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Scand. J. of Economics 121(3), 884–924, 2019
DOI: 10.1111/sjoe.12383
The Nobel Memorial Prize for William D.
Nordhaus*
Lint Barrage
Brown University, Providence, RI 02912, USA
lint barrage@brown.edu
Abstract
William D. Nordhaus and Paul M. Romer received the 2018 Sveriges Riksbank Prize in
Economic Sciences in Memory of Alfred Nobel. This paper surveys Nordhaus’ contributions
on “integrating climate change into long-run macroeconomic analysis”, for which he was
recognized with this Prize.
Keywords: Carbon tax; climate change; climate clubs; DICE model; energy models; integrated
assessment; social cost of carbon
JEL classification:B0; O4; O44; Q5; Q54
I. Introduction
William D. Nordhaus was awarded the 2018 Sveriges Riksbank Prize in
Economic Sciences in Memory of Alfred Nobel “for integrating climate
change into long-run macroeconomic analysis”. The ubiquity of climate
change in modern economic analyses might render it difficult to appreciate
how truly ground-breaking this contribution has been. In the early 1970s,
amidst heated public and academic debates about limits to growth from
energy and resource scarcity, Nordhaus presciently flagged climate change
as the more likely natural constraint on long-run growth (Nordhaus, 1974).
He cautioned about melting polar ice caps as a consequence of misdirected
economic growth almost 20 years before the United Nations released its
first Intergovernmental Panel on Climate Change (IPCC) report in 1990
(Nordhaus and Tobin, 1972). Nordhaus immersed himself in the physical
sciences literature and pioneered the first integration of a carbon cycle
model into an economic linear programming model of global energy
markets (Nordhaus, 1975a). He used this integrated model to produce the
*I am indebted to Kieran Walsh for detailed feedback and support in the writing of this article. I
also thank Ingrid Barrage, Ken Gillingham, John Hassler, Charlie Kolstad, Per Krusell, Christian
Traeger, and Ken Youngstein for their helpful comments, and Jesse Ausubel for sharing his
insights. Finally, I thank William Nordhaus for his invaluable feedback on this article, and for
everything he has taught me. All errors are my own.
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2019 The Author. The Scandinavian Journal of Economics published by John Wiley & Sons Ltd on behalf of F¨oreningen
f¨or utgivande av the SJE/The editors of The Scandinavian Journal of Economics.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License,
which permits use and distribution in any medium, provided the original workis properly cited, the use is non-commercial and
no modifications or adaptations are made.
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first ever estimates of global carbon taxes that could maximize economic
welfare subject to constraints on greenhouse gas concentrations (Nordhaus,
1977). This work so clearly defined a new frontier that 1975 Nobel
Laureate Tjalling Koopmans took time to describe the climate problem
and Nordhaus’ efforts in his own Nobel banquet toast at the time.1
After Nordhaus’ pioneering introduction in 1977, it would be years before
other scholars began to study carbon taxes, and the term did not even
appear again in the American Economic Review until 1991. Today, carbon
pricing policies have been adopted by an estimated 46 countries and
24 subnational jurisdictions around the world (World Bank, 2018). As
early as 1980, Nordhaus developed the first climate–economy optimizing
integrated assessment model (IAM) by simultaneously incorporating the
economy’s greenhouse gas emissions, the carbon cycle, and a first
aggregate climate change damage function into an economic growth model.
Nordhaus (1980) introduced both a theoretical characterization and the
first ever numerical estimates of optimal climate policy based on an
integrated cost–benefit analysis. This fundamental innovation also came
years before such frameworks became more widely studied, and other
scholars built on Nordhaus’ estimates from the beginning.2The 1980s
saw significant advancements in scientific understanding of climate change
and its potential impacts, and Nordhaus served on the frontlines of early
syntheses of this work, for example, through his service on the National
Academy of Sciences’ Carbon Dioxide Assessment Committee. Building
on this growing knowledge, Nordhaus continued to refine his climate–
economy model (Nordhaus, 1991a), culminating in the introduction of
the Dynamic Integrated model of Climate and the Economy (DICE;
Nordhaus, 1992, 1993a,b, 1994a). Since its inception, DICE has served
as a conceptual and modeling foundation for climate change economics
and its policy applications. DICE is an unequivocal benchmark of the
literature. Because of the model’s transparency and Nordhaus’ persistent
efforts to make its code accessible and understandable to all, countless
scholars have stood on the shoulders of DICE and its multi-regional
variant RICE (Nordhaus and Yang, 1996; Nordhaus and Boyer, 2000) to
analyze the climate implications of everything from scientific uncertainty
to international technology spillovers. In the policy realm, DICE is
one of three models that have been used by the US government to
value the social cost of carbon (SCC; Greenstone et al., 2013). These
1Koopmans received the prize jointly with Soviet scholar Leonid Kantorovich for their
“contributions to the theory of optimum allocation of resources” (see https://www.nobelprize.
org/prizes/economic-sciences/1975/koopmans/speech/).
2For example, Peck and Teisberg (1992) used the damage estimates in Nordhaus (1991a) to build
another early optimizing integrated assessment model.
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886 The Nobel Memorial Prize for William D. Nordhaus
SCC estimates have informed regulatory impact analyses of over 70 US
federal rule-makings.3The US Courts have even overturned federal agency
decisions for failing to incorporate these SCC estimates (Metcalf and Stock,
2017). Notwithstanding recent changes in US federal policy, these SCC
estimates continue to inform decision-making across US states and other
countries.4
Alfred Nobel established his namesake prize for “those who ...have
conferred the greatest benefit to humankind”.5Since diagnosing the lack
of a carbon price as key potential source of conflict between economic
growth and the environment in the 1970s, Nordhaus and his collaborators
have integrated research from the physical, natural, and social sciences to
give the world a flexible tool that can quantify such prices for a wide range
of policy objectives. This work remains foundational for modern climate
change economics, and carbon prices are now adopted by governments
around the world to redirect the global economy towards a more sustainable
long-term growth path. Without a doubt, this work exemplifies the spirit of
Nobel’s vision.
This body of work also represents science at its best: integrative across
disciplines, visionary in scope yet incremental in progress, transparent, and
producing knowledge for the benefit of humankind. Nordhaus has always
emphasized the importance of the broader scientific community and the
institutions that enable his (and all of our) work. He began his official
2018 Nobel Lecture in part by noting that:
“I am here today [...] just one person representing what I
think of as an invisible college of people around the world and
over time, not just in economics but in many disciplines [...],
dealing with this broad set of problems having to do not just
3See Table A1 in the Appendix for a listing of federal rules, and also Nordhaus (2014) for a
discussion.
4For example, both New York and Illinois have used this SCC estimate to set zero-
emissions electricity subsidy rates; the New York State Energy Research and Development
Authority (NYSERDA) Clean Energy Standard (https://www.nyserda.ny.gov/All-Programs/
Programs/Clean-Energy-Standard and the Future Energy Jobs Bill, SB 2814, 220 ILCS 5/20-
135). Canada has also adopted this SCC estimate (Policy on Cost–Benefit Analysis, Treasury
Board of Canada Secretariat (see https://www.canada.ca/en/treasury-board-secretariat/services/
federal-regulatory- management/guidelines-tools/policy- cost-benefit- analysis.html).
5While the Sveriges Riksbank Prize in Economic Sciences was not a part of Nobel’s original
will, the Royal Swedish Academy of Sciences “appoints the prize-winner(s) according to the
same principles as for the Nobel Prizes” (see https://www.riksbank.se/en-gb/about-the-riksbank/
the-tasks-of-the- riksbank/research/economics-prize/).
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with climate change, but with the interaction of the economy
with the natural world.”6,7
This invisible college has a long tradition, going back to
Sweden’s first Nobel Laureate, Svante Arrhenius, who in 1896 made
pioneering calculations on the relationship of atmospheric carbon dioxide
concentrations and earth’s heat retention.8Arrhenius’ rule is still used today
– and it was Nordhaus who introduced it into economic analysis.
This article surveys Nordhaus’ contributions on integrating climate
change in long-run macroeconomic analysis.9To begin, Section II reviews
Nordhaus’ identification of climate change and the lack of a carbon price
as impediment to sustainable long-run growth. Then, Section III chronicles
Nordhaus’ first breakthrough on integrating the carbon cycle into economic
modeling, based on his work at the International Institute for Applied
Systems Analysis. Section IV describes Nordhaus’ development of the
first ever optimizing climate–economy IAM, which provided the first fully
integrated cost–benefit assessment of climate policy. Section V presents
the DICE framework. We describe the model and survey the foundational
role it has played in the literature and policy realm to date. Finally,
Section VI concludes by highlighting Nordhaus’ influence on the levels of
rigor and openness in academic and public debates, and towards a shared
understanding of the issues.
II. A Prescient Diagnosis
“In contemplating the future course of economic growth in the
West, scientists are divided between one group crying ‘wolf’
6Transcribed from the Nobel Lecture video available from Nobel Media at https://www.
nobelprize.org/prizes/economic-sciences/2018/nordhaus/lecture/.
7Nordhaus’ influential first book on the DICE model (Nordhaus, 1994a) contained similar thanks
to “the invisible but substantial contributions of a cadre of colleagues in this field who have
contributed to the development of a field of the economics of global environmental issues.”
8Arrhenius was awarded the Nobel Prize in Chemistry in 1903 for his work on electrolytic
dissociation.
9Given this focus, we are thus unable to delve into Nordhaus’ other major contributions, which
span work on incorporating the environment into national accounts (Nordhaus and Tobin, 1972;
National Research Council, 1999; Muller et al., 2011), on endogenous technical change (e.g.,
Nordhaus, 1969), on developing a geographically based “G-Econ” database of gross value added
for every one-degree longitude by one-degree latitude cell around the world (Nordhaus et al.,
2006), on “the political business cycle” (Nordhaus, 1975b; this is actually Nordhaus’most widely
cited single paper as of February 2019), and on the measurement of income growth in the
presence of technological change (e.g., Nordhaus, 1996). This latter study is especially famous
for Nordhaus’ collection of ancient lighting instruments used to construct a history of the true
cost of lumen-hours from prehistoric fires to oil lamps to the present in an effort to test the ability
of national accounts’ price indices to adjust for technological progress.
