effects 

of a changing climate, as well as long-term impacts that 

would remain if temperature and greenhouse gas concentrations were stabilized and the world adjusted to the new 

equilibrium. For example, forests in some regions of the 

world could die off as temperatures rose, and new forests 

that had adapted to the new climate would take time to 

grow. In the long run, the effects of the change might be 

relatively modest, but the transition might be much more 

disruptive.

The degree of damage to both human and natural systems also would depend on the amount of adaptation 

that occurred, creating another source of uncertainty in 

predicting damages. For example, the damage from 

coastal flooding would be less severe if the threat of increased flooding was recognized and, as a result, development in coastal areas was limited. Similarly, the damage 

to agriculture would be less extensive if farmers raised different crops in response to the changed climate than if 

they continued to try to grow the same crops as they did 

in the past. One study estimated that without adaptation, 

global welfare losses in today’s agricultural food sector 

would be between $0.2 billion and $84 billion if carbon 

dioxide concentrations were suddenly doubled, but potential adaptation could reduce the upper bound on 

losses to $52 billion or even result in a gain of $10

billion.25

Despite the potential for adaptation in at least some regions, the IPCC projects a number of adverse effects on 

human systems:26

B A general reduction in potential crop yields in most 

tropical and subtropical regions from most projected 

temperature increases; 

B Decreased availability of water in many dry regions, 

particularly in the subtropics;27

B An increase in the number of people exposed to waterborne diseases such as cholera, diseases like malaria 

that are spread by arthropods (such as ticks and mosquitos), and an increase in heat-stress mortality;

B A widespread increase in the risk of flooding for many 

human settlements; and

B Increased energy demand for space cooling because of 

higher summer temperatures.

23. See Alley and others, “Abrupt Climate Change,” p. 2008.

24. See National Research Council, Abrupt Climate Change: Inevitable 

Surprises, p. 116.

25. See John Reilly, N. Hohmann, and S. Kane, “Climate Change 

and Agricultural Trade: Who Benefits, Who Loses?” Global Environmental Change, vol. 4, no. 1 (March 1994), pp. 24-36. 

26. See Intergovernmental Panel on Climate Change, Climate Change 

2001: Impacts, Adaptation, and Vulnerability (Cambridge, 

England: Cambridge University Press, 2001), p. 5.

27. Climate modelers at Princeton University also reached a similar 

conclusion. They modeled a quadrupling of atmospheric carbon 

dioxide above preindustrial levels. Their results found that freshwater would be significantly less available in regions that are 

already relatively dry. See Syukuro Manabe and others, “Century-Scale Change in Water Availability: CO2-Quadrupling 

Experiment,” Climatic Change, vol. 64, no. 1-2 (May 2004), pp. 

59-76. 
10 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

Box 2-1.

Scientific Understanding About Abrupt Climate Change

The current scientific emphasis on abrupt climate 

change is motivated by accumulating evidence of extreme and rapid climate changes in the past.1 An important example is the abrupt onset of a cold, dry, 

windy period—referred to as the Younger Dryas—

about 12,800 years ago, as the world was emerging 

from the previous Ice Age, and its equally abrupt end 

about 1,600 years later.2 A less dramatic, shorter, but 

equally abrupt cold snap occurred about 8,200 years 

ago. 

Scientists believe that those two episodes were probably 

triggered when large amounts of freshwater from 

melted glaciers broke through ice dams and flowed into 

the North Atlantic Ocean.3 Those flows decreased the 

salinity of the ocean’s surface water, slowing down a 

system of deep ocean circulation known as the thermohaline circulation, or THC.4 (The THC helps transfer 

a great deal of tropical heat to higher latitudes, affecting 

weather patterns throughout the world, and is largely 

responsible for the relatively mild climate of large parts 

of Europe.5) Historical changes in the THC are believed to have caused significant changes in climate 

around the globe.

Recently, some observers have expressed concern that 

global warming could trigger a disastrous slowdown of 

the THC, and they have argued that such a possibility 

may justify aggressive actions to limit greenhouse gas 

emissions immediately. However, although experts do 

not fully understand the causes of previous slowdowns 

of the THC, they generally consider such a development highly unlikely over the next century, in large 

part because there are no sufficiently large sources of 

freshwater near the North Atlantic Ocean that could be 

released suddenly.6

Scientists are also studying less dramatic but equally 

abrupt changes in climate that occurred during the Holocene period, the name given to the past 11,000 years 

of the Earth’s history. Such abrupt changes include 

rapid shifts in the magnitude and frequency of regional 

rainfall, hurricanes, and typhoons as well as global 

changes in temperature and precipitation patterns.7 Because they occurred in a climate much like today’s, 

such shifts may be particularly helpful in understanding what could unfold in the future. (Models used to 

simulate changes in climate are not yet sophisticated 

enough to project the likelihood of abrupt climate 

shifts in the future.) The National Research Council 

notes that “we know that droughts unprecedented in 

the last 150 years have occurred in the last 2,000 years 

and so could occur in the future, [but] we do not have 

the scientific understanding to predict them or to recognize their onset.”8 Although human actions did not 

cause those historical abrupt changes, scientists seek to 

understand how human-induced changes in climate 

could affect the likelihood of future abrupt changes. 

1. See R.B. Alley and others, “Abrupt Climate Change,” Science, vol. 299 (March 28, 2003), p. 2008.

2. See National Research Council, Abrupt Climate Change: 

Inevitable Surprises (Washington, D.C.: National Academy 

Press, 2002), p. 24.

3. Wallace S. Broecker, “Future Global Warming Scenarios,” 

Science, vol. 304 (April 16, 2004), p. 388.

4. Recent modeling indicates that the atmosphere-ocean system during the last glaciation was very close to a threshold, 

so relatively small increases in freshwater could have triggered abrupt changes in the THC. However, other factors, 

such as unknown periodic forcings and instabilities in ice 

sheets, also could have played a role. The basic question of 

the origin of the abrupt change in the THC is not resolved, 

but to date, models point to the key role of the freshwater 

balance in the Atlantic Ocean. See Peter U. Clark and others, “The Role of the Thermohaline Circulation in Abrupt 

Climate Change,” Nature, vol. 415, no. 6874 (February 21, 

2002), p. 866.

5. See National Research Council, Abrupt Climate Change,

p. 76.

6. The National Research Council concludes that predictions 

of dire near-term consequences are unfounded. In addition, 

one expert—the scientist who first discovered the link 

between the THC and the abrupt cooling—argues that the 

effect of global warming on sea ice formation in the North 

Atlantic could decrease the likelihood of a THC slowdown. 

See Broecker, “Future Global Warming Scenarios.” 

7. Changes in temperature and rainfall patterns around the 

globe can be triggered by El Niño or La Niña events, which 

are characterized by, respectively, unusually warm or cold 

temperatures in the Equatorial Pacific. See http://

www.pmel.noaa.gov/tao/elnino/la-nina-story.html. 

8. See National Research Council, Abrupt Climate Change,

p. 44.
CHAPTER TWO SCIENTIFIC AND ECONOMIC SOURCES OF UNCERTAINTY 11

However, the IPCC reports that climate change could 

have some beneficial impacts on human systems as 

well:28

B Higher potential crop yields in some regions at midlatitudes from increases in temperature of a few degrees Celsius or less; 

B A potential increase in the global timber supply from 

appropriately managed forests;

B Increased availability of water for populations in some 

relatively dry regions—for example, in parts of southeast Asia;

B Reduced winter mortality at mid- and high latitudes; 

and

B Reduced energy demand for space heating because of 

higher winter temperatures.

Finally, any change in climate could affect natural systems 

as well as human systems. Potential changes include:

B Changes in the distribution, population size, population density, and behavior of wildlife and plants;29

B Reduction in habitat for cold- and cool-water fishes 

and gains in habitat for warm-water fishes; and 

B Increases in erosion, accelerated loss of wetlands and 

mangroves, and seawater intrusion into freshwater 

sources as a result of increases in flooding. 

The increased risks of climate change appear to be particularly great for species that are already rare or endangered 

and for species whose habitat would probably disappear 

and who therefore cannot easily migrate. For example, 

some species are adapted to isolated habitats on top of 

mountains in the tropics; others species are endemic to 

the temperate climate of the southern tip of Africa. If the 

climate changes in those regions, mountaintop species 

cannot move farther uphill; nor can southern African species migrate farther south. 

The damaging effects of global warming on species would 

probably be exacerbated by human encroachment on natural habitats from population growth. While some species would be likely to disappear, the number or percentage of species in danger is extremely uncertain.

Differences in baseline climate conditions, changes in climate, initial vulnerability, and capacity for adaptation 

give rise to substantial differences in potential damages 

among regions. Predicting regional damages is further 

complicated by the fact that climate models do not yet 

yield reliable, detailed projections of regional changes. As 

a consequence, substantial uncertainty surrounds predictions of regional damages stemming from any particular 

degree or rate of climate change.

On the basis of analysts’ current understanding, it appears that in general, regions with the fewest resources—

in terms of wealth, infrastructure, technology, and education—would be likely to suffer the greatest losses, including damage to both human and natural systems. For example, the IPCC found that, to date, damages as a share 

of gross domestic product (GDP) from climate extremes 

have been substantially greater in developing countries 

than in developed countries.30 In part, that discrepancy 

results because the economies of some developing countries are relatively heavily dependent on climate-sensitive 

industries, such as agriculture or fisheries.31 In addition, 

developing countries typically have fewer resources to 

adapt to climate change and would therefore experience 

greater losses.32

28. See Intergovernmental Panel on Climate Change, Climate Change 

2001: Impacts, Adaptation, and Vulnerability, p. 6.

29. For example, a recent report on the Arctic predicted that changes 

in climate could have “devastating” consequences for polar bears. 

See statement of Robert W. Corell, November 16, 2004.

30. See Intergovernmental Panel on Climate Change, Climate Change 

2001: Impacts, Adaptation, and Vulnerability, p. 8

31. Ibid., p. 14

32. Ibid., p. 8.

3

Problems in Valuation

In addition to the numerous scientific and economic 

uncertainties involved in determining potential damages 

from climate change, it is very difficult to value such 

damages. The following discussion illustrates those challenges and controversies by describing the approach and 

results presented in a book by Yale University researchers 

William Nordhaus and Joseph Boyer.1 Although the 

problems discussed below arise in any attempt to measure 

the costs and benefits of climate policies, Nordhaus and 

Boyer’s work is particularly useful for illustrating them, 

in part because those researchers have made a comprehensive analysis of the potential economic impacts of climate change throughout the world, providing point estimates for many different types of economic impacts of 

climate change in many different regions.2

 Furthermore, 

they have incorporated their damage estimates in a relatively transparent, publicly available set of models. The 

availability of those models has allowed other analysts to 

understand how differences in assumptions influence policy recommendations. It also has allowed them to extend 

Nordhaus and Boyer’s framework to analyze how the recommended policies change when they account for uncertainty in the model’s parameter estimates. 3

Nordhaus and Boyer attempted to follow the conventional economic approach to valuing benefits, which is to 

determine what people are willing to pay for them—that 

is, the value they place on particular goods or services, as 

reflected in their willingness to forgo other goods and services to obtain them.4 Where goods and services are 

traded, their market prices provide some indication of 

what individuals would be willing to pay to avoid damCHAPTER

1. See William D. Nordhaus and Joseph Boyer, Warming the World: 

Economic Models of Global Warming (Cambridge, Mass.: MIT 

Press, 2000).

