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Sustainability Science (2021) 16:949–965
https://doi.org/10.1007/s11625-021-00910-5
ORIGINAL ARTICLE
The costs andbenefits ofenvironmental sustainability
PaulEkins1 · DimitriZenghelis2
Received: 23 December 2019 / Accepted: 19 January 2021 / Published online: 16 March 2021
© The Author(s) 2021
Abstract
The natural science in GEO-6 makes clear that a range and variety of unwelcome outcomes for humanity, with potentially
very significant impacts for human health, become increasingly likely if societies maintain their current development paths.
This paper assesses what is known about the likely economic implications of either current trends or the transformation to a
low-carbon and resource-efficient economy in the years to 2050 for which GEO-6 calls. A key conclusion is that no conven-
tional cost–benefit analysis for either scenario is possible. This is because the final cost of meeting various decarbonisation
and resource-management pathways depends on decisions made today in changing behaviour and generating innovation.
The inadequacies of conventional modelling approaches generally lead to understating the risks from unmitigated climate
change and overstating the costs of a low-carbon transition, by missing out the cumulative gains from path-dependent innova-
tion. This leads to a flawed conclusion as to how to respond to the climate emergency, namely that significant reductions in
emissions are prohibitively expensive and, therefore, to be avoided until new, cost-effective technologies are developed. We
argue that this is inconsistent with the evidence and counterproductive in serving to delay decarbonisation efforts, thereby
increasing its costs. Understanding the processes which drive innovation, change social norms and avoid locking in to car-
bon- and resource-intensive technologies, infrastructure and behaviours, will help decision makers as they ponder how to
respond to the increasingly stark warnings of natural scientists about the deteriorating condition of the natural environment.
Keywords GEO-6· Low-carbon transition· Path dependency and Lock in· Dynamic costs and benefits· Endogenous
growth
Introduction
The sixth UN Global Environment Outlook (GEO-6) (UNEP
2019) focused on the close relationship between human
and environmental health, presenting much evidence that
a healthy planet is necessary for healthy people and that,
conversely, an unhealthy planet damages human health. This
paper echoes, and indeed adds to, the findings of GEO-6 by
setting out the benefits to early policy action, not only to
limit potentially catastrophic environmental risks, but also
to shape new markets, create business opportunities and
induce new technologies and behaviours which will ben-
efit society beyond their environmental value. Section“The
costs of ‘grow now, clean up later’” of the paper reviews the
evidence from GEO-6 and elsewhere of the costs of envi-
ronmental damage resulting from a still largely dominant
global development model of ‘grow now, clean up later’.
This describes the approach through which societies’ efforts
to achieve economic growth damage natural systems and
their environmental functions, reducing their ability to
deliver multiple benefits in terms of ecosystem goods and
services, entailing costs to health, with knock-on effects on
human societies and economies. These costs could be much
amplified if global warming induces climate ‘tipping points’,
feedback effects through which warming itself is amplified.
GEO-6 did not investigate this in detail, but evidence is now
beginning to emerge as to the extra costs that these tipping
points could entail.
The costs of environmental damage become the ben-
efits of environmental protection and restoration, if they
are thereby mitigated or avoided. There are three broad
Handled by Detlef Vuuren, PBL Netherlands Environmental
Assessment Agency, Netherlands.
* Paul Ekins
p.ekins@ucl.ac.uk
1 UCL Institute ofSustainable Resources, University College
London, London, UK
2 London School ofEconomics andPolitical Science, London,
UK
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950 Sustainability Science (2021) 16:949–965
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environmental strategies to deliver these benefits, the ‘triple-
de’: decarbonisation, to reduce the level of global warming;
detoxification, to reduce the emissions or impacts of other
pollutants; and dematerialisation, to reduce the environmen-
tal impacts associated with resource extraction, conversion
and processing. Section“The costs of environmental protec-
tion” of the paper explores the issue as to what the imple-
mentation of ‘triple-de’ strategies would cost with a focus on
attempts to model the costs of decarbonisation. This is seen
to hinge on the role of innovation—in technologies, behav-
iours and institutions—that makes the costs endogenous to
the policy approach taken; the costs associated with the tran-
sition to a sustainable economy will be a function of today’s
decisions. The paper also considers the costs of locking in
to environmentally damaging technologies, behaviours and
institutions that then have to be abandoned or retrofitted—
costs that are avoided if economic development and clean
environmental performance are managed together working
with the investment cycle. The final section concludes and
draws recommendations for decision-makers.