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888 The Nobel Memorial Prize for William D. Nordhaus
and another which denies that species’ existence.” (Nordhaus,
1977)
The post-war economic boom of the 1950s and 1960s created a
sharp divergence in perspectives on the future of economic growth. For
economists, this period marked a shift towards expecting sustained growth
as a norm. Growth “was simultaneously the hottest subject of economic
theory and research [...] and a serious objective of the policies of
governments” (Nordhaus and Tobin, 1972). For others, natural resource
depletion became a paramount concern. In April 1970, an estimated 20
million Americans took to the streets to protest against environmental
degradation.10 Some scholars began to issue dire warnings about the planet’s
ability to sustain continued growth, as exemplified by prominent works such
as Paul Ehrlich’s neo-Malthusian The Population Bomb (Ehrlich, 1968) and
the highly influential Limits to Growth report by Meadows et al. (1972). The
authors warned that if present trends continue, the planet’s limits to growth
would be reached and “the most probable result will be a rather sudden and
uncontrollable decline in both population and industrial capacity” (Meadows
et al., 1972). In sharp contrast, the emerging standards of neoclassical
economic growth modeling did not even consider environmental processes.
Nordhaus, at the time an Associate Professor of Economics at Yale
University, took these concerns seriously, and began to bridge this chasm.
Nordhaus had completed his undergraduate studies at Yale and earned
his PhD at the Massachusetts Institute of Technology in 1967 under the
guidance of Robert Solow (1987 Nobel Laureate and one of the founders
of modern neoclassical growth theory), Edwin Kuh (an econometrician),
and Paul Samuelson (1970 Nobel Laureate and one of the founders of
modern economic analysis). From his dissertation, Invention, Growth, and
Welfare: A Theoretical Treatment of Technological Change and subsequent
work, Nordhaus was already confronting divergences between social and
private returns to activities that affect economic growth.
In both the classic “Is Growth Obsolete?” (Nordhaus and Tobin, 1972),
written with Yale colleague and 1981 Nobel Laureate James Tobin, and
in “Resources as a Constraint on Growth” (Nordhaus, 1974), Nordhaus
delivered several sharp insights on environmental limits to growth. On
the one hand, for “appropriable resources” that the market already treated
as economic goods (e.g., aluminum, coal, natural gas), Nordhaus (and
Tobin) reviewed economic theory, empirical evidence, and data on resource
endowments, consumption rates, and relative price trends with labor, and
concluded that these resources did not appear poised to become a constraint
10See “EPA History: Earth Day” on the Environmental Protection Agency’s website, https://www.
epa.gov/history/epa-history-earth-day.
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on growth in terms of availability, affordability, or efficiency.11,12 On the
other hand, they warned that “possible abuse of public natural resources
is a much more serious problem”. While Nordhaus and Tobin proposed a
novel “measure of economic welfare” that included some adjustments for
local air pollution disamenities, they noted that global environmental public
goods are different. “Maybe we are pouring pollutants into the atmosphere
at such a rate that we will melt the polar icecaps and flood all the
world’s seaports,” they cautioned. Nordhaus (1974) provided a more explicit
description of the greenhouse effect.13 He introduced new findings from the
physical sciences and effectively flagged climate change as the most serious
potential sustainability problem resulting from unfettered growth and energy
consumption.
Along with this diagnosis, Nordhaus and Tobin (1972) also immediately
pointed towards a solution that could deliver both growth and environmental
protection:
“The mistake of the antigrowth men is to blame economic
growth per se for the misdirection of economic growth. The
misdirection is due to a defect of the pricing system – a serious
but by no means irreparable defect [...].
“There are [...] serious consequences of treating as free things
which are not really free. [...] The producers of automobiles
and of electricity should be given incentives to develop and
to utilize ‘cleaner’ technologies. The consumers of automobiles
and electricity should pay in higher prices for the pollution they
cause, or for the higher costs of low-polluting processes. [...]
At present, overproduction of these goods is uneconomically
subsidized as truly as if the producers received cash subsidies
from the Treasury.
“Although general economic growth has intensified the problem,
it seems to originate in particular technologies. The proper
remedy is to correct the price system so as to discourage these
technologies. Zero economic growth is a blunt instrument for
cleaner air, prodigiously expensive and probably ineffectual.”
While it was Pigou (1920) who introduced the idea of corrective
taxes as a remedy for the divergence between the private and social
11Of course, Nordhaus was careful to note that cartels render oil markets non-competitive. He
deals with this issue formally in, for example, Nordhaus (1979).
12Leading formalizations of economic g rowth with scarce natural resources were later introduced
by Dasgupta and Heal (1974), Solow (1974), and Stiglitz (1974).
13Examples of even earlier mentions of climate change in economics exist, such as Ayres and
Kneese (1969) and Kneese (1971).
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890 The Nobel Memorial Prize for William D. Nordhaus
costs of an activity, the application of this concept to the global climate
presents a daunting challenge. In theory, a Pigouvian tax should reflect
the value of marginal damages from an additional unit of pollution,
evaluated at the socially optimal allocation. For pollutants that are local and
dissipate quickly, social costs are typically data-intensive but conceptually
straightforward to measure. For example, Pigou (1920) already cites a 1918
study by the Manchester Air Pollution Advisory Board, which surveyed
households in both Manchester (polluted) and Harrogate (clean) about their
laundry expenditures to estimate the washing externality costs of industrial
smoke. Coupled with estimates of the marginal contribution to “smoke”
concentrations from industrial activities, one could infer an approximate
Pigouvian tax.
For climate externalities, the relevant calculations are exponentially more
complex. First, each ton of carbon dioxide emitted today enters the global
carbon cycle and has time-varying impacts on the climate for centuries
to come. Second, the resulting marginal changes in the global climate
affect the economy and human welfare in varying ways across sectors,
countries, and time. Potential impacts range from changes in agricultural
productivity to disease vectors, energy requirements, biodiversity losses,
and potentially catastrophic climate destabilization, to name only a few.
Producing a credible estimate of the resulting aggregate costs would thus
require a rich body of literature about scientific impact that did not exist
at the time when Nordhaus began to tackle this endeavor. The first step
in this chain, however (i.e., the present and future impacts of energy
consumption on the climate system) was already the subject of active
research. Nordhaus and Tobin noted that “there is probably very little
that economics alone can say” on the dangers of global environmental
externalities. As a next step, collaboration with other disciplines would be
essential for progress.
III. Integrating the Climate into Economics
“The opportunity and need for fruitful collaboration between
economists and physical scientists has never been greater.”
(Nordhaus and Tobin, 1972)
In 1974, Nordhaus traveled to Austria to visit the International Institute
for Applied Systems Analysis (IIASA).14 IIASA had been founded in 1972
as a collaborative effort between the United States, the Soviet Union, and
14For further information about IIASA, see their website http://www.iiasa.ac.at/web/home/about/
whatisiiasa/what is iiasa.html.
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several other countries in order to conduct “research into problems of a
global nature that are too large or too complex to be solved by a single
country or academic discipline”. For example, IIASA’s first major study, the
Energy Project, embarked on a vast multidisciplinary investigation into the
world’s energy future (H¨afele et al., 1981). By 1975, IIASA already featured
“a sparkling array of talent working on problems of energy, ecology, water
resources, and methodology”.15 It was here that Nordhaus immersed himself
in the physical and natural sciences research on carbon and the climate,
learning from both colleagues and the literature (see Nordhaus, 2019). This
new knowledge enabled him to produce the ground-breaking innovation of
a first carbon-cycle economic IAM.
On the climate side, Nordhaus’ approach built closely on the work of
Lester Machta (1972), who had developed a matrix representation of the
carbon cycle based on the movement of carbon between different reservoirs,
such as the atmosphere and the ocean. Formally, in his 1975 IIASA
working paper “Can We Control Carbon Dioxide?” (Nordhaus, 1975a),
Nordhaus presented the following model based on this work. Let Mi(t)
denote the stock of carbon in reservoir iat time t,where i={Troposphere,
Stratosphere, Upper oceans, Deep oceans, Short-term biosphere, Long-term
biosphere, Marine biosphere}, and let dij denote annual transfer coefficients
from reservoir ito reservoir j. The carbon cycle can then be captured by
Mi(t)=
7
j=1
djiMj(t−1).(1)
In matrix form, equation (1) simply becomes M(t)=DM(t−1), where
Ddenotes the Markov matrix of transfer coefficients dij. Critically, this
representation enabled Nordhaus to incorporate the carbon cycle into linear
programming models. Based on the contributions of 1975 Nobel Laureates
Tjalling Koopmans and Leonid Kantorovich, this approach searches for
the optimal allocation of resources in an economy subject to any relevant
constraints, such as constraints on resource availability.
Thus, the fundamental innovation of Nordhaus (1975a) was to integrate
equation (1) as a constraint into a dynamic energy market equilibrium
model of the US and world economies, and to present the first estimates
of optimal global energy allocations and pricing subject to limitations on
global greenhouse gas concentrations. That is, Nordhaus used this integrated
carbon cycle–economy model to study how energy inputs and prices should
evolve across fuel types and sectors over time in order to maximize global
15See the talk “The Founding of the Institute” given by Howard Raiffa at IIASA on 23 September
1992; the edited transcript is available on IIASA’s website http://www.iiasa.ac.at/web/home/
about/whatisiiasa/history/founding/the founding of the institute.html.