2. Most researchers, in contrast, have tended to focus on only parts 

of the problem. However, other comprehensive estimates are 

available in William R. Cline, The Economics of Global Warming 

(Washington, D.C.: Institute for International Economics, 1992); 

Samuel Fankhauser, Valuing Climate Change: The Economics of the 

Greenhouse (London: Earthscan, 1995); Richard S.J. Tol, “Estimates of the Damage Costs of Climate Change, Part I: Benchmark Estimates,” Environmental and Resource Economics, vol. 21, 

no. 1 (January 2002), pp. 47-73; and Richard S.J. Tol, “Estimates 

of the Damage Costs of Climate Change, Part II: Dynamic Estimates,” Environmental and Resource Economics, vol. 21, no. 2 

(February 2002), pp. 135-160.

3. For instance, Klaus Keller and others have extended the Dynamic 

Integrated model of Climate and the Economy to examine the 

policy implications of a possible collapse in the thermohaline circulation; see Klaus Keller and others, “Preserving the Ocean Circulation: Implications for Climate Policy,” Climatic Change, vol. 

47, no. 1-2 (October 2000), pp. 17-43. William Pizer has 

extended the model to explicitly incorporate probability distributions for various parameters; see William A. Pizer, “Optimal 

Choice of Policy Instrument and Stringency Under Uncertainty: 

The Case of Climate Change,” Resource and Energy Economics, 

vol. 21 (1999), pp. 255-287. Tim Roughgarden and Stephen 

Schneider have reformulated the model to reflect an alternate estimate of the potential damages from climate change; see Tim 

Roughgarden and Stephen H. Schneider, “Climate Change Policy: Quantifying Uncertainties for Damages and Optimal Carbon 

Taxes,” Energy Policy, vol. 27, no. 7 (July 1999), pp. 415-429. 

William Cline has adapted the model to examine different 

assumptions about economic growth, rates of warming, and preferences between present and future consumption; see William R. 

Cline, “Meeting the Challenge of Global Warming,” in Bjorn 

Lomborg, ed., Global Crises, Global Solutions (Cambridge, 

England: Cambridge University Press, 2004), available at 

www.copenhagenconsensus.com/Files/Filer/CC/Papers/

Climate_Change_300404.pdf. Richard Howarth has extended 

the model to consider the interests of several different overlapping 

generations; see Richard B. Howarth, “Climate Rights and Economic Modeling,” in Darwin C. Hall and Richard B. Howarth, 

eds., The Long-Term Economics of Climate Change: Beyond a Doubling of Greenhouse Gas Concentrations (Amsterdam: Elsevier Science, 2001), pp. 315-326.

4. Alternatively, benefits may be measured by people’s willingness to 

accept compensation for losing them. Willingness-to-accept measures are generally found to be higher than willingness-to-pay 

measures.
14 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

ages. In a flood zone, for instance, property prices indicate the value that could be lost from unexpected severe 

flooding. Similarly, in cases in which an environmental 

good is directly linked to the consumption of a marketed 

good, researchers can impute values for the environmental good by observing behavior in related markets. For example, they may estimate the value of clean air by measuring the variation in housing prices in areas with 

different levels of air quality.

Determining people’s willingness to pay for an environmental good is particularly difficult when it is not bought 

or sold in a market and when its consumption is not directly linked to a marketed good. In that case, it is difficult to determine whether and how people are willing to 

trade environmental goods for other goods. Researchers 

may ask people directly what they are willing to pay for 

an environmental good, such as preserving species and 

their habitats (for example, the polar bear or the Great 

Barrier Reef), but that approach has been controversial, 

with some analysts questioning whether individuals can 

provide meaningful answers about the values that they 

would attach to such goods.5

A further difficulty is that many of the nonmarket damages—for example, habitat destruction and species extinction—that could result from climate change are damages to public goods, which, once provided, are available 

to everyone for free. The total value of the damages to a 

public good typically is taken to be the sum of the valuations of those damages across all people—valuations that 

could, in principle, vary from very positive to very negative. Thus, even if individuals could provide meaningful 

willingness-to-pay values, an extremely large sample size 

would be required to accurately assess that measure of total value.

Lacking empirical evidence on the actual value that individuals place on preventing damage from global warming, Nordhaus and Boyer used proxy data, rules of 

thumb, and expert opinion to construct estimates of people’s willingness to pay to avoid damages in 13 regions of 

the world, for six major areas of impact: agriculture, sea 

levels, other market sectors, health, nonmarket amenities, 

and human settlements and ecosystems. Furthermore, 

they assessed the expected aggregate global damages from 

a catastrophic change in climate.6

 Importantly, the researchers implicitly assumed that people in each region 

place no value on damages in any other region.

The following discussion focuses on potential damages in 

three of those areas—agriculture, health, and human settlements and ecosystems—and on the estimate of expected catastrophic damages to highlight the challenges 

and controversies involved. A final section discusses the 

usefulness of such arbitrary and subjective valuations.

Agriculture: Data Gaps Remain 

Researchers have devoted much effort to estimating the 

potential impacts of climate change on the agricultural 

sector. Assessing the value of damages to agriculture is 

relatively straightforward because agricultural goods are 

sold in markets and their prices are easily determined. As 

a result, estimates of potential agricultural impacts are 

probably more reliable than those for any other sector.

Nevertheless, evaluating potential damages in the agricultural sector presents serious challenges. In addition to facing scientific uncertainty about projections of global and 

regional changes in climate, researchers face economic 

uncertainty in projecting many variables:

B How the economy will develop over time,

B How agricultural technologies might change, 

B How agriculture’s share of the economy might 

change, and

5. See Henry D. Jacoby, “Informing Climate Policy Given Incommensurable Benefits Estimates,” Global Environmental Change: 

Human and Policy Dimensions, vol. 14, no. 3 (October 2004),

pp. 287-297.

6. For a complete discussion of the assessment of willingness to pay 

in each of those six areas and of the estimate of catastrophic damages, see Nordhaus and Boyer, Warming the World, pp. 71-89.
CHAPTER THREE PROBLEMS IN VALUATION 15

B How farmers could adapt by adjusting their crop mix 

to a change in regional climate.7

The last consideration is particularly important. Although a change in climate might make it impossible to 

grow the same crops in a particular region, it might favor 

the cultivation of other crops, with little net economic 

impact.

A further complication is that present data limitations 

make it nearly impossible to estimate potential agricultural losses for many low-income and middle-income 

countries. For those countries, the researchers simply relied on estimates of the share of agricultural output lost 

for the “rest of the world” by other researchers and made 

assumptions about how agriculture’s share of income differed among countries on the basis of their level of 

wealth.8

Health: Questions About 

Valuing Lives Saved 

Nordhaus and Boyer’s damage estimates for the health 

sector illustrate the additional complications involved in 

estimating the value of damages to nonmarketed goods 

and services.9

 Finding no comprehensive studies of the 

potential health effects from climate change, they relied 

on estimates of the actual global incidence of diseases and 

years of life lost as a result of them, identifying a subset of 

those diseases that they believed to be climate-related. 

The authors derived a very rough estimate of how much 

more prevalent those diseases might become with a 2.5o

C 

increase in the average global temperature, and they used 

that estimate to determine how many additional years of 

life could be lost in each region.10

To assign an economic value to their calculation of potential years of life lost, Nordhaus and Boyer estimated 

that people’s willingness to pay to avoid an additional 

year of life lost would be twice the annual per capita income in the region. That controversial assumption implies that the value of life depends on the current distribution of income and thus is proportionately greater in a 

high-income country than in a low-income country. In 

other words, the lower a person’s income, the less he or 

she would be able and willing to pay to avoid a premature 

death.

Although that approach reflects the real income constraints that countries face, it is perceived by some people 

as inequitable. Using any other approach, however, 

would present other problems. People in poor countries 

with very low incomes cannot, and do not, spend a great 

deal to reduce their risk of death. A climate policy that 

valued their years of life as highly as those of people in 

high-income countries would create a disparity between 

the value placed on potentially extending lives by means 

of climate change policies and the value placed on doing 

so via other policies—such as providing clean water or 

basic health care—that are funded by limited local resources. It also would place a disproportionate value on 

risk reduction from climate change policies and the value 

attached to other public goods and services that residents 

in poor countries might wish to have resources spent on, 

such as the building of roads or the provision of electricity. (The reverse problem would arise if a policy was 

adopted that valued years of life of high-income people as 

little as those of people in low-income countries.) In sum, 

7. On the basis of available data, Nordhaus and Boyer estimated that 

in 1995, the negative impact on U.S. agriculture of a 2.5oC 

increase in the average global temperature would have been about 

$4 billion—or about 0.065 percent of total output—in the U.S. 

economy. They concluded that the United States would be willing to pay 0.065 percent of its total output to avoid the damage to 

agriculture that a 2.5o

C increase in the average global temperature 

would be expected to bring about in today’s economy. They made 

adjustments to reflect the expected timing of the warming, which 

they assumed would occur in 2100, and the changes in the economy that they projected would have taken place by then.

8. See Nordhaus and Boyer, Warming the World, pp. 74-75. Countries for which information is extremely poor include those in 

Africa, the group of countries classified as lower middle income in 

the Regional Dynamic Integrated model of Climate and the 

Economy (for example, Thailand, Mexico, and Peru), and those 

classified as low income (for example, Indonesia, Bangladesh, and 

Bolivia).