The costs of‘grow now, clean uplater’
The common policy approach to economic development has
been to concentrate on getting rich first, and hope to have
the resources to fix the environment later—the ‘grow now,
clean up later’ mind set. This is the way the old industrial
countries did it, and the standard assumption, especially in
developing and emerging economies, and despite increas-
ing rhetoric espousing ‘sustainable development’ and the
Paris Agreement, is that there is no better way to develop
economically.
Notwithstanding the benefits that economic growth
has brought millions of people in both old industrial and
emerging economies—lifting them out of poverty, reducing
infant mortality and other preventable deaths, increasing life
expectancy, literacy, access to water and sanitation, eradi-
cation of diseases—evidence in respect of the environment
and natural resources now suggests that this approach has
brought human societies to the brink of catastrophe, putting
at serious risk all these benefits and, indeed, the continu-
ance of human civilisation itself. This section will explore
these risks, and the current costs that accompany them. It
will reveal the new priorities of human development to be
detoxification, decarbonisation and dematerialisation.
The irony is that the assumption that countries at an early
stage of development need to suffer gross pollution to get
richer flies in the face of more than two decades of evidence,
as will be seen.
The costs of‘clean uplater’
Early evidence
One of the earliest papers to investigate the assumption that
pollution was a necessary accompaniment to early growth
was O’Connor (1996), who tested it in respect of the newly
industrialising or recently industrialised economies of East
and South East Asia. He considered the environmental
dimension of the growth process of Japan, what were then
called ‘the four dragons’—Hong Kong, Korea, Taiwan, and
Singapore—and some later industrialising countries in the
region (Indonesia, Malaysia, and Thailand). He reviewed
evidence on relative pollution intensity and energy intensity,
estimates of the environmental damage costs incurred by
these East Asian economies and how these related to actual
measured output, and evidence on environmental expen-
ditures in these countries, both actual and projected. His
conclusions were startling. He found that all the countries
studied had to some extent taken a ‘grow now, clean up later’
approach, but some markedly more so than others.
What was clear was that the countries with the more
pollution-intensive growth patterns later faced significant
challenges that could constrain future growth through “rap-
idly escalating external costs from accumulated pollution
damage and/or rapidly escalating investments in remediation
of that damage” (p.15). Moreover, there was no evidence at
all that the countries which had invested early in pollution
control along with their industrialisation (e.g. Hong Kong
and Singapore) had suffered lower growth rates than those
countries that had invested much less. The oft-hypothesised
growth-environment trade-off at early stages of development
was simply not apparent in the data.
O’Connor 1996 (pp.31–32) identifies a number of rea-
sons why it may be more expensive to address pollution
problems after they have been created rather than preventing
them from occurring. Most obviously, collecting and treating
waste is likely to be cheaper before it is widely dispersed in
the natural environment. But there are also issues related
to abatement costs. Cleaning up polluting plant usually
involves either scrapping equipment before its due date, or
retrofitting it, or fitting end-of-pipe treatment technology.
It will often be the case that initial investment in cleaner, if
initially more expensive, technology that avoids these extra
costs, ‘leap-frogging’ the phase of gross pollution, can be
economically preferable.
Moreover, the ‘lock-in’ from past investments, especially
in infrastructure, may mean that environmental improvement
can only gradually be achieved leaving a long period of high
environmental costs that could have been avoided with dif-
ferent initial infrastructure decisions. O’Connor (1996, p.36)
also cites evidence that much environmental improvement
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951Sustainability Science (2021) 16:949–965
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can be achieved through measures with very low payback
times that make economic sense in their own right. All
this leads him to conclude that any negative effects from
increased environmental expenditures “should be largely if
not wholly offset by the positive effect on the productivity of
public and private sector investments, through the mitigation
of health and other pollution damages” (p.34). Unsurpris-
ingly, he finds no evidence of slower economic growth in
those Asian countries (e.g. Hong Kong, Singapore) that have
considered environmental as well as economic performance
compared with those that have not.