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892 The Nobel Memorial Prize for William D. Nordhaus
welfare subjects to limits on climate change. As there were neither policy
targets nor damage estimates available at the time, Nordhaus considered
constraints designed to keep the climatic effects of carbon dioxide emissions
“well within the normal range of long-term climatic variation”. This type
of analysis also remains the bedrock of policy applications of integrated
assessment models to analyze how politically agreed upon climate targets,
such as a limit to 2◦C warming, can be achieved at the lowest economic
cost. As a testament to Nordhaus’ ability to capture the essence of complex
processes even in parsimonious specifications, several of the model’s
predictions turned out to be strikingly accurate. For example, the model
projected year 2000 tropospheric carbon dioxide concentrations in the
absence of a global emissions control program to be 376 parts per million
(ppm). In reality, they were 370 ppm in 2000, and reached 376 by 2003.16
Back in the United States, Nordhaus disseminated these findings along
with a third trail-blazing contribution: carbon taxes. Nordhaus (1977)
presented estimates of carbon tax schedules that could decentralize the
efficient energy resource allocations from his model. This foundational
contribution was again rooted in the linear programming approach, which
enables researchers to calculate shadow prices that reflect the social costs
of activities. While Nordhaus (1975a) had already presented estimates of
shadow prices on carbon dioxide, Nordhaus (1977) labeled these explicitly
as carbon taxes. These were the first ever quantitative estimates of carbon
taxes as a tool to meet a policy objective, here to stabilize the global climate
at least cost.17
Nordhaus continued to blaze the carbon tax analysis trail for several
years (e.g., Nordhaus, 1979, 1980, 1982; Nordhaus and Yohe, 1983) before
other scholars formally joined, with Edmonds and Reilly (1983) serving as
an early example and others following in the later 1980s and early 1990s
(e.g., Manne and Richels, 1990; see also Section IV). It should be noted
that Nordhaus’ carbon tax proposal was initially met with some fundamental
skepticism (e.g., Hasson, 1980), as had been the case with early calls for
pollution levies in other settings (Resources Editor, 2001). Thus, we should
not take for granted the broad support that carbon pricing now enjoys, and
we must credit Nordhaus for first introducing, quantifying, and championing
this idea. Of course, we must also give credit to other scholars in the
invisible college who had in parallel been advocating for pollution levies
16See “Full Mauna Loa CO2record” on the National Oceanic and Atmospheric Administration
(NOAA) website https://www.esrl.noaa.gov/gmd/ccgg/trends/full.html.
17This statement reflects the best of our knowledge. We did not find any other prior references
to carbon taxes or related phrases on JSTOR or on other scholarly archives. Google Scholar
lists several carbon tax references with earlier dates, but we have found them to be (wildly)
mis-labeled.
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as a cost-effective alternative to command-and-control regulations, such as
for water pollution (e.g., Kneese and Bower, 1968; Kneese and Schultze,
1975).
Despite their ground-breaking nature, the carbon tax estimates in
Nordhaus (1977) did not yet correspond to Pigouvian levies, as they
reflected arbitrary rather than optimal emissions targets based on cost–
benefit considerations. As noted by Nordhaus (1977): “The central question
for economists, climatologists, and other scientists remains: How costly are
the projected changes in (or the uncertainties about) the climate likely to
be, and therefore to what level of control should we aspire?”
IV. Climate Change Impacts and Integrated Assessment
“We now move from the terra infirma of climate change to the
terra incognita of the social and economic impacts of climate
change.” (Nordhaus, 1991a)
While increased scientific attention towards greenhouse warming
brought with it early calls for policy interventions (e.g., Woodwell et al.,
1979), these continued to lack a cost–benefit foundation. In a 1980 Cowles
Foundation working paper, Nordhaus proceeded to tackle this enormous
challenge, and, in the process, made several fundamental contributions
(Nordhaus, 1980).
First, Nordhaus presents a theoretical analysis of optimal growth and
climate change. Though stylized so as to be accessible and “introduce to
the natural scientist the analytical tools of the economist”, this paper derives
results that have remained central to economists’ analyses of the climate
problem. These include an analytical expression for the optimal carbon tax
and a thorough treatment of how the pure rate of time preference, the
intertemporal elasticity of substitution, and future output growth affect the
social cost of carbon, bridging to the foundational work of Ramsey (1928)
on the determinants of savings and interest rates.
Nordhaus’ treatment distills the economic problem of climate
management to its essence. On the one hand, current consumption c(t)is
an increasing function f(.)of current fossil fuels usage and thus emissions
E(t). On the other hand, consumption (broadly defined to include, e.g.,
environmental amenities) can be harmed by the stock of accumulated
atmospheric carbon M(t)over pre-industrial levels via some relation h(.).
In its simplest form, a one-box representation, the law of motion for
atmospheric carbon M(t)can be boiled down to the fraction of carbon
emissions entering the atmosphere β(i.e., remaining in the atmosphere net
of immediate absorption by the biosphere) and the fraction δleaving the
atmosphere into an implicit sink, such as the deep oceans. In the simplest
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894 The Nobel Memorial Prize for William D. Nordhaus
setting (without growth), the climate problem is thus to maximize the
present value of utility u(.)for current and future generations subject to
its resource constraints and the laws of atmospheric carbon accumulation:
max
{c(t)}W=∫∞
0
e−ρt·u[c(t)]dt;(2)
c(t)=f[E(t)] − h[M(t)];(3)
·
M(t)=βE(t)−δM(t).(4)
Here, ρdenotes the pure rate of social time preference. The solution to
this problem and the optimal carbon price q(t)that can implement this
allocation in the decentralized economy are then defined by the following
condition:
f[E(t)]
Marginal
abatement cost
=∫∞
0
e−(ρ+δ)vu[c(v)]
u[c(t)]
Present value of future consumption
·h[M(v)]
β
Future marginal damages
dv
=q(t)
Opt. carbon price
.(5)
Expression (5) illustrates the cost–benefit approach to climate policy.
Emissions should be reduced up until the point where the marginal
abatement cost (i.e., the amount of consumption society has to give up
today to reduce emissions by one unit f[E(t)]) equals the present value
of marginal damages from emitting another ton, which corresponds to
the marginal abatement benefit. Evaluated at the optimal allocation, this
expression defines the optimal carbon pollution price q(t). Intuitively, setting
a carbon tax equal to q(t)dollars per ton ensures that firms and consumers
reduce their carbon emissions up until the point where their private marginal
abatement costs equal q(t), and thus the marginal abatement benefit.
Along with this transparent analytical illustration, Nordhaus introduced
quantifications of the elements in equations (2)–(4) as a second key
innovation. That is, rather than modeling the details of global energy
markets as he had done in previous work, Nordhaus now used the
results from those complex models to estimate a reduced-form abatement
cost function f[E(t)] that would be intuitive to understand and use.
Perhaps most significantly, Nordhaus introduced a first set of aggregate
climate change impact functions h[M(t)]. While the research available
to inform this quantification was extremely limited at the time, the paper
pioneered a way of thinking about the problem. Nordhaus’ approach, now
referred to as “enumerative”, compiled available impact estimates across
sectors, extrapolated them to unavailable countries and time periods, and
aggregated them into a damage function h[M(t)] (see also Section V).
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Here, Nordhaus utilized some of the first impact estimates for agriculture,
energy demand, health, and amenities as compiled by Ralph d’Arge for
the World Meteorological Organization’s First World Climate Conference
in 1979 (d’Arge, 1979). Nordhaus also produced original estimates for
sea level rise and its potential costs across different assumptions about
critical uncertainties, such as the fate of the West Antarctic ice sheet and
the pace of human adaptation. Throughout the paper, Nordhaus was careful
to emphasize that these estimates were highly preliminary. Indeed, he only
presented ranges of results “rather than give the spurious precision of a
single figure”.18
With these components, Nordhaus (1980) had built the first optimizing
climate–economy IAM.19 He translated the phenomenally complex problem
of managing a dynamically changing global climate from growing
greenhouse gas emissions into a transparent framework, distilling the core
trade-offs into components that researchers would study and modify for
decades to come (i.e., the “damage function”, the “abatement cost function”,
discounting parameters, etc.). In short, Nordhaus turned Pigouvian theory
into an actionable reality for the global climate.
Of course, the quantifications were still highly preliminary in 1980, and
with the benefit of another decade of climate change research, Nordhaus
(1991a) published an advanced iteration.20 In this paper, Nordhaus
presented a break-down of US gross domestic product (GDP) by sectoral
vulnerability to climate change, and combined these figures with newer
impact estimates to construct a revised damage function with a much
narrower range of 0.25–2 percent of GDP-equivalent loss associated with
3◦C warming. This “first serious and systematic effort to quantify economic
damages from climate change” quickly became “a benchmark or reference
point” to other studies (Toth, 1993). For example, Peck and Teisberg (1992)
used Nordhaus’ damage estimates to build an alternative optimizing IAM,
the CETA model, which they subsequently used to analyze issues such
as warming uncertainties and the value of information. Similarly, Manne
and Richels (1995) build on the Nordhaus (1991a) damage estimates
in deriving cost–benefit assessments for competing climate policies in
their MERGE model. Others followed Nordhaus’ enumerative approach
to construct additional aggregate damage estimates (e.g., Cline, 1992a;
Frankhauser, 1992). Of course, the most influential benchmark came with
18The resulting range was wide indeed, suggested that a doubling of CO2concentrations could
alter aggregate consumption by −12 to +5 percent.
19Of course, the results of this optimizing model represent a competitive equilibrium outcome,
given appropriate prices and policies.
20A summary of the Cowles Foundation working paper (Nordhaus, 1980) was published in
Nordhaus (1982).
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the first iteration of the DICE model (Nordhaus, 1992, 1993a,b, 1994a),
which contained advanced damage estimates and has served as a basis for
countless studies, as described below. Before proceeding, however, we note
three points.