9. Ibid., pp. 78-82.

10. Nordhaus and Boyer used three alternative methods to provide a 

rough estimate of the increase in those diseases that might occur 

with a 2.5o

C increase in the average global temperature. Method 

A assumes that half of the years of life lost (YLLs) because of 

climate-related diseases estimated by the researchers for the 1990-

2020 period will be lost as a result of a 2.5oC warming. Method B 

adjusts the change in YLLs for each region to approximate the difference among subregions that is related to climate. Method C 

uses econometrics to determine the relationship between differences in climate-related YLLs in various regions and differences in 

climate. The authors take the average of those three methods to 

estimate the additional years of life lost from climate change in 

each of the regions identified in their model.
16 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

setting priorities among alternative policies becomes very 

difficult if some policies have willingness-to-pay benefit 

estimates that reflect a country’s actual income constraint 

and others do not.11

Human Settlements and Ecosystems: 

Valuing Damages to Nonmarketed 

Goods and Services

Nordhaus and Boyer highlight the importance and difficulty of evaluating the effects—particularly the nonmarket damages—that climate change might have on human 

settlements (for example, losses due to water intrusion in 

low-lying cities or countries, such as Venice or Bangladesh) and on natural systems (for example, the loss of 

species that have limited ranges or the destruction of 

complex ecosystems). Faced with no meaningful valuations, the authors developed rough estimates of the capital value of climate-sensitive human settlements and natural ecosystems in each region—ranging from 5 percent 

to 25 percent of regional output—and assumed that each 

region would be willing to pay roughly 1 percent of that 

capital value annually to prevent the damage that it might 

incur as a result of a 2.5o

C increase in the average global 

temperature. For the United States, they estimated that 

the capital value of climate-sensitive human and natural 

settlements was 10 percent of national output, or $500 

billion, and that Americans would be willing to pay $5 

billion per year to protect that value.12

Catastrophic Damages: Expert

Opinions Vary Widely

To provide a rough estimate of the potential for catastrophic damages from climate change—as well as their 

possible magnitude—Nordhaus surveyed a group of natural scientists, environmental economists, and other social scientists about their expert assessments of the probability that a temperature increase of either 3°C or 6°C by 

2095 would lead to catastrophic damages, which he defined as a 25 percent reduction in global world product 

(GWP).13

Nordhaus used the survey responses to develop a set of 

“certainty-equivalent” damages, which convert low-probability catastrophic losses into certain losses of lower 

value. Nordhaus assumed risk neutrality in those conversions; under that assumption, a 1 percent chance of losing $100 is equivalent to a certain loss of $1. (Under an 

assumption of risk aversion, it would be equivalent to 

more than $1.) Using that approach, Nordhaus converted the experts’ varying assessments of the likelihood 

of a 25 percent loss of GWP into a certain loss of 0.36 

percent of GWP for a warming of 2.5°C and 2.04 percent of GWP for a 6°C warming.14

Nordhaus also asked the experts to provide their best 

guesses of the magnitude of the damages that might result 

from a 3°C or 6°C increase in average global temperature 

by 2095. The experts’ estimates ranged from 0.3 percent 

to 21 percent of GWP for the value of damages from a 

3°C increase and from 0.8 percent to 62 percent of GWP 

for a 6°C increase.15 The experts also provided estimates 

11. For an extensive discussion, see Paul R. Portney, “Applicability of 

Cost-Benefit Analysis to Climate Change,” in William D. Nordhaus, ed., Economics and Policy Issues in Climate Change (Washington, D.C.: Resources for the Future, 1998), pp. 122-123. 

Portney presents the argument somewhat differently, stating that 

using a global average value for all lives saved would lead developing countries to concentrate all of their attention on programs 

that saved lives in the short term and to pay little or no attention 

to climate change policies. However, the real problem stems not 

from the time frame of the policies but from evaluating some policies with willingness-to-pay estimates that reflect a domestic budget constraint and evaluating others using a global budget 

constraint.

12. Nordhaus and Boyer assumed that this estimate of willingness to 

pay would be sensitive to changes in income. As countries’ 

incomes grew, their willingness to pay to prevent damages to 

human settlements and natural ecosystems would increase as well. 

For additional detail, see Nordhaus and Boyer, Warming the 

World, pp. 85-87.

13. See William D. Nordhaus, “Expert Opinion on Climate 

Change,” American Scientist, vol. 82, no. 1 (January-February 

1994), pp. 45-51.

14. See Nordhaus and Boyer, Warming the World, pp. 87-89. 

Nordhaus adjusted the certainty-equivalent calculations to 

account for information about the potential shutdown of the 

Atlantic Ocean’s thermohaline circulation that became available 

after his survey was done (see Box 2-1). He assumed that the 

probability of a catastrophic loss with a 2.5°C temperature 

increase was double the experts’ estimated probabilities for a 3°C 

warming and that the probability associated with a 6°C warming 

was double the experts’ estimates.

15. Best guesses are defined as 50 percentile estimates—the point at 

which the expert surveyed believed that there was a 50 percent 

chance that actual damages could lie either above or below that 

level. For an analysis of those survey results, see Roughgarden and 

Schneider, “Climate Change Policy: Quantifying Uncertainties 

for Damages and Optimal Carbon Taxes.”
CHAPTER THREE PROBLEMS IN VALUATION 17

of the probability ranges around those best guesses: at 

least one expert felt that there was a 10 percent chance 

that the damage from a 3°C rise in average global temperature could exceed 31 percent of GWP; at the other extreme, at least one expert thought that there was only a 

10 percent chance that the damage resulting from a 3°C 

rise could exceed 0.6 percent of GWP.

The experts’ damage estimates seem to depend on their 

particular area of knowledge: natural scientists tended to 

predict larger losses than social scientists did, with the 

bulk of the expected losses consisting of damages to nonmarketed goods and services rather than the types of 

goods and services that are measured in standard national 

economic accounts. Thus, much of the variance in damage estimates appears to come from divergent views about 

either the extent of damage to the natural world, the 

value of that damage, or both. 

Other researchers have applied the responses from 

Nordhaus’s survey to develop policy recommendations 

that reflect the uncertainty associated with potential damages. Those analyses are discussed in Chapter 5. 

The Usefulness of Subjective Estimates 

The lack of meaningful data on the value of many potential damages from climate change leads researchers to use 

arbitrary rules of thumb to determine values. In at least 

some cases, the rules of thumb and the predicted damages 

are highly speculative and probably inaccurate measures 

that provide only very rough guidance at best in the development of policy. However, such efforts may be helpful in providing some sense of the likely magnitude of 

damages and, thus, some general sense about the desirability of alternative policies. As discussed in Chapter 5, 

clarifying the process by which those values are determined (and describing how the use of alternative values 

affects policy prescriptions) may be as useful in informing 

policymakers as the estimates themselves.

4

Problems in Aggregation

The evaluation of climate policy is further complicated by the fact that benefits and costs would occur at 

widely different times and could occur in different parts 

of the world. For both of those reasons, climate change—

and policies to avert it—would probably yield gains for 

some regions and countries and losses for others. That 

fact raises complicated problems about how to aggregate 

and balance gains and losses over time and across

locations.

Problems in Comparing Present Costs 

and Future Damages 

The damages associated with climate change are expected 

to occur many years from now—with most researchers 

estimating that the bulk of damages from current emissions may occur a century or more in the future. In contrast, the cost of policies enacted to avoid damages would 

be incurred in the near term. As a consequence, analysts 

and policymakers must consider trade-offs between the 

costs that climate policies impose on people today and 

the benefits that they are projected to yield for future 

generations. Although many analysts adopt the conventional economic approach to evaluating long-term benefits, others argue for an alternative approach.

The Conventional Approach to Discounting

The conventional “opportunity-cost” approach to comparing the current costs and the future benefits of policies 

is to convert future values to present values using market 

interest rates. The approach is based on the fact that resources devoted to a policy also could be invested at current market interest rates and allowed to compound over 

time, yielding significantly more income in the future. 

Following that logic, the conventional approach is to 

weigh policy costs against the investment opportunities 

forgone by undertaking the policy.

Suppose, for example, that current generations were considering a policy that they expected would yield $1,000 

worth of climate benefits to people living a century from 

now. An alternative would be to provide those future 

generations with $1,000 worth of inflation-adjusted income. The amount of income to set aside today for that 

purpose depends on the expected rate of return on investments: if the rate was expected to be 3 percent, the current generation would have to invest about $52 to make 

sure that $1,000 was available a century hence. In other 

words, at a 3 percent interest (or discount) rate, the 

present value of $1,000 one century from now is $52 today. Because the present cost of providing $1,000 to future generations through a conventional investment is 

$52, analysts conclude that at a 3 percent discount rate, 

$52 is the present value of $1,000 of any sort of benefit a 

century from now.

If the rate was expected to be lower—say, 1 percent—the 

current generation would have to put aside more income 

to yield $1,000 in a century—nearly $370. At a higher 

rate—say, 5 percent—the current generation could put 

aside much less income—about $8. The farther in the future the income is needed, the smaller the initial investment can be, because it has longer to compound and 

grow: the present value of $1,000 two centuries from 

now is about $137 at a 1 percent rate of return but less 

than $3 at a 3 percent rate and only six cents at a 5 percent rate (see Figure 4-1). Although present-value calculations may seem to dramatically devalue future damages 

from climate change, they simply reflect the fact that alternative long-term investments can and do yield positive 

rates of return.

A related way of thinking about the problem of comparing present and future values—one that leads to the same 

conclusion—is in terms of compensation: if current generations are producing emissions that will impose damCHAPTER
20 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

Figure 4-1.

The Present Discounted Value

of $1,000

(Dollars)

Source: Congressional Budget Office.

ages on future generations, they may set aside income today to compensate future generations for the damages 

they are expected to incur. To provide compensation, 

people can invest income today and allow it to grow, 

yielding the appropriate amount of compensating income 

in the future.

The same logic can be applied to setting the level of a 

price on greenhouse gas emissions. An appropriately set 

tax on carbon would lead current generations to eliminate those emissions that were more costly to compensate 

future generations for than to forgo, but to continue 

those emissions that would cost more for current generations to eliminate than the discounted damages that they 

caused and the compensation that they could, in principle, pay to future generations.

According to the opportunity-cost approach, then, the 

present value of all future benefits, including climate 

damages, depends on the market rate of interest. However, analysts encounter a serious problem in implementing that approach for very-long-term policies: there are 

no financial markets in which to make centuries-long investments and from which to determine very-long-term 

interest rates. Some observers argue that the absence of 

such rates calls the opportunity-cost approach into question, but most analysts use rates on long-term government bonds as a rough proxy for such very-long-term 

rates of return.1

To derive a discount rate for present-value calculations 

from such market rates, analysts must adjust the rates to 

eliminate compensation for expected inflation and various forms of risk.2

 Furthermore, adjusting for the uncertainty about rates of return on long-term bonds yields an 

implicit rate of return that is lower than the average 

rate—and one that declines the farther in the future the 

values are converted to present ones. That adjustment 

can considerably increase the weight attached to longterm benefits, compared with simply applying a constant 

average discount rate based on the returns on long-term 

bonds. According to recent research, that adjustment increases the present value of one estimate of future climate-related damages over the next four centuries by 7 

percent to 95 percent, depending on the initial interest 

rate and the assumed reasons for the variability.3

10 50 100 150 200

0

100

200

300

400

500

600

700

800

900

1,000

At 1 Percent

At 3 Percent

At 5 Percent

0

Years in the Future

1. For example, funds continuously reinvested in 10-year U.S. Treasury bonds from 1789 to the present would have earned an average inflation-adjusted return of slightly more than 3 percent a 

year.

2. Interest rates typically reflect the riskiness of the relevant investment: the riskier an investment, the less likely it will be to pay a 

return, and the greater the rate of return that investors will 

demand as a condition for accepting the risk of failure. Similarly, 

interest rates typically include an upward adjustment that reflects 

expectations about the risk of future inflation. Adjusting for risk 

does not imply that future damages should be considered certain, 

but rather that the comparison of present and future values should 

be distinguished from calculations of risk—an issue discussed in 

the next section.