Evidence since2010
Unfortunately, despite the evidence cited above, this lesson
is far from learned. A book-length study by the World Bank
of India’s environmental and economic development record
(Mani 2014) asserts, (p.4): “The “grow now, clean up later”
doctrine, though much debated, is now widely discredited
by the experiences of many developing countries.” But much
of the subsequent text goes to show that the ‘doctrine’ is still
very much in evidence in the state of India’s air, water and
ecosystems. The report puts the “total cost of environmental
degradation in India” at 5.7% of India’s GDP (mid-point,
range 2.6–8.8%), comprising costs from outdoor and indoor
air pollution (29% and 21% respectively), from inadequate
water supply, sanitation and hygiene (14%) and degradation
of cropland (19%), pasture (11%) and forests (4%) (percent-
ages are of the mid-point damages).
More recently, the comprehensive assessment of the
health impacts of global pollution of Landrigan et al.
(2018) shows just how few lessons have been learned since
the 1990s. They estimate that pollution-related disease was
responsible for 16% of total global mortality, or 254 million
years of life lost, in 2015. As shown in Fig.1, this number is
considerably greater than the estimated deaths from a num-
ber of other causes that have a much higher public profile.
The total welfare damages of this pollution burden have been
estimated for 2015 at USD4.6 trillion, equivalent to 6.2% of
global GDP (Landrigan etal. 2018, p.487). Landrigan etal.
(2018) echo the findings of O’Connor some 20years earlier:
“The claim that pollution control stifles economic
growth and that poor countries must pass through a
phase of pollution and disease on the road to prosperity
has repeatedly been proven to be untrue. … Many of
the pollution control strategies that have proven cost-
effective in high-income and middle-income countries
can be exported and adapted by cities and countries at
every level of income.” (Landrigan etal. 2018, p.463).
Detoxification, it seems, often makes economic sense
quite apart from the welfare benefits of resulting in healthier
people. The next section shows that the arguments for decar-
bonisation are just as strong.
The ‘fat‑tailed’ costs ofclimate change
The estimates of possible damages from climate change are
so large they are difficult to comprehend. The IPCC 1.5°C
report made clear that even going beyond a temperature
increase of 1.5°C would significantly increase the risks of
substantial damage from climate change, and cites estimates
Fig. 1 Global estimate deaths
in 2015 by major risk factor and
cause; Source: Landrigan etal.
2018, Fig.5, p.473
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952 Sustainability Science (2021) 16:949–965
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of the extra damage caused in 2100 by 2°C as opposed to
1.5°C as USD 15–38.5 trillion (2.3–3.5% of Gross World
Product) (IPCC 2018, p.256).
Steffen etal. (2018) have investigated in detail the vari-
ous planetary thresholds that may act as ‘tipping points’, at
different levels of global warming, into a Hothouse Earth.
The colours in their ‘Global map of potential tipping cas-
cades’ illustrate the average global temperature increases at
which that particular feature may tip into a different state.
The arrows, based on expert elicitation, indicate how the
activation of some tipping points by a relatively low level of
global warming (e.g. melting of the Greenland Ice Sheet at
1–3°C) could push the global average temperature higher,
activating further tipping points such as the thermohaline
circulation, thereby causing a tipping point ‘cascade’ effect.
Of course, there is very great uncertainty about the pre-
cise magnitude of these effects, and it is probably best to
think of these numbers in terms of risk, in this case the risk
from a probability distribution that has a ‘fat-tailed’ prob-
ability of very large costs. Weitzman emphasised the “truly
extraordinary uncertainty about the aggregate welfare
impacts of catastrophic climate change, which is represented
mathematically by a PDF that is spread out and heavy with
probability in the tails.” (Weitzman 2011, p.285).
To emphasise further how difficult people find it to act
consistently in the face of such uncertainty, consider Table1,
from Wagner and Weitzman (2015).
Using the IPCC’s ‘likely’ climate sensitivity, Table1
shows the median temperature increase at different levels
of atmospheric concentration of carbon dioxide equivalents
(CO2e), but also the probability that the temperature increase
will be more than 6°C—which Wagner and Weitzman call
‘an indisputable global catastrophe’ (Wager and Weitzman
2015, p.88). This probability is seen to be 11% at an atmos-
pheric GHG concentration of 700ppm, which is in line with
the IEA’s projection for 2100 even if governments kept their
then current promises (cited in Wager and Weitzman 2015,
p.55). But they also give a 0.3% chance of exceeding a 6°C
temperature increase at 450ppm, which is roughly the cur-
rent atmospheric GHG concentration.