First, beyond his modeling work, Nordhaus has also contributed directly
to the climate change impact estimation literature, employing diverse
approaches ranging from expert elicitations (Nordhaus, 1994b) to the
estimation of hurricane wind speed impact (Nordhaus, 2010b). Among the
most influential is a paper written jointly with Robert Mendelsohn (a former
Nordhaus student who also became a leader in environmental and climate
economics) and Daigee Shaw (an environmental economist who had visited
the Yale School of Forestry and Environmental Studies). Mendelsohn et
al. (1994) developed a novel “Ricardian” approach to evaluating climate
impacts on agriculture, which encapsulated two core insights. (i) While
it was common to project yield losses for specific crops (e.g., corn)
based on changes in ambient conditions, they noted that farmers could be
expected to switch crops as the climate changes, mitigating income losses
compared with what crop-specific damage assessments would suggest. (ii)
The productivity value of climatic conditions should be capitalized into
the prices of agricultural land. The Ricardian approach thus uses cross-
sectional variation to infer the impacts of long-run climate on agricultural
productivity. Though subject to intense debate to this day, the Ricardian
approach has been extensively applied, and the study remains extremely
influential.
Second, both scientific and policy attention towards climate change
expanded rapidly during the 1980s. Nordhaus was involved in key work
at this nexus. While there had already been high-level discussions of
climate change in the US policy realm (e.g., Tukey et al., 1965), two
influential reports released in 1979 brought the issue further into the
limelight.21 Spurred by these reports, the US Congress tasked the National
Academy of Sciences with investigating the implications of fossil fuel
combustion and carbon dioxide build-up in the atmosphere through the
Energy Security Act of 1980 (Nierenberg et al., 2010).22 Nordhaus served
on the resulting Carbon Dioxide Assessment Committee. Their landmark
report, released in 1983, provided comprehensive reviews on climate science
and climate change impacts, including impacts on agriculture and water
supplies. Nordhaus further presented two chapters detailing estimates of
21One report was written by a group of eminent physicists of the JASON defense advisory panel
(MacDonald et al., 1979). The other was an ad hoc study by the National Academy of Sciences
(Charney et al., 1979).
22See “Getting to know Bill Nordhaus and Climate” by Jesse Ausubel, https://phe.rockefeller.
edu/news/wp-content/uploads/2019/01/Nordhaus- and-Climate-Jesse- recollection3.pdf .
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future greenhouse gas emissions. One was based on a detailed review
of the literature conducted with Jesse Ausubel, a fellow IIASA alumnus
and a global leader in advancing climate research programs (Ausubel
and Nordhaus, 1983). The second (Nordhaus and Yohe, 1983) was based
on original modeling and data analysis joint with Gary Yohe, a former
Nordhaus student who would also become a leader in the field, and later
served as lead author at the IPCC. This forecasting work would also form
the basis for the first DICE treatment of future population and productivity
growth uncertainty.
Third, over the coming years, an increasing number of energy–economy
and computational general equilibrium models began to account for
greenhouse gas emissions (e.g., Edmonds and Reilly, 1983; Manne and
Richels, 1990; Jorgensen and Wilcoxen, 1990); for reviews, see Nordhaus
(1991b) and Gaskins and Weyant (1993). At this point, we shall also
note the pioneering role that some of these modelers had played in first
integrating energy systems into economic growth models, with Alan Manne
(1977) serving as an early example (see also the discussion in Nordhaus,
2013). Now, these models typically included highly detailed representations
of the energy sector and could be used to simulate, for example, the costs
of greenhouse gas emissions reductions. Some environmental simulation
models also began to consider socioeconomic climate change impacts, with
Rotmans (1990) serving as an early example. While these were not cost–
benefit integrated assessment models, it was not long until other researchers
introduced such models, including many that remain influential today, such
as PAGE (e.g., Hope et al., 1993) and FUND (e.g., Tol, 1997; Anthoff and
Tol, 2008); see early reviews by Kelly and Kolstad (1999b) and Weyant
et al. (1996). Back then as now, these models often take a very different
approach from Nordhaus as they are highly disaggregated and not based on
macroeconomic growth models. That is, many early IAMs took economic
growth as exogenous and did not model dynamic equilibrium.23 While this
set-up permits the simulation of emissions and impacts across a detailed set
of sectors, it has the disadvantage of lowering the models’ transparency and
portability into other macroeconomic frameworks and settings. As explained
by Nordhaus (2013a):
23Of course, there were early exceptions. For example, Scheraga et al. (1993) incorporate several
sectoral climate impacts (e.g., agricultural production cost increases) into the computational
general equilibrium model of Jorgenson and Wilcoxen. The aforementioned CETA and MERGE
models are also dynamic equilibrium frameworks. In later years, many more neoclassical growth
model-based IAMs were developed, often building on DICE directly or indirectly, as discussed in
Section V. See also later literature reviews such as Nordhaus (2013a), Weyant (2017), and Hassler
et al. (2016).
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“A useful analogy here is to the animal kingdom. Each model is
like an animal that has its useful niche in the policy ecosystem.
Small models can be fleet and can adapt easily to a changing
environment, while large models take many years to mature but
are able to handle much larger and more complex tasks. There
is room for all in the world of climate change science.”
In sum, while there was rapid entry of computational modelers into
the energy–economy–climate nexus in the early 1990s, the need for
a transparent growth-model based climate–economy–optimization model
remained, leaving DICE to become a keystone species.
V. DICE
Model Overview
“ ‘God does not play dice with the universe’ was Albert
Einstein’s reaction to quantum mechanics. Yet mankind is
playing dice with its natural environment.” (Nordhaus, 1994a)
In 1992, Nordhaus published the first version of the influential DICE
model. It is based on a standard neoclassical (Ramsey–Cass–Koopmans)
growth model, but adds the three key ingredients of (i) endogenous
greenhouse gas emissions from economic activity, (ii) a carbon cycle and
climate system representation, and (iii) climate change impacts on the
economy. The model arguably exemplifies Albert Einstein’s principle that
“[e]verything should be made as simple as possible, but not simpler”.24 At
this point in time, Nordhaus already had 20 years of experience in working
with energy–economy and energy–climate models, and he had been at the
forefront of the literature as it developed. This experience enabled him to
make very deliberate choices about the relevant levels of detail to include,
which would prove to be of enduring value.
We now review the central equations of the DICE model. We focus on
the 2008 version as a compromise between the earliest and latest versions;
see Nordhaus (2018a) for a review of DICE model changes over time. First,
aggregate global output Q(t)is produced with a standard Cobb–Douglas
technology using capital K(t)and labor L(t)inputs:
Q(t)=Ω(t)[1−Λ(t)]A(t)K(t)γL(t)1−γ.(6)
24While this quote is commonly attributed to Einstein, it is not actually clear whether he said those
words as such. A closely related confirmed quote reads more specifically that “[i]t can scarcely
be denied that the supreme goal of all theory is to make the irreducible basic elements as simple
and as few as possible without having to surrender the adequate representation of a single datum
of experience” (Robinson, 2018).
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Available output further depends on total factor productivity A(t), on climate
change impacts via Ω(t), and on greenhouse gas abatement expenditures via
Λ(t), both described below. Net output Q(t)can be used for consumption
C(t)or investment I(t):
Q(t)=C(t)+I(t).(7)
Capital accumulates based on investment and the prior capital stock net of
depreciation δk:
K(t)=(1−δk)K(t−1)+I(t−1).(8)
In lieu of the detailed energy sector modeling in Nordhaus’ early work,
economic activity in DICE is linked to industrial greenhouse gas emissions
in a “reduced-form” way. On the one hand, there is a baseline emissions
intensity σ(t), which reflects the economy’s current and expected future
emissions per dollar of GDP in a business-as-usual scenario. This parameter
can be calibrated to match competing predictions of future autonomous
energy efficiency improvements. On the other hand, a fraction μ(t)of
emissions can be abated through implicit investments in appropriate
technologies. Net industrial emissions EInd(t)are thus given by
EInd(t)=[1−μ(t)]σ(t)Q(t).(9)
The limited nature of fossil fuel resource endowments is further captured
with a constraint that cumulative carbon usage cannot exceed CCum:
CCum ≥EInd(t).(10)
Next, the total costs of emissions reductions μ(t)are specified as a fraction
of aggregate output Λ(t)via
Λ(t)=π(t)·θ1(t)μ(t)θ2.(11)
Intuitively, the higher the fraction of emissions avoided (e.g., μ(t)=0.5
implies an emissions reduction of 50 percent), the higher the fraction of
GDP that must be spent on abatement, Λ(t). The parameters θ1(t)and θ2
governing the shape of this function are estimated based on the results
of detailed quantitative energy–economy models and on cost estimates for
specific technologies. The variable π(t)shifts abatement costs in the case
of incomplete participation in global climate policy. Intuitively, the costs
of reducing global emissions by a given amount are considerably higher if
this abatement is undertaken by a few countries rather than spread across
many nations. Letting ϕ(t)denote the climate policy participation rate, π(t)
is thus specified as
π(t)=ϕ(t)1−θ2.(12)
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Net industrial emissions EInd(t)and exogenous land-based emissions
ELand(t)then enter the carbon cycle through the atmosphere. The 2008
version of DICE tracks three carbon reservoirs: the atmosphere AT , the
upper ocean and biosphere UP, and the lower ocean LO, with coefficient
matrix φgoverning transfer rates between reservoirs:
MAT (t)
MUP(t)
MLO(t)
=
φ11 φ21 0
φ12 φ22 φ32
0φ23 φ33
MAT (t−1)
MUP(t−1)
MLO(t−1)
+
EInd(t)+ELand(t)
0
0.(13)
One of the important innovations of the DICE model compared with
Nordhaus’ earlier work was that it featured not only the carbon cycle,
but also the climate system. That is, the DICE model introduced a
final link from atmospheric carbon concentrations to global temperature.