3. See Richard G. Newell and William A. Pizer, Discounting the Benefits of Climate Change Mitigation: How Much Do Uncertain Rates 

Increase Valuations? (Arlington, Va.: Pew Center on Global Climate Change, December 2001). When the future real interest rate 

is uncertain, the value of a future benefit, discounted by that 

interest rate, could be high or low; and the expected value of that 

future benefit today is the average of the possible outcomes. 

Because interest rates compound over time, the difference 

between higher and lower discounted values of a given benefit gets 

larger the farther out in the future the benefit occurs. The net 

effect of that divergence between higher and lower discounted values is to generate an expected benefit that is much closer to the 

value implied by the low rate than the one implied by the high 

rate.
CHAPTER FOUR PROBLEMS IN AGGREGATION 21

The opportunity-cost approach thus allows analysts to 

convert future values into present ones in a way that is 

consistent with the ability to convert present income into 

future income and that can be adjusted for many kinds of 

uncertainty. If analysts believe that past variability in such 

market rates does not fully reflect the potential for variability in future returns—perhaps because of the potential for disasters even greater than those that have occurred during the period for which long-term 

government bond rates exist—they can assume a greater 

degree of future variability when calculating the implicit 

discount rate, yielding a lower set of rates.

The Prescriptive Approach to Discounting

Despite the flexibility of the conventional approach and 

its general acceptance by economic analysts, some analysts have argued for a “prescriptive” approach that uses 

lower discount rates to convert future values into present 

ones.4 The main argument usually cited for doing so is 

that society does not save and invest sufficiently—in 

terms of physical capital, technology, or a beneficial climate—to provide for future generations. Market distortions are one source of the problem, particularly taxes on 

capital that drive a wedge between pretax and after-tax returns on investments. Some analysts argue further that 

pure impatience or “time preference” leads people to 

undervalue the future in their personal financial behavior.

According to the prescriptive approach, taxes and impatience both may induce people to save and invest less 

than they would otherwise, leaving pretax interest rates 

higher than they would be in an ideal world in which the 

tax system was not so distortionary and people were not 

so impatient. Proponents of that view argue that public 

policies that address long-term problems should offset the 

effects of market distortions and impatience by evaluating 

projected future damages using discount rates that are 

lower than market rates.5

The effect of the prescriptive approach is to place a higher 

value on climate-related damages (and other damages 

evaluated using lower rates) than is placed on comparable 

future benefits that are evaluated using market rates. To 

illustrate that point, consider the example presented earlier. If climate-related damages are expected to be $1,000 

a century from now, applying a lower discount rate—say, 

1 percent instead of a 3 percent market rate—increases 

the present value of those damages from $52 to $370 and 

thus leads to a recommendation to undertake more mitigation today. However, that $370 could be invested today and could be expected to yield much more than 

$1,000 in income in a century, even at a very uncertain 

market interest rate—so long as the rate ranged around 

the long-run historical average of about 3 percent. Therefore, as long as most investments are undertaken at market rates, the recommendation to apply a lower discount 

rate has the effect of valuing future climate damages more 

highly than comparable benefits from most other investments.6

The only way to compare all future benefits on an equal 

basis is to evaluate them using a similar set of discount 

rates. Thus, the only way for policies evaluated at lowerthan-market rates to be compared on an equal basis with 

4. The distinction between the prescriptive and conventional (or 

“descriptive”) approach is discussed in K.J. Arrow and others, 

“Intertemporal Equity, Discounting, and Economic Efficiency,” 

in James P. Bruce, Hoesung Lee, and Erik F. Haites, eds., Climate 

Change 1995: Economic and Social Dimensions of Climate Change 

(Cambridge, England: Cambridge University Press, 1996), pp. 

125-144. A particularly well-known version of the prescriptive 

argument is made by William R. Cline, “Discounting for the Very 

Long Term,” in Paul R. Portney and John P. Weyant, eds., Discounting and Intergenerational Equity (Washington, D.C.: 

Resources for the Future, 1999), pp. 131-140.

5. Under the prescriptive approach, future generations’ well-being 

may be discounted to some extent—for instance, because of risk 

aversion or because they are likely to have much greater wealth 

than current generations to offset a climate-related loss of wellbeing—but not by as much as is implied by market interest rates. 

Interestingly, some research also indicates that people may 

approve of public policies that place more emphasis on benefits in 

the distant future than they do in their own personal saving and 

investment behavior. For further discussion, see Maureen L. 

Cropper, Sema K. Aydede, and Paul R. Portney, “Preferences for 

Life Saving Programs: How the Public Discounts Time and Age,” 

Journal of Risk and Uncertainty, vol. 8, no. 3 (1994), pp. 243-265.

6. Skeptics of the opportunity-cost approach sometimes object that 

the proposed alternative investment could not serve as adequate 

compensation for climate-related damages. That, too, is another 

way of saying that the climate-related damages should be given 

not just a higher present value but also a higher future value. 

Another argument presented for using a lower discount rate for 

environmental benefits such as averting damages from climate 

change is that future generations are likely to enjoy higher 

income, so they may value those benefits more highly than current 

generations do and would be willing to pay more for them. That 

argument is also, in effect, a way of placing a higher future value 

on future damages. (William Nordhaus and Joseph Boyer, taking 

that consideration into account, incorporate the effect of rising 

income on willingness to pay in their valuation of climate-related 

damages; thus, the argument would not apply to their estimates.)
22 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

other policies would be for society as a whole to increase 

its investment to the point at which the rate of return on 

investments was driven down to the same lower rate. At 

that point, the opportunity-cost approach and the prescriptive approach would yield the same evaluation for 

any proposed policy or investment. Because that is not 

the case in reality, the prescriptive approach drives a 

wedge between the present value of typical market investments and that of policies evaluated at below-market 

rates.

All of the difficulties described above—uncertainty about 

the future rate of return, the valuation of future damages, 

market distortions, and concerns about how to value different types of benefits and the welfare of future generations—complicate the balancing of present and future 

costs and benefits. The discount rate chosen can dramatically affect conclusions about the appropriate stringency 

of policy today. In one application of the Dynamic Integrated model of Climate and the Economy, for instance, 

the present value of future climate-related damages, at a 4 

percent discount rate, is about $8 per ton of carbon emitted but nearly $29 per ton at a 2 percent rate.7

Problems in Determining the

Appropriate Level of Risk Reduction

Given the many uncertainties associated with climate 

change, the choice of policy stringency is similar to a 

choice about insurance coverage: higher emissions prices 

impose higher costs on households and businesses today 

but provide more protection against unpleasant surprises 

from damages in the future. Yet another potential source 

of controversy, therefore, is that people vary in their aversion to risk: although a person who views risk neutrally 

may value a 1 percent probability of sustaining $100,000 

in damage at $1,000—and therefore would be willing to 

pay up to $1,000 to avoid it—another person who is very 

averse to risk may be willing to pay considerably more.

Differences in risk aversion can thus lead people to differ 

in the level of policy stringency they prefer, even if they 

agree on all the other scientific, economic, and valuation 

uncertainties. Because of the formidable difficulties in 

evaluating uncertain costs and benefits assuming risk 

aversion, however, very little research has been done in 

that area. The cost-benefit assessments discussed in previous chapters all assume risk neutrality and therefore provide little guidance to policymakers on how to evaluate 

potential costs and benefits under different risk preferences.

Problems in Aggregating Costs and 

Benefits Across Regions

Just as problems arise in balancing present and future 

costs and benefits, complications arise in aggregating 

costs and benefits across individuals, regions, and countries. As discussed in Chapter 3, one source of controversy is that estimates of benefits reflect the affected people’s willingness to pay to avoid potential damages—and 

therefore are linked to their income. Thus, equivalent 

damages receive greater weight if they occur in high-income countries than in low-income ones.

A second source of controversy, discussed in Chapter 2, is 

that the effects of climate change are likely to be very unevenly distributed: according to one estimate, for example, India would experience an annual loss equal to about 

5 percent of its total output if the average global temperature rose by 2.5° Celsius, whereas Russia would benefit 

by an amount equal to about 0.65 percent of its total output.8 An aggregation of potential damages would conflate 

India’s losses and Russia’s gains, yielding a single value 

for net losses, regardless of whether Russia used any of its 

gains to compensate India for its losses.

A third source of controversy is that countries that are expected to bear a large share of the cost of mitigation policies, such as the United States, may receive only a small 

share of the benefits. At the same time, developing countries, which may bear a relatively small share of the mitigation costs, are expected to receive a large share of the 

benefits. The assumption implicit in analyses that maximize global net benefits is that countries that benefit 

could theoretically compensate those that bear the cost—

making all countries better off—yet few observers expect 

such compensation to occur.

Finally, benefits and costs can be aggregated only if they 

can be translated into common units—for instance, a 

monetary value such as constant dollars. However, as dis7. Newell and Pizer, Discounting the Benefits of Climate Change Mitigation.

8. See William D. Nordhaus and Joseph Boyer, Warming the World: 

Economic Models of Global Warming (Cambridge, Mass.: MIT 

Press, 2000), p. 91.
CHAPTER FOUR PROBLEMS IN AGGREGATION 23

cussed in Chapter 3, assigning monetary values to 

avoided damages for nonmarketed goods and services is 

extremely difficult. Furthermore, many of those damages 

are to public goods, and their valuation requires some 

method of aggregating people’s different evaluations of 

the same phenomena.

Those complications in aggregating benefits are not the 

same as scientific uncertainties about the radiative forcing 

value for different greenhouse gases or the response of 

species to changes in habitat. However, they are important factors contributing to differences of opinion about 

how aggressively to pursue any climate policy.

5

Policy Implications

Large uncertainties are inherent in estimating the 

costs and benefits of any policy to address the possible 

risks associated with climate change; yet the stakes in 

making policy choices are high. Although reducing 

greenhouse gas emissions could impose significant costs 

on nations around the globe, some experts believe that 

those emissions, if left unrestrained, could lead to costly 

damages. 

Climate policy will probably involve a sequence of decisions based on the gradual accumulation of information 

and the resolution of uncertainties.1 Waiting until all uncertainties are resolved and then implementing a single 

long-term “best” solution may not be a pragmatic approach, for three reasons. First, uncertainty in the assessment of climate policy can be decreased but not eliminated. Second, greenhouse gases that are emitted today 

will contribute to a gradual long-term warming, the full 

effects of which will become apparent only over many decades. Third, reducing the global economy’s reliance on 

fossil energy would be a slow process.

Actions taken over the next decade are likely to have relatively little impact on the extent of any climate change a 

century from now, since long-term climate change will 

depend on the path of the global economy and policies 

pursued over the whole century. However, current actions might lay the groundwork for potentially large reductions in emissions in the future, should research indicate the need for them. That possibility suggests a flexible 

strategy that could be easily modified over time and that 

could include several elements:

B Research to resolve uncertainties about potential damage and to develop technologies that might cut the 

cost of reducing emissions or be helpful in adapting to 

a warmer climate;

B Economic incentives to encourage inexpensive reductions in emissions today, with the expectation that 

more-extensive reductions may be merited in the future; and 

B Policies that would facilitate adaptation, thus lowering 

the cost of any warming that did occur. 

Determining the appropriate magnitude of each of those 

strategies or the balance among them is beyond the scope 

of this paper. Instead, the paper examines implications 

about policy formation that can be drawn from an understanding of the uncertainties described in previous chapters, focusing on mitigation—the area for which existing 

research offers the most useful insights. 

Research and Development 

Research would be an essential part of a comprehensive 

approach to addressing climate change. Research may 

even yield economic benefits if it helps resolve uncertainty about elements of the problem, thus reducing the 

likelihood of taking unnecessarily expensive measures or 

not taking actions that would have proved beneficial. 

(However, as it has in the past, research may also uncover 

new elements of the problem whose importance had previously gone unrecognized. In that respect, greater 

knowledge may not necessarily reduce the overall range 

of uncertainty about the risks of climate change.)

CHAPTER

1. That sequence is sometimes referred to as an “act, then learn, then 

act” process. A seminal discussion of that approach is provided in 

A.S. Manne and R.G. Richels, Buying Greenhouse Insurance: The 

Economic Costs of CO2 Emission Limits (Cambridge, Mass.: MIT 

Press, 1992). Another useful discussion is found in L. James Valverde A. Jr., Henry D. Jacoby, and Gordon M. Kaufman, 

“Sequential Climate Decisions Under Uncertainty: An Integrated 

Framework,” Journal of Environmental Modeling and Assessment, 

vol. 4, no. 2-3 (1999), pp. 87-101. 
26 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

One team of analysts has estimated that research to reduce uncertainty about those risks is likely to have the 

biggest payoff if it is directed at improving knowledge 

about the value of potential damages (for example, the 

monetary value of health damages or reductions in species) and the cost of reducing emissions.2 In contrast, 

they found a somewhat lower payoff from obtaining a 

better understanding of the climate system or of the future growth of emissions. An important limitation of that 

study, however, is that it measures only the expected benefits of research and not what the required research would 

cost.

Research could also play a key role in developing technologies to reduce the cost of making more dramatic emissions reductions in the future, should they be warranted, 

or to reduce the cost of adapting to a warmer climate, 

should it become necessary. The availability of such technologies would make the transition away from reliance 

on fossil energy (or the sequestration of fossil-fuel-related 

emissions) or the adaptation to a warmer climate less expensive than it would otherwise have been. If potential 

damages do not indicate a need for those technologies, 

the development cost would represent insurance against a 

risk that did not ultimately materialize.

Mitigation 

Policymakers may choose to limit emissions by using a 

variety of command-and-control strategies—those that 

specify firm-specific emissions reductions or technology 

requirements—or by using policies that provide broad 

economic incentives to reduce emissions.3

 When economic incentives can be successfully applied, they are 

generally less costly than command-and-control approaches. Command-and-control policies that dictate explicit methods for reducing emissions are unlikely to prescribe the best technology in every application, and they 

may easily overlook cost-effective solutions. Likewise, 

government regulators are unlikely to know which firms 

can cut emissions most cheaply. For that reason, experts 

believe that broad-based economic incentives, which provide firms with much more leeway in where and how to 

reduce emissions, are likely to result in more cost-effective emissions reductions than are command-and-control 

regulations. 

Experts generally agree that economic incentives could be 

successfully applied to regulate carbon dioxide emissions 

from the burning of fossil fuels, nitrous oxide emissions 

from industrial sources, and methane emissions from 

landfills. Those types of emissions are relatively easy to 

measure and monitor, making the administrative cost of 

implementing and enforcing an incentive-based policy 

relatively low.4 In contrast, greenhouse gas emissions that 

come from agricultural and forestry activities are much 

more difficult to monitor, complicating the application 

of incentive-based policies.

When monitoring and enforcement considerations allow 

the use of economic incentives, policymakers must decide 

between two general forms—incentives that limit the 

overall level of emissions (so-called quantity instruments) 

or incentives that reduce emissions by raising their price 

(so-called price instruments). Cap-and-trade programs 

offer a way to set an aggregate limit on the level of greenhouse gas emissions while relying on economic incentives 

to determine where and how those emissions reductions 

take place. Under such a program, policymakers would 

establish an overall cap on emissions but allow regulated 

firms to trade rights (or allowances) to those emissions. 

Trading would allow firms that could reduce their emissions most cheaply to do so in order to sell some of their 

allowances to firms that faced higher costs to reduce their 

emissions. Furthermore, the price increases that resulted 

from the cap would encourage households to consume 

less fossil fuel, thus leading to lower carbon emissions. 

That approach would achieve the emissions target at the 

2. See William Nordhaus and David Popp, “What Is the Value of 

Scientific Knowledge? An Application to Global Warming Using 

the PRICE Model,” Energy Journal, vol. 18, no. 1 (1997),

pp. 1-45.

3. Command-and-control policies can include policies that set specific emissions limits (or standards) that firms must make but do 

not specify how those limits must be met. For example, corporate 

average fuel economy standards specify an average fuel economy 

standard that each auto manufacturer’s fleet must meet but do not 

specify how manufacturers must meet that standard. Although 

such policies provide manufacturers with some degree of flexibility, they provide much less flexibility than cap-and-trade programs. 

4. Fossil fuels are produced by a relatively small number of firms, 

and the carbon content of those fuels is well known; the other 

emissions also come from a relatively small number of sources 

that, for the most part, are already monitored for other types of 

pollution emissions. The removal and sequestration of emissions 

from large sources—such as electric power plants and industrial 

boilers—would also be relatively easy to monitor and measure.
CHAPTER FIVE POLICY IMPLICATIONS 27

lowest possible cost, but it would not necessarily balance 

that cost against the benefits achieved by the target.

Taxing greenhouse gas emissions, in contrast, would 

boost the cost of those emissions, thereby encouraging 

households and firms to cut emissions as long as the cost 

of doing so was below the tax. (Households and firms 

could reduce emissions by using less fossil fuel or by relying on fossil fuels yielding relatively few emissions.) That 

price-based approach would establish an upper bound on 

the cost of individual emissions reductions—the level of 

the tax—but would not ensure that any particular emissions target was met. Such an approach would balance 

benefits and costs only if the tax was set equal to the benefit resulting from incremental reductions in emissions.

A cap-and-trade program with a “safety valve” combines 

an aggregate cap on total emissions with a ceiling on the 

allowance price. Under that hybrid approach, policymakers would establish an overall cap and allow firms to 

trade allowances, but they would also set an upper price 

for allowances, referred to as the safety-valve price. If the 

price of allowances rose to the safety-valve price, the government would sell as many allowances as was necessary 

to maintain that price. Thus, if the safety valve was triggered, the actual level of emissions would exceed the cap. 

The cap would be met only if the price of allowances 

never rose above the safety-valve price.5

Given Current Uncertainties, Pricing Policies Better 

Balance Costs and Benefits Than Emissions Caps 

If policymakers could be sure of the costs and benefits of 

limiting emissions, they could set either an emissions cap 

or an emissions price at exactly the right level to achieve 

the largest net benefits (benefits minus costs). Either approach could induce households and firms to reduce 

emissions up to the point at which the cost of the most 

expensive reduction in emissions was equal to the benefit 

that it would yield. Because the cost of emissions reductions would rise as successively costly cuts were undertaken, each reduction in emissions prior to that point 

would produce a benefit that exceeded the cost of achieving it, and each reduction after that point would have a 

benefit that fell below its cost. 

In reality, of course, neither potential benefits nor potential costs are certain. As a consequence, policymakers cannot be sure that a policy designed to maximize expected

benefits minus expected costs would maximize actual benefits minus actual costs: benefits, costs, or both are likely 

to end up being different than anticipated. Setting an excessively high price or too tight a cap would impose costs 

that were not justified by their benefits. Conversely, setting too low a price or too loose a cap would result in forgone benefits that outweighed the cost of obtaining 

them.

Most analysts believe that for greenhouse gas emissions 

that can be regulated through economic incentives, a policy that sets emissions prices is much more likely to minimize the adverse consequences of making a wrong choice 

than a policy that sets a strict limit on emissions.6 The 

reasons, discussed below, are related to characteristics of 

the costs and benefits of controlling stock pollutants.

Why Are Price Instruments More Efficient than

Emissions Caps? If the costs of policies to restrict emissions could be accurately determined and only the benefits of those policies were uncertain, then the choice be5. Another hybrid approach includes a “circuit breaker” rather than 

a safety valve. Under that approach, the cap would gradually 

decline as long as the price of allowances stayed below a predetermined trigger price. If the allowance price increased to the level of 

the trigger, the cap would be frozen. Once that happened, the 

price of allowances could remain above the trigger—which would 

be likely to occur, because the frozen cap would be harder to meet 

as the economy grew. Thus, a circuit breaker would not cap costs 

in the manner of a safety valve.

6. One researcher found that under certain conditions (including a 

perfect trading market and a lack of random shocks to allowance 

prices that do not stem from shocks in abatement costs), a tradable-allowance policy could cause firms to make greater investments in abatement technologies than an emissions price that 

produced the same level of emissions in the initial year. See Jinhua 

Zhao, “Irreversible Abatement Investment Under Cost Uncertainties: Tradable Emission Permits and Emissions Charges,” 

Journal of Public Economics, vol. 87, no. 12 (December 2003), pp. 

2765-2789. In contrast, emissions charges could offer a substantial advantage if the revenue generated from the charges was used 

to reduce existing taxes that cause distortions in the economy, 

such as taxes on capital and labor. The economic benefits of 

decreasing those distortionary taxes could substantially reduce the 

costs of the policy. A cap-and-trade program could offer a similar 

advantage, but only if the allowances were sold to firms rather 

than given away for free. For a discussion of that issue, see Ian 

Parry, Revenue Recycling and the Costs of Reducing Carbon Emissions, Climate Issue Brief No. 2 (Washington, D.C.: Resources for 

the Future, 1997); and Ian W.H. Parry, Roberton C. Williams 

III, and Lawrence H. Goulder, “When Can Carbon Abatement 

Policies Increase Welfare? The Fundamental Role of Distorted 

Factor Markets,” Journal of Environmental Economics and Management, vol. 37, no. 1 (January 1999), pp. 52-84.
28 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

tween policies that specified emissions limits or emissions 

prices would be irrelevant. Policymakers could set either 

an emissions price or an emissions limit at the point at 

which the expected cost of the last reduction in emissions 

was equal to the expected potential benefit that it would 

produce. If benefits ended up being lower than expected, 

the policy would end up being too stringent; if benefits 

were greater than expected, the policy would be too lenient. Either way, however, the adverse consequences of 

having chosen the wrong policy—the gap between costs 

and benefits—would be the same. The fact that the actual benefits were different than expected would have no 

effect on people’s response to the policy. Those responses 

would be determined either by the cap on emissions or 

the price, both of which were based on expected benefits. 