Nordhaus’ approach built closely on the Schneider–Thompson climate
model (Schenider and Thompson, 1981), which represented temperature
dynamics across layers such as the atmosphere and the ocean through a
parsimonious set of equations. Formally, in DICE, increases in atmospheric
carbon MAT (t)lead to an increase in the Earth’s net radiative energy
balance, or radiative forcing F(t)(measured in watts per square meter),
as first noted by Arrhenius (1896):
F(t)=ηlog2MAT (t)
MAT (1750)+FEX(t).(14)
Here, FEX(t)denotes exogenous forcings, such as from aerosols and
certain chemicals (e.g., chlorofluorocarbons), and ηis a parameter. Finally,
increased forcings raise atmospheric temperatures TAT (t). DICE models this
process along with ocean temperatures TLO(t)in order to capture heat
exchange between the atmosphere and upper ocean and the deep ocean,
and the resulting warming delays:
TAT (t)
TLO(t)=(1−ξ1ξ2−ξ1ξ3)ξ1ξ3
(1−ξ4)ξ4TAT (t−1)
TLO(t−1)
+ξ1F(t)
0.(15)
Here, ξare parameters governing heat transfer rates. Next, a critical
element of integrated assessment is that atmospheric warming TAT (t)links
back to the economy and human welfare via the impact function Ω(t),
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which is specified as
Ω(t)=1
1+π1TAT (t)+π2TAT (t)2.(16)
The quantification of the damage function has evolved considerably over
the years as more research has become available. Consider agricultural
impacts. Early estimates were only available for the United States. The
synthesis by Nordhaus (1994a) suggested a benchmark estimate of around
5 percent of agricultural output lost from atmospheric CO2doubling. He
extrapolated to other countries by econometrically estimating the association
of per capita GDP and agricultural output shares, and by combining these
estimates with future GDP growth projections for each country. In contrast,
within a few years, agricultural impact estimates had become available for
a wider range of countries and regions, permitting Nordhaus and Boyer
(2000) to utilize local estimates in an updated damage function calibration.
The latest iterations of DICE aggregate overall impact estimates statistically
across a detailed review of the literature (Nordhaus, 2017; Nordhaus and
Moffat, 2017). In DICE 2016, the income-equivalent25 loss from a doubling
in CO2concentrations corresponds to 2.1 percent of global GDP (Nordhaus,
2017). If this figure seems modest, it might be useful to remember that
world GDP declined by “only” 1.73 percent during the Great Recession of
2009.26
The final element of DICE is its objective or social welfare function,
which is specified as the present value of the population L(t)-weighted
utility U(.)over per capita consumption c(t)≡C(t)/L(t):
W≡
t
U[c(t),L(t)](1+ρ)−t
=
t
L(t)[c(t)]1−α−1
1−α(1+ρ)−t.(17)
Here, αcaptures the degree of curvature in the utility function, and
ρdefines the pure rate of social time preference. Both are highly
consequential parameters for climate policy as they reflect the rate at
which society is willing to trade off consumption in the present versus the
future and across generations with different levels of income. The DICE
model calibrates these parameters to match empirically observed savings
25One important point to note is that DICE seeks to include estimates of non-market costs and
ecosystems losses in quantifications of equation (16), if largely by assumption due to the lack of
quantitative evidence.
26Of course, the disruptive nature of these events is not comparable. The Great Recession involved
a sudden year-on-year decline in GDP levels, whereas Ω(t)corresponds to a reduction in GDP-
equivalent relative to its potential in the absence of climate change.
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and interest rates so as to reflect both society’s revealed preferences and
the opportunity cost of investing in climate abatement over alternative assets
(e.g., health research, tech start-ups, etc.). As is well known, this approach
is not without its critics (e.g., Stern, 2007), and DICE has also been used
to study alternative approaches, as discussed below.
In full optimization mode, DICE then effectively maximizes equation
(17) subject to constraints (6)–(16) by choice of capital investments I(t)and
abatement rates μ(t). The model can also be run in business-as-usual mode
with no controls on carbon emissions (μ(t)=0), or in cost-effectiveness
mode to identify the least-cost way of achieving an additionally specified
policy goal, such as keeping temperature change below 2◦C. As is standard,
the resulting primal solution for the optimal allocation can be decentralized
as a competitive equilibrium through appropriate choices of prices and
policies. The optimal carbon tax at each point in time, then, is simply
the marginal abatement cost evaluated at the desired abatement level
μ∗(t)or, equivalently, the social cost of carbon as defined in equation
(5).27 Of course, the optimal allocation can also be decentralized by an
appropriately designed emissions trading scheme. Beyond these basic runs,
DICE can also be used to study a wide range of questions ranging from
the welfare costs of delaying emissions reductions to the implications of
clean energy innovations. As the benchmark results of DICE are both
broadly familiar and best described by Nordhaus himself, we now turn
the discussion towards extensions done by Nordhaus and others, and on the
enormous influence of DICE in research and beyond. As noted by Dietz
and Stern (2015): “To look only at Nordhaus’s own studies with DICE
is to understate its contribution hugely, because, by virtue of its simple
and transparent unification of growth theory with climate science (not to
mention Nordhaus’s considerable efforts to make the model code publicly
available), it has come to be very widely used by others.”
Extensions and Influence
The unparalleled power of DICE as a basis for new research was apparent
from the start. As its first iteration was published (Nordhaus, 1992),
Kolstad (1993, 1994) had already built a model based on DICE to study
uncertainty and learning about climate change (the “SLICE” model). Even
Cline (1992b), who disagreed with aspects of Nordhaus’ approach, used
27To be clear, the optimal tax is not equal to the social cost of carbon if the latter is evaluated at a
suboptimal allocation. In addition, marginal abatement costs as defined by equation (5) have an
upper bound in DICE at μ=100 percent. At this point, the present value of marginal damages
can diverge from the marginal abatement cost and, thus, the minimum tax required to implement
the optimal allocation.
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the DICE model to formalize his arguments. Over the years, practically
every element of DICE has been tested and extended by the literature, and
countless studies have stood on its shoulders to investigate a kaleidoscope
of questions. To give a sense of the richness of this influence, we now
survey some examples.
Before proceeding, we stress that the following subsections highlight
examples of the DICE model family in furthering the literature and do not
constitute a general review. Even with this focus, there are thousands of
studies citing and building on DICE. Apologies are thus extended to the
many whose excellent work cannot be referenced here.
Uncertainty. While the DICE model is deterministic, it has enabled
researchers to make significant progress towards understanding the vast and
varied uncertainties that affect the climate problem. First, the comparatively
small size of DICE permits extensive Monte Carlo analyses to assess the
significance of uncertainty over each of its elements. Nordhaus (1994a)
already devotes three out of eight book chapters to uncertainty. Nordhaus
has continually produced dedicated analyses on this topic, including a
probabilistic PRICE model extension (Nordhaus and Popp, 1997), updated
uncertainty analyses with new DICE iterations (e.g., Nordhaus, 2008),
and recently also a multimodel comparison together with five other IAMs
(Gillingham et al., 2018).
On the one hand, these analyses illuminate the key sources of
uncertainty afflicting our predictions of the future. For example, Gillingham
et al. (2018) find that uncertainty over future economic growth is a
significantly larger contributor to uncertainty over model outcomes than
uncertainty over the equilibrium climate sensitivity or population growth.
Another surprising result of this multimodel comparison is that parametric
uncertainty dominates model uncertainty. That is, what we collectively
do not know as a modeling community constitutes a larger source of
uncertainty than the differences between our models.
On the other hand, these analyses have also illustrated the various
channels through which uncertainty can affect climate policy design.
For example, uncertainty about future climate change and damages
renders stricter policy more desirable as insurance against worse outcomes
(Nordhaus, 1994a). At the same time, if the states of the world where
climate damages are unexpectedly high are also states of the world in
which consumption levels are high (e.g., because of high future productivity
growth), then this insurance value is diminished (Nordhaus, 2008).28
28This question of the “climate beta” has received increasing attention in the literature. See, for
example, Dietz et al. (2018) for a recent analysis building on DICE.
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Another consideration is the option value of waiting to learn more about
climate change. Kelly and Kolstad (1999a) build on DICE to highlight
this channel in a stochastic dynamic programming (SDP) extension with
Bayesian learning over the climate’s sensitivity to carbon dioxide, finding
ambiguous net impacts on optimal policy. Several recent studies have
developed SDP extensions of DICE, and have documented similarly
nuanced results.29 For example, Jensen and Traeger (2014) find that the
impacts of output growth uncertainty on the optimal carbon price differ
considerably depending on whether preferences are as in equation (17) or
Epstein–Zin (Epstein and Zin, 1989; Weil, 1990). Crost and Traeger (2014)
similarly find that the effects of damage function coefficient uncertainty
can differ depending on whether the level or curvature of equation
(16) is uncertain. DICE has also been used to study specific damage
function uncertainties such as “tipping points” in the climate system.
While Nordhaus (1980) already considered optimal climate policy with
known tipping points, Lemoine and Traeger (2014) do so in a stochastic
framework; see also the “DSICE” model analysis of Cai et al. (2018),
which considers climate and economic uncertainty jointly.30 Newer work
has further considered richer sets of uncertainty. For example, Rudik
(2019) introduces a DICE-based robust control framework that allows for
consideration of structural damage function uncertainty and unknown model
misspecification. Perhaps surprisingly, these are found to have only modest
effects on optimal climate policy. Finally, other studies have used DICE
to investigate more specific issues such as the consumption discounting
implications of interest rate uncertainty (Newel and Pizer, 2003). In sum,
while the literature does not yet provide harmonized answers to how
different types of uncertainty should alter climate policy design (Lemoine
29A fundamental trade-off between the Monte Carlo and SDP approaches is as follows. On the
one hand, Monte Carlo analyses can simultaneously consider uncertainty over many if not all
model parameters, whereas SDP frameworks have traditionally only been able to consider one
or two sources of uncertainty at a time (see Lemoine and Rudik, 2017). On the other hand, SDP
models formally capture decision-making under uncertainty, whereas Monte Carlo analyses do
not (Crost and Traeger, 2013). Thus, several scholars have also innovated mixed approaches. For
example, Nordhaus and Popp (1997) utilize results from a sophisticated Monte Carlo analysis
to summarize uncertainty over all parameters into five “states of the world”, which they then
consider in an SDP (expected utility maximization) variant of DICE, the PRICE model. Another
example, Pizer (1999), utilizes an analytical approximation to household decision-rules in order
to consider a broader range of uncertainty in an SDP extension of DICE.