Thus, the actual emissions reductions—and the costs and 

benefits of those reductions—would be the same under 

either policy instrument.

When the costs of restricting emissions are also uncertain, 

however, the two policy instruments may result in very 

different levels of actual emissions—and different costs 

and benefits—even if both are set to yield the same expected level of emissions. Under a price instrument, 

households and firms will adjust their level of emissions 

reductions in a way that will keep actual costs roughly in 

balance with expected benefits—something they cannot 

do if faced with a strict limit on emissions.7

 The advantage of a price instrument is particularly great when regulators are very uncertain about the costs of reducing carbon emissions—either because they have less information 

about those costs than firms do or because those costs 

will ultimately depend on factors that neither firms nor 

policymakers know at the present time (such as the development of new technologies).

The illustrative example in Table 5-1 demonstrates that 

point. Despite the uncertainty surrounding the marginal 

benefit of reducing emissions, this example arbitrarily assumes that the value is $10 per metric ton of carbon. Furthermore, the example assumes that firms would minimize their compliance costs—either by equating their 

marginal cost of reducing emissions to the emissions 

price (under a tax) or to the allowance price (under a capand-trade policy).8 The example shows outcomes for two 

domestic policies (a price on emissions and a cap on 

emissions) that are designed to produce the same level of 

emissions reductions (and thus, the same expected costs 

and benefits). If policymakers charged a tax of $10 per 

ton on carbon (based on the expectation that the benefits 

of reducing a ton of carbon emissions is $10) and if the 

cost of reducing emissions was what they had anticipated, 

the $10 tax would result in a reduction of 29 million 

metric tons of carbon in the first year of the policy and 

provide a net benefit of $143 million.

If, however, the cost of reducing emissions by that 

amount was 50 percent lower than anticipated, firms 

would find it advantageous to undertake additional lowcost reductions—nearly twice as many—in lieu of paying 

the tax on those emissions. As a result of the unexpectedly 

low cost and the subsequent adjustment in emissions reductions, actual net benefits would be $280 million, 

which is $137 million greater than anticipated. Similarly, 

if costs were 50 percent higher than anticipated, firms 

would make fewer cuts in emissions—19 million mtc instead of 29 million mtc. The level of net benefits also 

would be lower than expected—but not as low as it 

would have been if firms had not had the flexibility to 

make fewer reductions and had been forced to make the 

full cut as was originally expected. Furthermore, given 

that reductions would be made up to the point at which 

the actual cost of the last reduction was equal to the expected benefit (because the tax had been set equal to that 

expected benefit), actual net benefits would be maximized, regardless of whether the costs were higher or 

lower than anticipated. 

Suppose, in contrast, that policymakers set an emissions 

cap that they believed would reduce emissions by the 

same amount as the $10 tax—29 million metric tons of 

carbon. The cap would be met regardless of the cost. If 

the marginal cost of meeting that cap turned out to be 50 

percent lower than expected, then actual net benefits, at 

7. Martin L. Weitzman first showed that a government policy that 

set a price on pollution would lead to higher expected net benefits 

than a policy that limited the level of pollution. See Martin L. 

Weitzman, “Prices vs. Quantities,” Review of Economic Studies, 

vol. 41, no. 4 (October 1974), pp. 477-491.

8. If this assumption did not hold, then the potential cost savings of 

an economic incentive policy would not be realized. For example, 

if firms chose to pay the tax rather than to undertake emissions 

reductions that could be made at a lower cost, firms’ costs (including tax payments) would be higher—and emissions reductions 

would be lower—than estimated in this example. Likewise, if 

firms did not make potentially cost-saving allowance trades, then 

the cost of meeting an emissions cap would be higher than estimated.
CHAPTER FIVE POLICY IMPLICATIONS 29

Table 5-1.

An Example of the Advantage of Using a Tax, Rather Than a Cap, to Reduce

Carbon Emissions

Source: Congressional Budget Office.

Notes: This example arbitrarily assumes that the benefit of reducing carbon emissions is $10 per metric ton. It examines the net benefits that 

would result in the first year of each policy, assuming that the policy would apply only to the United States, that the initial year would 

be 2010, and that the policy would have been announced 10 years earlier. The cost of firms’ emissions reductions (and the response 

to various taxes) is derived from Mark Lasky, The Economic Costs of Reducing Emissions of Greenhouse Gases: A Survey of Economic 

Models, CBO Technical Paper No. 2003-03 (May 2003), available at www.cbo.gov/Tech.cfm.

n.a.=not applicable.

a. The actual marginal cost of reducing 29 million metric tons (mmt) of carbon is $5, but the tax induces reductions up to 56 mmt, at a marginal cost of $10.

b. The actual marginal cost of reducing 29 mmt of carbon is $15, but the tax induces fewer reductions (19 mmt instead of 29 mmt), up to a 

marginal cost of $10.

$215 million, would be significantly greater than expected—but still lower than the $280 million in net 

benefits from the tax, which would induce firms to make 

additional beneficial emissions reductions (that is, reductions that would cost less than the benefits that they created). The cap, in contrast, would not induce firms to 

make any such adjustment.

Likewise, if the cost of meeting the cap was higher than 

anticipated, firms would still be required to reduce emissions by 29 million mtc, even though emissions reductions beyond 19 million mtc (the amount induced by a 

$10 tax) would cost more than the benefits that they created. As a consequence of that inflexibility, the net beneActual Outcomes

Expected Outcomes

 If the Cost of Reducing

Emissions Was 50 Percent 

Lower Than Expected

If the Cost of Reducing

Emissions Was 50 Percent 

Higher Than Expected

Set a Tax of $10 per Ton of Carbon

Marginal Cost (Dollars) 10 10a 10b

Emissions Reduction 

(Millions of metric tons) 29 56 19

Net Benefit (Millions of 

dollars) 143 280 96

Set a Cap to Reduce Carbon Emissions by 29 Million Metric Tons

Marginal Cost (Dollars) 10 5 15

Emissions Reduction 

(Millions of metric tons) 29 29 29

Net Benefit (Millions of 

dollars) 143 215 72

Memorandum:

Percentage Increase in

Net Benefit from a Tax 

Rather Than a Cap n.a. 30 34
30 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

fits from the cap would be 34 percent lower than the net 

benefits from the tax.9

An important assumption in this example is that the expected benefit of each emissions reduction is roughly constant—at about $10 per ton—across the range of possible 

emissions reductions in a given year. The fact that carbon 

dioxide is a stock pollutant, with damages determined by 

the total amount in the atmosphere, makes that assumption plausible. In the year in which this example is assumed to take place—2010—the policy-induced reductions in emissions constitute only 1 percent to 3 percent 

of total projected U.S. carbon dioxide emissions, which 

themselves will only amount to far less than 1 percent of 

the total stock of carbon dioxide in the atmosphere. 

Thus, the reductions would yield extremely small changes 

in the stock—a few hundredths of a percent at most. 

Over such a small range, the incremental benefit associated with each ton of reductions is expected to be roughly 

constant. That is not to say that the damages from a ton 

of emissions are zero, and it has nothing to do with the 

fact that the damages are very uncertain. The logic is simply that the incremental damage from each additional ton 

of emissions is essentially the same as the damage from 

each of the preceding tons in that year.10

The less information policymakers have about the cost of 

meeting a particular emissions cap, the greater the advantage offered by a price instrument. As discussed in Chapter 2, the cost of meeting a given cap is likely to be difficult to estimate for at least three reasons. First, the cost of 

meeting a future cap would vary significantly with the 

amount of growth in baseline carbon emissions. Those 

emissions are difficult to predict: they are a function of 

numerous factors, including population trends, economic 

growth, and energy prices. Second, policymakers have 

less information about the cost of reducing emissions 

than do the regulated firms. Third, the cost of meeting 

the future cap would depend on the technologies that 

were developed to reduce carbon dioxide emissions and 

the economic consequences of adopting those technologies—neither of which can be predicted with certainty. 

Are Price Instruments Still Preferred When the

Potential for Abrupt Climate Change Is Taken into

Account? Intuitively, the case for emissions caps would 

appear to be much stronger if there were evidence that 

temperature increases above a certain threshold would 

cause catastrophic damages—especially given the inertia 

of the climate system and the long adjustment to changes 

in concentrations. (See Box 2-1 on page 10 for a discussion of the scientific understanding about the potential 

for catastrophic damages.) That possibility might seem to 

call for a cap on emissions to avoid crossing the threshold. Current research supports that intuition, but only 

under a very restrictive set of circumstances:11

B There must be a trigger temperature that, if exceeded, 

results in a steep increase in damages; 

B Policymakers must have clear information about the 

location of the trigger temperature—for instance, if 

scientists uncovered evidence that an abrupt change 

that would be economically catastrophic would definitely occur at a temperature increase of 4.0o

 Celsius 

(C); and 

B The threshold must be sufficiently near so that policymakers would want to virtually shut down emissions—regardless of the cost—to avoid, or delay, 

crossing it.

Under those circumstances, either a price instrument or 

an emissions cap (appropriately set) would probably yield 

very large benefits, but the expected benefits from using 

an emissions cap would be greater.

If there is uncertainty about either the existence or the 

level of a trigger temperature—as is currently the case—

the potential advantages of emissions caps decline. Under 

those circumstances, it is no longer clear whether, or at 

what level, to set a cap to avoid a catastrophic outcome. 

9. Those results are based on a very simplified example of a domestic 

emissions reduction policy in force for one year. In a more rigorous analysis that used the Dynamic Integrated model of Climate 

and the Economy and accounted for numerous sources of uncertainty, Resources for the Future researcher William Pizer found 

that a price instrument could generate expected net benefits that 

were up to five times as high as those resulting from a cap. See 

William A. Pizer, “Choosing Prices or Quantity Controls on 

Greenhouse Gases,” in Michael A. Toman, ed., Climate Change 

Economics and Policy: An RFF Anthology (Washington, D.C.: 

Resources for the Future, 2001), pp. 99-107. 

10. See Henry D. Jacoby and A. Denny Ellerman, The Safety Valve 

and Climate Policy, Report No. 83 (Cambridge, Mass.: MIT Joint 

Program on the Science and Policy of Global Change, July 2002). 

11. See William A. Pizer, Climate Change Catastrophes, Discussion 

Paper 03-31 (Washington, D.C.: Resources for the Future, May 

2003).
CHAPTER FIVE POLICY IMPLICATIONS 31

Thus, setting an upper limit on the incremental cost of 

reducing emissions via a price instrument (even though 

that limit may be high) becomes relatively more important.12

Similarly, price instruments are generally superior if damages are expected to grow large, but at a gradual rate of 

increase (rather than increasing very rapidly beyond a 

known temperature threshold). Under those circumstances, being able to control emissions precisely is less 

critical (because there is less concern about passing a trigger point).

Finally, price instruments are preferred if modest emissions reductions are called for. If policymakers wished to 

slow the growth of the existing stock (or stabilize it, but 

only after a period of several decades), then there would 

be considerable leeway as to how reductions could be allocated across time. Costs would be minimized by making cuts when it was least costly to do so. A price instrument would allow for such flexibility in timing, whereas 

short-term emissions caps would not. Such caps would 

become desirable only if extremely large cuts in current 

emissions were required to quickly stabilize the atmospheric stock in order to avoid crossing a threshold.13

In sum, price-based policy instruments appear to be superior to caps, at least for the present—when uncertainty 

about the potential for catastrophic effects is large, the 

temperature increase that could trigger catastrophic outcomes is unknown, and the emissions reductions being 

contemplated fall substantially short of a complete shutdown. However, the choice of instrument could be revisited as information and circumstances change. Policymakers could switch from a price instrument to an 

emissions cap if possible future damages became more 

imminent and certain or if the potential for catastrophic 

effects became clearer. A hybrid cap-and-trade program 

with a safety-valve price could be easily transformed into 

an emissions cap simply by eliminating the safety valve.

The “Best” Emissions Price Is Unclear

If the expected marginal benefits of reducing emissions 

are greater than zero, the corresponding price on emissions will be greater than zero. A recent survey of the 

marginal benefits of reducing carbon emissions found 88 

estimates in 22 studies, authored by 12 independent 

teams of researchers.14 That survey found a wide range of 

estimates, with values very sensitive to the discount rate 

used in the analysis (lower rates led to higher marginal 

benefit values). The author concluded that “using standard assumptions about discounting and aggregation, the 

marginal cost of carbon dioxide emissions [that is, the 

marginal benefit of emissions reductions] is unlikely to 

exceed $50 per ton and is probably much smaller.”15 The 

Regional Dynamic Integrated model of Climate and the 

Economy (constructed by William Nordhaus and Joseph 

Boyer and described in this paper) estimates that the best 

price for a policy beginning in 2005 would be $12 per 

ton.16

The wide range of marginal benefit estimates (and thus 

recommendations about the best price) stems from the 

fact that determining the appropriate price requires longterm projections of uncertain economic and climate developments, valuation of uncertain impacts, and the balancing of competing interests and attitudes toward risks. 

Given that there is a wide range of valid opinions about 

those numerous factors, general agreement on a best price 

is highly unlikely.

Regardless of the level of stringency desired, costs could 

be moderated by phasing in prices gradually. A gradual 

phase-in would allow the economy to replace the existing 

capital stock at minimal cost to adjust to restrictions on 

fossil-fuel use. Prices could be increased over time as fu12. Furthermore, the uncertainty between carbon emissions and temperature change forces emissions caps to overcontrol emissions to 

make sure that the temperature threshold is not crossed. In that 

way, emissions caps become more like price instruments, which 

must overcontrol to account for the uncertainty in the relationship between increases in the price of carbon and the resulting 

reduction in carbon emissions. See Pizer, Climate Change Catastrophes.

13. For further discussion, see Pizer, “Choosing Prices or Quantity 

Controls on Greenhouse Gases.” 

14. Richard S.J. Tol, “The Marginal Costs of Carbon Dioxide Emissions” (presentation from an International Seminar on the Social 

Cost of Carbon sponsored by the U.K. Department for Environment, Food, and Rural Affairs, July 7, 2003, draft dated August 

24, 2003), available at www.defra.gov.uk/environment/climate 

change/carbonseminar/tol.pdf 

15. Ibid., abstract.

16. See William D. Nordhaus and Joseph Boyer, Warming the World: 

Economic Models of Global Warming (Cambridge, Mass.: MIT 

Press, 2000), p. 133. Numbers have been updated from 1990 dollars to 2005 dollars using a GDP deflator.
32 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

ture damages became more certain or took on more 

weight (as they became more imminent) or if information revealed that damages were likely to be greater than 

anticipated. If damages were projected to become sufficiently serious and imminent, a hybrid cap-and-trade 

program with a safety-valve price could be converted to a 

fixed cap by eliminating the safety valve.

The Most Efficient Policies Would Require International Coordination

Any effective mitigation policy would require international cooperation. Inexpensive opportunities to reduce 

emissions exist around the world, so costs would be minimized only if all countries imposed similar price-based 

emissions controls. The policy analyses discussed in this 

paper are based on the assumption that nations would cooperate to maximize global net benefits. However, some 

rapidly developing countries, such as China and India, 

may be reluctant to adopt lower-carbon technologies that 

could increase their cost of economic development, particularly in light of the fact that developed countries incurred no such penalty during the early phases of their industrialization. At the same time, developing countries 

will contribute a growing share of carbon emissions over 

time, and the infrastructure that they put in place today 

will affect carbon emissions for decades in the future. Finally, the requirements associated with enforcing a global 

solution might make some nations reluctant to participate and add a source of uncertainty about how effective 

and cost-effective the policies would be. (See Box 5-1 for 

a discussion of the current state of international coordination on climate policy.)

A further difficulty is that, as discussed in Box 5-1, international negotiations have focused on developing a set of 

national emissions allowance quotas or caps. Under that 

approach, nations might be able to minimize the cost of 

achieving the overall global emissions cap by trading allowances at the international level, but they would not 

necessarily do so at a marginal cost that was equal to the 

expected marginal benefit. That goal could be achieved 

by introducing a safety-valve price—set equal to the expected marginal benefit—that each country would agree 

to maintain by selling allowances at that price. Under a 

policy that incorporated an international safety valve, 

permits would be traded at the international level only if 

the market price was below the level of the safety valve.

Effectively implementing any international solution 

would require a means of monitoring emissions and ensuring enforcement. Monitoring would be easier if policies were limited to emissions of carbon dioxide from fossil fuels: nearly all fossil fuels are traded in commercial 

markets; information on countries’ fuel consumption is 

readily available; and the carbon content of different fuels 

is well understood.17 Significantly greater challenges arise 

in monitoring carbon emissions from (as well as uptake 

in to) forests and soils and in monitoring flows of other 

greenhouse gases from almost all sources.18

Even with a monitoring system in place, enforcing emissions restrictions would present a series of challenges. International environmental laws might be enforced 

through dispute resolution, unilateral actions such as economic sanctions, and the use of nongovernmental organizations, such as environmental groups.19 Advocates of an 

international cap-and-trade program for carbon dioxide 

emissions have also considered the possibility that international enforcement could be achieved by making either 

the seller or the buyer of allowances liable for the allowances’ integrity. A complete discussion of the pros and 

cons, and likely effectiveness, of those various approaches 

is beyond the scope of this paper; however, the ability to 

enforce such a global system of economic incentives to reduce greenhouse gases remains an important aspect of the 

problem—and an important source of uncertainty about 

costs.20

17. See David G. Victor, The Collapse of the Kyoto Protocol and the 

Struggle to Slow Global Warming (Princeton, N.J.: Princeton University Press, 2001), pp. 56-57. Victor notes that some on-site 

inspection could be needed for countries, such as Russia, that have 

poor fossil-fuel accounting systems and that consume a large percentage of the fossil fuels they produce. 

18. Ibid., p. 59.

19. For example, environmental groups have played prominent roles 

in enforcing international agreements to protect wildlife, such as 

panda bears, elephants, and tigers. Ibid., p. 66. 

20. Ibid., pp. 63-74.
CHAPTER FIVE POLICY IMPLICATIONS 33

Information on Underlying Uncertainties,

Nonmarket Benefits, and Distributional Effects 

Could Highlight Policy Trade-offs

While policymakers may derive important insights from 

assessments that attach monetary values to expected benefits and that aggregate the expected costs and benefits of 

mitigation policies, they may also profit from supplemental information that reveals the underlying uncertainties, 

reports key nonmarket benefits in natural units (such as 

the number of species lost), and reveals distributional effects. 

Box 5-1.

International Cooperation on Climate Policy

International cooperation to address the prospect of 

climate change began with the creation of the Intergovernmental Panel on Climate Change in 1988. 

Four years later, most of the world’s nations signed 

the United Nations Framework Convention on Climate Change, committing to undertake extensive research to better understand the climate system and, 

ultimately, to stabilize atmospheric concentrations of 

greenhouse gases at levels that would prevent dangerous climate change. 

In 1997, following several years of negotiations, participating countries adopted the Kyoto Protocol to 

the convention. The Kyoto Protocol limits greenhouse gas emissions from 38 developed countries to 

generally somewhat below their 1990 levels but exempts developing countries from restrictions altogether. The restrictions are scheduled to take effect 

during the so-called First Budget Period, from 2008 

to 2012, with no restrictions specified after that period. Ratification by Russia in late 2004 allowed the 

Kyoto Protocol to be officially accepted by enough 

countries to come into force in early 2005. 

Countries that have accepted restrictions on emissions under the protocol will probably be able to 

meet their commitments at little cost. They are allowed a significant degree of flexibility, including the 

right to trade allowances to emit greenhouse gases, 

the option to receive some credit for carbon sequestered in growing forests, and the option to receive 

credits by financing projects to reduce emissions in 

countries that are not subject to emissions limits. 

Moreover, a few countries—notably Russia and the 

Ukraine—are expected to have substantial amounts 

of surplus emissions allowances during the 2008-

2012 period. Other countries will be able to fulfill 

their commitments in part by buying surplus allowances and forestry credits at relatively low cost and 

thus will not have to undertake extensive emissions 

reductions domestically. 

Although countries’ costs of meeting their commitments are expected to be relatively low, experts generally agree that the cost of reducing emissions will 

probably vary considerably among countries, despite 

the option of trading allowances at the international 

level. Moreover, the actions taken by countries with 

commitments will be more than offset by the growth 

of emissions elsewhere and therefore will do little to 

moderate the growth in global emissions. 

Even if fully implemented, the Kyoto Protocol is expected to have only a small impact on temperature 

increases. One research team projects that permanently complying with the emissions limits outlined 

in the protocol would reduce the 2.53o

 Celsius (C) 

increase in the average global temperature that is predicted to occur over the next century in the absence 

of policy initiatives by 0.03o

C to 0.04oC.1

Having effectively withdrawn from negotiations in 

2001, the United States has not undertaken any 

commitments under the Kyoto Protocol. The next 

round of international negotiations, over what steps 

to take after 2012, will begin later this year.

1. See William D. Nordhaus and Joseph Boyer, Warming the 

World: Economic Models of Global Warming (Cambridge, 

Mass.: MIT Press, 2000), p. 153.
34 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

Figure 5-1.

Projected Change in Temperature in 

2100 from a Specific Policy

(Probability density)

Source: Congressional Budget Office adapted from Figure 1(B) in 

Mort Webster and others, “Uncertainty Analysis of Climate Change and Policy Response,” Climatic Change, vol. 

61, no. 3 (December 2003), p. 310.

Note: The specific policy illustrated in this figure is to stabilize carbon dioxide concentrations in the atmosphere at 550 parts 

per million.