30At the extreme, Weitzman (2009) and others have raised concerns over cost–benefit climate
policy analyses not accounting for “fat tails”. Recent work seeking to incorporate the possibility
of extreme parameter realizations in DICE suggests that a combination of both extremely high
temperature sensitivity and climate damage sensitivity in a no-policy scenario are required to
produce catastrophic outcomes (e.g., Ackerman et al., 2010; Nordhaus, 2013a).
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and Rudik, 2017), it does illustrate the power of DICE as a foundation for
these important investigations.
EndogenousTechnical Change. While the DICE model treats technological
change as exogenous, it has enabled researchers to consider competing
specifications of endogenous technological change (ETC), building also
on the work of fellow 2018 Nobel Laureate Paul Romer. Two important
advantages of DICE in this realm are that its tractability facilitates
appropriately extensive sensitivity analyses given the high degree of
uncertainty in quantifications of ETC, and that it allows for both cost-
effectiveness and cost–benefit analysis of climate policy. Goulder and
Mathai (2000) introduce two types of ETC (i.e., R&D investments and
learning-by-doing) into a DICE-based framework. They find that the
resulting policy implications might be large for cost-effective carbon taxes,
but are modest for optimal climate policy. Intuitively, ETC might lower
the carbon tax necessary to meet a given emissions reduction target, but it
might also increase the optimal abatement level, thus having a smaller net
effect on optimal carbon pricing. Nordhaus (2002) finds similar results in
introducing the R&DICE model, which allows firms to lower the carbon
intensity of production σ(t)through R&D expenditures. While this form
of ETC contributes to emissions reductions, its effects are quantitatively
modest. At the same time, Nordhaus notes the importance of market failures
due the divergence of private and social returns to research. Popp (2004)
confirms these general findings in the ENTICE model, which also builds
on DICE but incorporates ETC in a richer set of ways. David Popp, a
former Nordhaus student, has become a leader in this field, contributing
to both modeling and empirical advancements of ETC (e.g., Popp, 2002).
Despite these consistent early results, many questions remain unanswered,
and the nexus of ETC and climate policy remains a highly active area
of research (see the review by Gillingham et al., 2008). Relevant to the
present discussion, influential recent work such as that by Acemoglu et
al. (2012) – which allows for directed technical change in both dirty and
clean inputs, and finds a significant role for clean energy research subsidies
– has continued to build on Nordhaus’ work for core specifications and
quantifications.
Spatial Heterogeneity. DICE is a global model that aggregates climate
impacts, policies, and factors across countries. Though tractable, a global
framework provides limited insights into regionally differentiated climate
policies, such as the landmark Kyoto Protocol (in 1997), an international
agreement of a select group of countries to reduce their greenhouse gas
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emissions. Nordhaus thus developed the RICE (Regional Integrated Model
of Climate and the Economy) model, a multiregion version of DICE,
in collaboration with his former student and climate change economist
Zili Yang (Nordhaus and Yang, 1996). They used the model to compare
climate outcomes and welfare across regions under business-as-usual, non-
cooperative (Nash equilibrium), and idealized cooperative climate policy
regimes. In updated versions, including joint work with Joseph Boyer
(Nordhaus and Boyer, 2000), Nordhaus used variants of RICE to analyze
international agreements such as the Kyoto Protocol (Nordhaus and Boyer,
1999) and the Copenhagen Accord (Nordhaus, 2010a). More recently,
Nordhaus built on RICE to develop an international coalition-building
model and to introduce the concept of “climate clubs”, as described below
(Nordhaus, 2015).
Despite its richness, the RICE model is again sufficiently transparent
and accessible that it has been used extensively by others. Scholars have
utilized RICE to analyze climate policy implications of issues such as
inter-regional inequality aversion (Anthoff and Emmerling, 2019), age-
specific demographics (Fenichel et al., 2017), and technological change with
spillovers (e.g., the FEEM–RICE model by Bosetti et al., 2006; Buonanno
et al., 2003). Hassler and Krusell (2012) extend RICE in a decentralized
equilibrium setting and study carbon leakage in oil markets from regional
climate policies. Leading new work by Krusell and Smith (2018) formalizes
the heterogeneous agent representation and considers a much finer degree of
spatial disaggregation than RICE, but also builds on Nordhaus’ work in its
general approach and in relying on the G-Econ spatial economic database
(Nordhaus et al., 2006).
One particularly innovative new development based on RICE is
Nordhaus’ analysis of “climate clubs”. While serving as President of the
American Economic Association, Nordhaus began his 2015 presidential
address by noting that international free-riding remains the most vexing and
unresolved aspect of climate change. As a potential mechanism to overcome
this classic public goods problem, Nordhaus proposed a “climate club”,
which would consist of two parts: (i) an agreement by a group of countries
to undertake emissions reductions through a harmonized carbon price, and
(ii) a penalty jointly levied upon non-participating countries in the form of
a small uniform percentage tariff.31 In order to investigate the viability of
such a scheme, Nordhaus developed the Coalition-DICE (C-DICE) model,
31Some prior literature and policy discussions have considered “carbon tariffs” based on the
carbon content of imported goods. In theory, such a duty would level the playing field and
alleviate trade disadvantages for countries adopting carbon pricing. However, Nordhaus (2015)
notes that “studies of carbon duties indicate they are complicated to design, have limited coverage,
and do little to induce participation”.
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which is based on RICE and designed to analyze coalition stability with
such trade levies. The results are remarkable: all regions would find it
advantageous to join a climate club with a harmonized carbon price of $25
per ton CO2given non-participation penalties as low as a 3 percent tariff.
The net economic benefits associated with climate clubs are enormous,
potentially of the order of hundreds of billions of dollars.
While some might be quick to question the legal and political viability
of such tariffs, it should be noted that many policies of today would have
been unthinkable in the not-too-distant past. “What is toxic or opposed in
one generation gradually becomes accepted in the next. Social security took
a long time. It was opposed for many, many decades but since Reagan it
has been widely accepted,” Nordhaus commented in a recent interview.32
Broader Literature. The broader literature builds on Nordhaus’ work in
myriad ways across multiple fields and generations. On the one hand,
there is a wealth of literature directly extending DICE, with applications
spanning topics as diverse as overlapping generations (e.g., Howarth, 1998;
Leach, 2009), limited substitutability between environmental and market
goods (Sterner and Persson, 2008), carbon tax interactions with fiscal policy
(Barrage, 2019), disagreement about discount rates (Heal and Millner,
2014), and climate policy design from the perspective of policy-makers
who are agnostic about climate science (Rezai and van der Ploeg, 2019).
On the other hand, Nordhaus’ work has informed the development of
other IAMs, which have, in turn, spawned further academic offspring.
For example, the analytically tractable decentralized equilibrium climate–
economy model of Golosov et al. (2014) builds on DICE in numerous ways,
and has itself become highly influential as a basis for other studies. Finally,
macroeconomics as a field has come to recognize the importance of climatic
and environmental processes. Growth scholars ranging from Acemoglu et al.
(2012) to Brock et al. (2014) and Desmet and Rossi-Hansberg (2015) have
followed Nordhaus in integrating climate change into their growth models.
Indeed, “Environmental Macroeconomics” now features as a chapter in the
Handbook of Macroeconomics, based on the foundations of Nordhaus’ work
(Hassler et al., 2016). In sum, whether directly or indirectly, a prodigious
body of literature thus ultimately stands on Nordhaus’ shoulders.33
32See the article “After Nobel in Economics, William Nordhaus Talks About Who’s Getting His
Pollution-Tax Ideas Right” by Coral Davenport, in the New York Times, 13 October 2018 (https://
www.nytimes.com/2018/10/13/climate/nordhaus-carbon-tax-interview.html).
33Of course, we must also acknowledge the vast number of IAMs that have been independently
developed by research teams around the world over the past years; see, for example, newer reviews
by Nordhaus (2013a), Weyant (2017), and Clarke et al. (2009).
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Policy Impacts
Taking a step back, we recall that Nordhaus initially diagnosed the lack
of a carbon price as an impediment to sustainable long-run growth. He
worked for decades to produce a transparent, credible, and widely applied
framework that could quantify this missing carbon price (i.e., the SCC
estimates). As of 2018, an estimated 46 countries and 24 subnational
jurisdictions have levied a price on carbon emissions (World Bank, 2018),
and 17 out of 23 OECD countries recently reported using SCC values in
public cost–benefit analyses (Smith and Braathen, 2015). Even beyond the
idea of carbon pricing, Nordhaus’ work is too influential as a fundamental
way of thinking about the climate problem to trace out his policy impacts
comprehensively. As is well known – including from other work by
Nordhaus and his fellow 2018 Nobel Laureate Paul Romer – the social
returns to research and new ideas greatly exceed the credit that innovators
privately receive.
For a recent example of this continued general influence, consider the
European Union’s debate about whether and how to adjust its greenhouse
gas emissions trading scheme in the wake of the 2009 financial crisis. The
European Economic and Social Committee (EESC) eventually issued the
following official opinion:34
“There is a broad consensus that setting an appropriate,
generally accepted price on carbon is key to a successful climate
change policy (William D. Nordhaus, Economic Issues in a
Designing a Global Agreement on Global Warming). If the
price of carbon is not set appropriately and is not generally
accepted, it cannot have an incentivising effect. [...] Therefore
the EESC calls on the European Commission to present options
to strengthen the EU ETS, and consistent measures in the non-
ETS sectors.”
Beyond this broad influence of Nordhaus’ ideas, his specific research
findings have also contributed to international climate policy compendia
such as the UK Stern Review on the Economics of Climate Change (Stern,
2007) and the Intergovernmental Panel on Climate Change’s Assessment
Reports (IPCC, 2001, 2007, 2014).
Most directly, the US Government has used DICE to value the social
cost of carbon for regulatory impact analysis. After the US Supreme Court
ruled in 2007 that carbon dioxide and other greenhouse gases should be
regulated as “air pollutants” under the US Clean Air Act, there was no
34Opinion of the European Economic and Social Committee on “The impact of the crisis on the
ability of European firms to undertake pro-climate investments”, 2012/C 24/02.
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established figure for how to value these emissions in regulatory impact
analyses (Nordhaus, 2014). Several rule-makings in 2009 relied on a review
by Tol (2005), which already included several SCC estimates by Nordhaus
and co-authors (listed in the Appendix). In 2010, an Interagency Working
Group (IWG) was formed to produce a harmonized set of SCC estimates
for use by the US federal government (Greenstone et al., 2013). Their
analysis used DICE along with two other IAMs: the PAGE model by Hope
(2006) and Hope et al. (1993), and the FUND model by Tol (1997) and
Anthoff and Tol (2008, 2014). By our accounting, these and the survey-
based SCC estimates have been used in regulatory impact analyses for over
70 US final rule-makings to date (listed in the Appendix). While the Trump
Administration has disbanded the IWG (Executive Order 13793, 2018), its
SCC estimates are still used to inform climate policy design.35 First, several
US states have used the IWG SCC estimates. For example, the public utility
commissions of several states, such as those of Colorado and Minnesota,
have adopted IWG SCC figures in their proceedings and resource planning
(Paul et al., 2017). California’s Air Resources Board is using the IWG
SCC figures in its climate policy planning, and both Illinois and New York
have used the IWG SCC figures in setting subsidy rates for zero-emissions
electricity. Second, other countries such as Canada have adopted modified
versions of the IWG SCC figures for regulatory impact analysis.36 Finally,
several federal US carbon tax policy proposals introduced in Congress have
been based on the IWG SCC figures, highlighting their continued policy
relevance going forward.37
VI. Conclusion
“We need to approach the issues with a cool head and a warm
heart. And with respect for sound logic and good science.”
(Nordhaus, 2012a)
35One contentious issue is whether the United States should consider only domestic or global
impacts of its regulations. The IWG had focused on the global SCC, whereas the Trump
Administration has posited an alternative value for the domestic SCC in its regulatory impact
assessments (see the Regulatory Impact Analysis for Review of the Clean Power Plan: Proposal,
US Environmental Protection Agency, October 2017).
36For example, the Policy on Cost–Benefit Analysis, Treasury Board of Canada Secretariat,
Government of Canada (2018). For a survey of other countries’ uses of SCC values in cost–
benefit analysis, see Smith and Braathen (2015).
37The American Opportunity Carbon FeeAct (S.2368) is directly motivated by the IWG estimates
(Whitehouse, 2017). Other recent proposals consider carbon prices in the relevant $15 to $50
range (Ye, 2018).
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910 The Nobel Memorial Prize for William D. Nordhaus
In 2019, the world finds itself at a divisive moment. In the United
States, President Trump has denounced climate change as “a hoax”, while
Democrats in Congress are pushing for a “Green New Deal” of aggressive
measures striving to eliminate greenhouse gas emissions within a decade. At
first glance, one may wonder how much has really changed since Nordhaus’
1977 description of debates about the environment and the economy as
“divided between one group crying ‘wolf’ and another which denies that
species’ existence”. Beneath the surface, however, there have been tectonic
shifts of progress emanating from the scientific community. Here, we
conclude by reviewing Nordhaus’ contributions to elevating scholarly and
public debates to higher levels of rigor and openness, and to fostering a
shared understanding of the issues.
First, since Nordhaus introduced the idea of carbon taxes in 1977,
economists from across the political spectrum have come to support carbon
pricing with unique levels of agreement and enthusiasm. A bipartisan group
of over 3,500 economists recently issued a formal statement in support of
carbon pricing in the United States, including numerous former Chairs of
the US Federal Reserve and of the Council of Economic Advisers.38
Second, while significant disagreements remain among economists about
the appropriate level for such prices and the social cost of carbon, Nordhaus
has led the literature by example through in-depth engagements with
alternative points of view. Consider, for example, the critique of utility
discounting of future generations as unethical by Stern (2007) – that is, ρ
in equation (17) – or the “Dismal Theorem” critique by Weitzman (2009)
that “fat-tailed” risks render the climate problem unsuitable for cost–benefit
analysis. Nordhaus not only wrote dedicated analyses carefully responding
to these ideas (Nordhaus, 2007, 2009), but he has also maintained an
academic dialogue with them throughout his subsequent work.39 In his
official Nobel Lecture, Nordhaus added: “A special word of thanks to my
critics, because those are the people you learn from the most.”40
At its core, this serious engagement with new ideas, findings, and
opposing points of view reflects Nordhaus’ core desire to get things right,
earning him a reputation for being “careful and apolitical” (Gillingham,
38See the Economists’ Statement on Carbon Dividends, available on the Climate Leadership
Council website, https://www.clcouncil.org/economists-statement/.
39For example, Nordhaus routinely reports “Stern Review discounting” scenarios along with
standard DICE model results (e.g., Nordhaus, 2017), and has devoted entire book chapters
to scholarly engagement with Stern’s perspective (e.g., Nordhaus, 2008). Nordhaus has also
repeatedly returned to the question of “fat tails” in his analyses of uncertainty and climate change,
such as by studying under which parametric and policy scenarios catastrophic risks might arise
(e.g., Nordhaus, 2013a; Gillingham et al., 2018).
40Transcribed from the Nobel Lecture video available from Nobel Media at https://www.
nobelprize.org/prizes/economic-sciences/2018/nordhaus/lecture/.
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2018). A third contribution in this regard is that Nordhaus has continually
pushed the literature towards transparency and critical self-assessments. In
recent work, he shines a light both on the prediction errors in his own
past work (Nordhaus, 2018a), and on thorny questions about computational
complexity and errors in the broader literature (Nordhaus, 2012b). In
Gillingham et al. (2018), Nordhaus joins forces with several IAM modeling
groups in order to push the frontier on multimodel comparisons so as to
illuminate key uncertainties afflicting our projections of the future.
Fourth, Nordhaus has also led by example in engaging with climate
change skeptics. Responding to a Wall Street Journal editorial entitled
“No Need to Panic About Global Warming”, Nordhaus wrote a pointed,
fact-based response, “Why the Global Warming Skeptics Are Wrong”
(Nordhaus, 2012a), which quickly became a sensation in itself. One of
the misleading claims by the skeptics pertained to Nordhaus’ work and the
costs of delaying climate policy for 50 years. In response, Nordhaus created
a dedicated Excel version of the RICE model and posted it to his website
with instructions for anyone to run the model and see for themselves.41 This
episode again demonstrates the power of Nordhaus’ transparent approach as
a teaching tool, and universities from around the world have incorporated
Nordhaus’ work into their curricula.42 Nordhaus’ response further illustrates
his desire to be open, fact-based, and rigorous. “The history of science
tells us that we need to be alert to the possibility of allowing a false
consensus,” he wrote in Nordhaus (2013b). “The correct response to critics
is to look carefully at their arguments and determine whether they do indeed
undermine standard theories. Scientists and economists need to confront
contrary arguments with the same vigor with which they argue for the
validity of their own approaches.”
Finally, it should be clear at this point that Nordhaus has led the
way in building bridges between the natural and economic sciences. The
Nobel Prize announcement commended that he “significantly broadened
the scope of economic analysis by constructing models that explain how
the market economy interacts with nature” (Royal Swedish Academy of
Sciences, 2018). Importantly, however, Nordhaus has continued to lead in
this engagement, noting that the “findings [of our models] must be qualified
and constantly updated because of the uncertainties involved at all stages”
41Though no longer available on Nordhaus’ website, the Internet Archive (Wayback Machine)
snapshot of his website from 21 July 2012 features the link to the RICE, “Model available for
NYRB readers (March 2012)”, as can be seen at https://web.archive.org/web/20120721224053/
http://www.econ.yale.edu/∼nordhaus/homepage/RICEmodels.htm.
42For example, Nordhaus’ response to the skeptics’editorial can be found on syllabi ranging from
MBA courses (Slaughter, 2014) to undergraduate courses on climate change economics (e.g.,
Bosetti, 2018) and MPA courses at policy schools (e.g., Pizer, 2018).
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(Nordhaus, 2013b). To this end, for example, the latest version of DICE
incorporates a novel representation of Greenland ice sheet dynamics that
can account for hysteretic or irreversible effects of a rise in sea level
(Nordhaus, 2018b).
As noted at the beginning of this article, the rich and ever-expanding
literature on the economics of climate change and sustainable growth now
feature many studies that incorporate climatic processes into economic
analyses. At this point, however, the ubiquity of this approach shall leave no
doubt about the enormity of its contribution, which we owe to the curiosity,
brilliance, and scholarship of William D. Nordhaus.
Appendix
Table A1 lists the US Federal (Final) Rules using SCC estimates either from
the Interagency Working Group (which uses DICE as one of three models
to estimate the SCC) or based on a survey by Tol (2005), which also
included several DICE- and RICE-based estimates. The list was compiled
by searching the Federal Register website for final rules referencing the
“social cost of carbon”, and manually sorting through the results to confirm
the relevant SCC was used (as opposed to, for example, merely mentioned
in a comment).