Revealing Information About the Uncertainty of Policy 

Effects. Policy recommendations that take the form of 

point estimates can be useful, but they mask the enormous uncertainty underlying such estimates as well as the 

trade-off between higher current costs and greater protection from the risks of future damages. Although some 

studies have demonstrated how changes in a small subset 

of uncertain parameters can affect policy outcomes, no 

existing model is capable of simultaneously addressing all 

of the relevant uncertainties. Explicitly revealing uncertainty about costs and benefits could provide a more 

meaningful range of potential policy options and a better 

understanding of the probability that a given policy 

would actually balance future benefits and current 

costs.21 Policymakers may be able to make moreinformed decisions about how to insure against those 

risks if they have a sense of the full range of potential risks 

rather than certainty-equivalent point estimates based on 

that range.

One way of conveying uncertainty about the effects of a 

given policy is to present graphs that illustrate the likelihood of different outcomes, or tables that report several 

different points in the distribution of outcomes. Figure 5-

1, adapted from a policy analysis from the Massachusetts 

Institute of Technology, illustrates how a specific policy 

might affect the average global temperature, taking into 

account uncertainty about future emissions, their rate of 

accumulation in the atmosphere, and the response of the 

climate. 

The figure shows two distributions of temperature increases in 2100: one represents a “base” case; the other a 

policy designed to stabilize carbon dioxide concentrations 

in the atmosphere at 550 parts per million.22 (The higher 

the curve is above a particular temperature increase, the 

more likely that increase is to occur.) In the base case, the 

expected mean temperature increase in 2100 is 2.4°C, 

but there is a 1-in-40 chance (5 percent) that the increase 

will exceed 4.9°C. Under the specific policy, the expected 

increase is 1.7°C, which is 0.7°C less than in the base 

case, and there is an exceedingly small chance that the increase will exceed 4.9°C. However, there is still a 1-in-7 

chance (about 14 percent) that the temperature increase 

would exceed 2.4°C (the mean increase predicted in the

012345678

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

With Specific Policy

Without Specific Policy

(Base case)

Mean Global Temperature Change from 1990 (°C)

21. Similar recommendations are made by S.H. Schneider, K. KuntzDuriseti, and C. Azar in “Costing Non-Linearities, Surprises, and 

Irreversible Events,” Pacific and Asian Journal of Energy, vol. 10, 

no. 1 (June 2000), pp. 81-106; and by Henry D. Jacoby, 

“Informing Climate Policy Given Incommensurable Benefits Estimates,” Global Environmental Change: Human and Policy Dimensions, vol. 14, no. 3 (October 2004), pp. 287-297. Simultaneously 

accounting for all of the uncertainties involved in calculating the 

costs and benefits of climate change policies would be intractable. 

Nevertheless, analysts could focus on developing probability distributions for key parameters and on revealing the uncertainty 

about which policy that results from those underlying distributions would be best.

22. See Figure 1(B) in Mort Webster and others, “Uncertainty Analysis of Climate Change and Policy Response,” Climatic Change, 

vol. 61, no. 3 (December 2003), p. 310. 
CHAPTER FIVE POLICY IMPLICATIONS 35

base case) and a 1-in-40 chance that it would be greater 

than 3.2°C.23

Those distributions do not imply that there is a chance 

that the policy would not restrain the temperature increase at all; rather, they imply that the exact outcome 

cannot be predicted in either case. The lesson for policymakers is that policies are more accurately viewed as 

changing the distribution of potential future temperatures rather than as achieving specific targets.

Another method of revealing the uncertainty associated 

with alternative policies is to provide several point estimates that correspond to outcomes that have different 

likelihoods of occurring. A demonstration of that technique is provided by Stanford University researchers Tim 

Roughgarden and Stephen Schneider, drawing on a survey by William Nordhaus (discussed in Chapter 3). That 

survey revealed widely divergent views about the potential damages—and the value of those damages—that 

would result from a 3o

C or 6oC temperature increase in 

2095. Roughgarden and Schneider carried out a Monte 

Carlo analysis (see Chapter 2 for a description of that 

technique) to determine the range of possible “best” 

prices. In that analysis, each of 1,000 runs of the simulation model selected random damages from the probability distribution of potential damages based on the full set 

of experts’ estimates in Nordhaus’s survey.24

Roughgarden and Schneider estimated that the mean 

“best” price (which would balance benefits and costs) 

would be $53 per ton of carbon in 1995 and $145 in 

2105. At the same time, there is the possibility that damages could be very large and that the true optimal price 

could be very high: the researchers calculated a 5 percent 

chance that the optimal price could be at least as high as 

$255 per ton of carbon in 1995 and $683 in 2105.

The probabilities and damage estimates underlying that 

analysis are based on experts’ best guesses and should not 

be considered scientifically determined. Despite those 

limitations, the analysis offers a valuable lesson: recommended emissions prices can vary depending on policymakers’ aversion to the risks from climate change.25 If 

risk-averse policymakers wanted to choose a policy that 

would be optimal if experts predicting large damages 

were correct, then they should set a very high emissions 

price—and accept the cost that such a high price would 

impose on economic growth.

Although characterizing the uncertainty associated with 

policy outcomes can be useful, such attempts can create a 

false sense of precision. Analysts should be careful to acknowledge the lingering uncertainties that cannot be 

meaningfully quantified in their analyses. 

Revealing Information About Nonmarket Benefits. As 

discussed in Chapter 3, there is no clear-cut method for 

attaching monetary values to many of the nonmarket 

damages that would result from climate change. Policymakers could therefore profit from additional information on the benefits derived from nonmarketed goods 

and services that underlie policy recommendations.26 For 

example, policy outcomes could include predictions of 

reductions in the number of species lost, premature 

deaths avoided, or land area lost because of a rise in sea 

level and could indicate the values that were used for 

them in the analysis. That approach would allow policymakers to determine whether the weights used in the 

23. Matters get even more complicated when all greenhouse gases are 

included in the analysis, because of uncertainties about how powerful their greenhouse effects are and how long they stay in the 

atmosphere. See Marcus C. Sarofim and others, Stabilization and 

Global Climate Policy, Report No. 110 (Cambridge, Mass.: MIT, 

July 2004).

24. See Tim Roughgarden and Stephen H. Schneider, “Climate 

Change Policy: Quantifying Uncertainties for Damages and Optimal Carbon Taxes,” Energy Policy, vol. 27, no. 7 (July 1999), pp. 

415-429. Numbers are in current dollars. Also note that this study 

examined uncertainty only in damages, using best estimates for all 

of the other inputs to the analysis, such as mitigation costs, the 

degree of climate change, and the discount rate. 

25. William Nordhaus used the experts’ responses to develop a set of 

certainty-equivalent damages (see Chapter 3). Using that certainty-equivalent damage function in a climate policy model, 

Nordhaus estimated that costs and benefits would be best balanced by a carbon tax that started at $8 per ton in 1995 and rose 

to $89 per ton in 2105 (numbers are in current dollars). While 

that expected-value method of determining damages provides 

some insights into a price that might result in a balancing of benefits and costs, it conceals the considerable amount of uncertainty 

about which price would actually accomplish that goal. That is, it 

does not reveal the probability that the actual best price could 

prove to be higher or lower; nor does it calculate the price that 

would balance uncertain costs and benefits if people were more 

averse to risk.

26. Ideally, the probability distributions underlying such predictions 

could be reported as well. For a more detailed discussion of this 

recommendation and others discussed in this section, see Jacoby, 

“Informing Climate Policy Given Incommensurable Benefits

Estimates.”
36 UNCERTAINTY IN ANALYZING CLIMATE CHANGE: POLICY IMPLICATIONS

analysis were consistent with their own or their constituents’ preferences.

Revealing Information About Distributional

Effects. Since the costs and benefits of climate policies are 

not expected to be evenly distributed across the globe, information on the regional distribution of costs and benefits associated with alternative policies could help policymakers understand the strength of other countries’ and 

regions’ interests in international negotiations. To the extent that nonmarketed goods are a key component of the 

benefits of a given policy, reporting those nonmarket 

benefits on a regional basis could be helpful. Given the 

current level of knowledge, however, predictions of outcomes at the regional level are likely to be particularly 

speculative.

Adaptation

The world is committed to some degree of warming from 

emissions that have already occurred, and even very aggressive emissions restrictions are unlikely to halt the 

growth of concentrations for many years to come.27 In 

light of the potential for future temperature increases, adaptation could play an important role in any effective climate strategy.

Unlike mitigation policy, which could be implemented 

largely with a single instrument—for instance, a single 

emissions price, or an aggregate emissions cap—policies 

to promote adaptation are likely to be more diffuse, involving numerous policies in many different areas and involving different levels of government. Potential adaptations could be facilitated through various policies, 

including: 28

B Promoting the efficient use of water resources (which 

would become scarcer in a warmer world) through 

prices that reflect scarcity or the establishment of markets for water;

B Encouraging the development of low-cost technologies for desalinating seawater;

B Instituting vaccination programs to prevent the spread 

of diseases transmitted by arthropods, such as ticks or 

mosquitos; 

B Encouraging the preservation of green corridors that 

would allow plant and animal species to migrate as 

their habitat changed;

B Developing early-warning systems to alert people to 

potential flooding, developing more appropriate 

building standards and design codes for buildings in 

flood-prone areas, and facilitating the relocation of 

people living in low-lying areas in counties prone to 

increased flooding; and

B Encouraging the development and use of droughtresistant crops.29

Local, state, and federal governments could be involved 

in such efforts. For example, local governments could institute early-warning systems, enact building codes, or restrict development in flood-prone areas. The federal government could fund research, develop education 

programs, and subsidize immunization programs. International organizations could also play an important role 

in adaptation efforts, as when the World Bank established a Disaster Management Facility in 1998 to facilitate a more strategic response to disaster emergencies and 

to integrate policies to reduce the risk of disasters into development activities.30 As the above list illustrates, many 

policies that could facilitate adaptation to a changing climate are likely to yield benefits even if climate change 

proves to be relatively benign.

27. For example, William Nordhaus and Joseph Boyer provide a bestguess projection that limiting global carbon dioxide emissions to 

1990 levels would reduce the expected temperature increase in 

2100 from 2.53°C to 2.02°C. See Nordhaus and Boyer, Warming 

the World, p. 141. Researchers at MIT projected that a policy 

designed to stabilize carbon concentrations in the atmosphere at 

550 parts per million would reduce the expected average global 

temperature increase from 2.4°C to 1.7°C. See Webster and others, “Uncertainty Analysis of Climate Change and Policy 

Response.”

28. See Intergovernmental Panel on Climate Change, Climate Change 

2001: Impacts, Adaptation, and Vulnerability (Cambridge, 

England: Cambridge University Press, 2001), p. 88. 

29. Ibid., pp. 885-886.

30. See Ajay Mathur, Ian Burton, and Maarten van Aalst, eds., An 

Adaptation Mosaic: A Sample of the Emerging World Bank Work in 

Climate Change Adaptation (Washington, D.C.: World Bank Global Climate Change Team, February 2004).