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Tab l e A1. US Federal Final Rules using the SCC in impact analysis
Rule title Agency Date
Energy Conservation Program: Energy Conservation Standards for Walk-In Cooler and Freezer Refrigeration Systems DOE 10/07/2017
Energy Conservation Program: Energy Conservation Standards for Residential Central Air Conditioners and Heat Pumps DOE 26/05/2017
Energy Conservation Program: Energy Conservation Standards for Dedicated-Purpose Pool Pumps DOE 26/05/2017
Energy Conservation Program: Energy Conservation Standards for Miscellaneous Refrigeration Products DOE 26/05/2017
Energy Conservation Program: Energy Conservation Standards for Ceiling Fans DOE 19/01/2017
Energy Conservation Program: Energy Conservation Standards for Dedicated-Purpose Pool Pumps DOE 18/01/2017
Energy Conservation Program: Energy Conservation Standards for Residential Central Air Conditioners and Heat Pumps DOE 06/01/2017
Stream Protection Rule DOI; OSMRE 20/12/2016
Roadless Area Conservation; National Forest System Lands in Colorado USDA; FS 19/12/2016
Energy Conservation Program: Energy Conservation Standards for Residential Dishwashers DOE 13/12/2016
Minimum Training Requirements for Entry-Level Commercial Motor Vehicle Operators DOT; FMCSA 08/12/2016
Energy Conservation Program: Energy Conservation Standards for Miscellaneous Refrigeration Products DOE 28/10/2016
Cross-State Air Pollution Rule Update for the 2008 Ozone NAAQS EPA 26/10/2016
Emission Guidelines and Compliance Times for Municipal Solid Waste Landfills EPA 29/08/2016
Standards of Performance for Municipal Solid Waste Landfills EPA 29/08/2016
Energy Conservation Program: Energy Conservation Standards for Battery Chargers DOE 13/06/2016
Energy Conservation Program: Energy Conservation Standards for Dehumidifiers DOE 13/06/2016
Energy Conservation Program: Energy Conservation Standards for Commercial Prerinse Spray Valves DOE 27/01/2016
Energy Conservation Program: Energy Conservation Standards for Pumps DOE 26/01/2016
Energy Conservation Program: Energy Conservation Standards for Residential Boilers DOE 15/01/2016
Energy Conservation Program for Certain Industrial Equipment: Energy Conservation Standards for Small, Large,and Very
Large Air-Cooled Commercial Package Air Conditioning and Heating Equipment and Commercial Warm Air Furnaces
DOE 15/01/2016
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Tab l e A1. Continued
Rule title Agency Date
Energy Conservation Program: Energy Conservation Standards for Refrigerated Bottled or Canned Beverage Vending
Machines
DOE 08/01/2016
Energy Conservation Program: Energy Conservation Standards for Ceiling Fan Light Kits DOE 06/01/2016
Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating Point Source Category EPA 03/11/2015
Carbon Pollution Emission Guidelines for Existing Stationary Sources: Electric Utility Generating Units EPA 23/10/2015
Standards of Performance for Greenhouse Gas Emissions From New, Modified, and Reconstructed Stationary Sources:
Electric Utility Generating Units
EPA 23/10/2015
Energy Conservation Program: Energy Conservation Standards for Single Package Vertical Air Conditioners and Single
Package Vertical Heat Pumps
DOE 23/09/2015
Energy Conservation Program: Energy Conservation Standards for Packaged Terminal Air Conditioners and Packaged
Terminal Heat Pumps
DOE 21/07/2015
Energy Conservation Program for Certain Industrial Equipment: Energy Conservation Standards and Test Procedures for
Commercial Heating, Air-Conditioning, and Water-Heating Equipment
DOE 17/07/2015
Final Affordability Determination-Energy Efficiency Standards USDA; HUDD 06/05/2015
Energy Conservation Program: Energy Conservation Standards for Automatic Commercial Ice Makers DOE 28/01/2015
Energy Conservation Program: Energy Conservation Standards for General Service Fluorescent Lamps and Incandescent
Reflector Lamps
DOE 26/01/2015
Energy Conservation Program: Energy Conservation Standards for Commercial Clothes Washers DOE 15/12/2014
National Pollutant Discharge Elimination System-Final Regulations To Establish Requirements for Cooling Water Intake
Structures at Existing Facilities and Amend Requirements at Phase I Facilities
EPA 15/08/2014
Energy Conservation Program for Consumer Products: Energy Conservation Standards for Residential Furnace Fans DOE 03/07/2014
Energy Conservation Program: Energy Conservation Standards for Walk-In Coolers and Freezers DOE 03/06/2014
Energy Conservation Program: Energy Conservation Standards for Commercial and Industrial Electric Motors DOE 29/05/2014
Energy Conservation Program: Energy Conservation Standards for Commercial Refrigeration Equipment DOE 28/03/2014
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Tab l e A1. Continued
Rule title Agency Date
Energy Conservation Program: Energy Conservation Standards for External Power Supplies DOE 10/02/2014
Energy Conservation Program: Energy Conservation Standards for Metal Halide Lamp Fixtures DOE 10/02/2014
Energy Conservation Program: Energy Conservation Standards for Standby Mode and Off Mode for Microwave Ovens DOE 17/06/2013
Energy Conservation Program: Energy Conservation Standards for Distribution Transformers DOE 18/04/2013
National Emission Standards for Hazardous Air Pollutants for Major Sources: Industrial, Commercial, and Institutional
Boilers and Process Heaters
EPA 31/01/2013
2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy
Standards
EPA; DOT; NHTSA 15/10/2012
Energy Conservation Program: Energy Conservation Standards for Dishwashers DOE 01/10/2012
Standards of Performance for Petroleum Refineries; Standards of Performance for Petroleum Refineries for Which
Construction, Reconstruction, or Modification Commenced After May 14, 2007
EPA 12/09/2012
Oil and Natural Gas Sector: New Source Performance Standards and National Emission Standards for Hazardous Air
Pollutants Reviews
EPA 16/08/2012
Energy Conservation Program: Energy Conservation Standards for Residential Clothes Washers DOE 31/05/2012
Energy Conservation Program: Energy Conservation Standards for Residential Dishwashers DOE 30/05/2012
Energy Conservation Program for Certain Industrial Equipment: Energy Conservation Standards and Test Procedures for
Commercial Heating, Air-Conditioning, and Water-Heating Equipment
DOE 16/05/2012
National Emission Standards for Hazardous Air Pollutants From Coal- and Oil-Fired Electric Utility Steam Generating
Units and Standards of Performance for Fossil-Fuel-Fired Electric Utility, Industrial-Commercial-Institutional, and Small
Industrial-Commercial-Institutional Steam Generating Units
EPA 16/02/2012
Energy Conservation Program: Energy Conservation Standards for Fluorescent Lamp Ballasts DOE 14/11/2011
Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines andVehicles EPA; DOT; NHTSA 15/09/2011
Energy Conservation Program: Energy Conservation Standards for Residential Refrigerators, Refrigerator-Freezers, and
Freezers
DOE 15/09/2011
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Tab l e A1. Continued
Rule title Agency Date
Federal Implementation Plans: InterstateTransport of Fine Particulate Matter and Ozone and Correction of SIP Approvals EPA 08/08/2011
Energy Conservation Program: Energy Conservation Standards for Residential Furnaces and Residential Central Air
Conditioners and Heat Pumps
DOE 27/06/2011
Energy Conservation Program: Energy Conservation Standards for Residential Clothes Dryers and RoomAir Conditioners DOE 21/04/2011
National Emission Standards for Hazardous Air Pollutants for Area Sources: Industrial, Commercial, and Institutional
Boilers
EPA 21/03/2011
National Emission Standards for Hazardous Air Pollutants for Major Sources: Industrial, Commercial, and Institutional
Boilers and Process Heaters
EPA 21/03/2011
Standards of Performance for New Stationary Sources and Emission Guidelines for Existing Sources: Commercial and
Industrial Solid Waste Incineration Units
EPA 21/03/2011
Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards; Final Rule EPA; DOT; NHTSA 07/05/2010
Energy Conservation Program: Energy Conservation Standards for Residential Water Heaters, Direct Heating Equipment,
and Pool Heaters
DOE 16/04/2010
Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard Program EPA 26/03/2010
Energy Conservation Program: Energy Conservation Standards for Small Electric Motors DOE 09/03/2010
Energy Conservation Program: Energy Conservation Standards for Certain Consumer Products (Dishwashers,
Dehumidifiers, Microwave Ovens, and Electric and Gas Kitchen Ranges and Ovens) and for Certain Commercial and
Industrial Equipment (Commercial Clothes Washers)
DOE 08/01/2010
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Tab l e A1. Continued
Rule title Agency Date
*Energy Conservation Program: Energy Conservation Standards for Refrigerated Bottled or Canned Beverage Vending
Machines
DOE 31/08/2009
*Energy Conservation Program for Certain Industrial Equipment: Energy Conservation Standards and Test Procedures
for Commercial Heating, Air-Conditioning, and Water-Heating Equipment
DOE 22/07/2009
*Energy Conservation Program: Energy Conservation Standards and Test Procedures for General Service Fluorescent
Lamps and Incandescent Reflector Lamps
DOE 14/07/2009
*Energy Conservation Program: Energy Conservation Standards for Certain Consumer Products (Dishwashers,
Dehumidifiers, Microwave Ovens, and Electric and Gas Kitchen Ranges and Ovens) and for Certain Commercial and
Industrial Equipment (Commercial Clothes Washers)
DOE 08/04/2009
*Average Fuel Economy Standards Passenger Cars and Light Trucks Model Year 2011 DOT; NHTSA 30/03/2009
*Energy Conservation Program for Commercial and Industrial Equipment: Energy Conservation Standards for
Commercial Ice-Cream Freezers; Self-Contained Commercial Refrigerators, Commercial Freezers, and Commercial
Refrigerator-Freezers Without Doors; and Remote Condensing Commercial Refrigerators, Commercial Freezers, and
Commercial Refrigerator-Freezers
DOE 09/01/2009
Source: Federal Register Search.
Notes: The table lists US Federal (Final) Rules using IWG SCC estimates in cost–benefit assessments. An asterisk indicates Tol (2005) survey-based SCC. The acronyms used are as
follows: DOE, Department of Energy; EPA, Environmental ProtectionAgency; DOI, Department of Interior; OSMRE, Office of Surface Mining Reclamation and Enforcement; USDA,
Department of Agriculture; FS, Forest Service; DOT, Department of Transportation; FMCSA, Federal Motor Carrier Safety Administration; HUDD, Housing and Urban Development
Department; NHTSA, National Highway Traffic Safety Administration.
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