To put this in perspective, it may be noted that in 2018
there were around 38 million aircraft flights per year (ICAO
2018), with one fatal accident every three million flights,1
a probability of 0.000033%. A 0.3% probability of a fatal
accident would mean over 300 fatal accidents each day.
How many people would fly given that kind of accident rate
reported daily on the news? Yet that is the risk human socie-
ties are currently taking in respect of catastrophic climate
change. Such risk taking becomes even more bizarre when it
is considered that the health benefits just from reduced local
air pollution of achieving the 2°C target could be 1.4–2.5
times the cost of mitigation, the higher figure involving ben-
efits of USD 54.1 trillion for a global expenditure of USD
22.1 trillion (UNEP 2019, Box24.1, p.588). Deep decar-
bonisation makes sense whether looked at from the point
of view of global insurance against catastrophe for future
generations, or health benefits for those currently alive.
The costs ofresources
The ‘grow now, clean up later’ mind set has not only been
cavalier in respect of pollution and indifferent to the green-
house gas emissions causing climate change, it has also been
extraordinarily wasteful in its use of resources, through a
related mind set of ‘take-make-use-dispose’. The ‘grow now,
clean uplater’ economy has also been a linear, throw-away
economy, as attested by the mountains of garbage and oceans
of plastic that are now in evidence almost everywhere.
The Global Resources Outlook of the International
Resource Panel (IRP 2019a; b) has documented the growth
of resource use since 1970 and associated environmental
impacts. Since 1970 global material use has more than tri-
pled from 27 billion tonnes to 92 billion tonnes, with bio-
mass increasing from 9.1 to 24.1 billion tonnes, fossil fuels
from 6.2 to 15.0 billion tonnes, metal ores from 2.6 to 9.1
billion tonnes, and non-metallic minerals, the greatest pro-
portionate increase due to its importance in infrastructure
construction, from 9.2 to 43.8 billion tonnes (IRP 2019a,
p.43–44).
This extractive activity is associated with very large envi-
ronmental impacts, as shown in Fig.2. Biomass production
Table 1 Probabilities of exceeding an average global temperature increase of 6°C at different atmospheric concentrations of GHGs; Source:
Wagner and Weitzman 2015, Table3.1, p.54.
CO2 concn. (ppm) 400 450 500 550 600 650 700 750 800
Median temp. increase (°C) 1.3 1.8 2.2 2.5 2.7 3.2 3.4 3.7 3.9
Chance of > 6°C (%) 0.04 0.3 1.2 3 5 8 11 14 17
1 https ://editi on.cnn.com/2019/01/02/healt h/plane -crash -death s-intl/
index .html.
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953Sustainability Science (2021) 16:949–965
1 3
alone (mainly agriculture) is responsible for nearly 90% of
biodiversity loss and water stress. Extraction (including fos-
sil fuels) is also responsible for 50% of greenhouse gas emis-
sions and 30% of particulate matter health impacts. Yet these
industries only contribute around 20% of global value added.
On current trends global material extraction would double
again by 2060 to 190 billion tonnes, with greenhouse gas
emissions increasing by 43%, and cropland and pasture land
increasing by 20% and 25% respectively, with forests and
other natural habitat decreasing by 10% and 20% respec-
tively (IRP 2019a, Sect.4.2, pp.102ff.). Many populations
will experience water scarcity, with growing competition
for water between cities and agriculture. It is very unlikely
that the Earth’s natural systems would sustain this kind
of increase in natural resource extraction and the associ-
ated environmental impacts. A liveable future will demand
dematerialisation of the economy, particularly a decoupling
between economic growth and resource use, and an absolute
reduction in the environmental impacts of resource extrac-
tion of all kinds (how to achieve this is discussed in sec-
tion“The costs of environmental protection”).
The age ofirreversibility
While the ‘grow now, clean up later’ approach was always
economically unsound, more recently it has become theo-
retically unsound as well. At a local level, it is possible for
a time to substitute natural capital for physical capital and
boost prosperity, as arguably the UK did during the indus-
trial revolution. But at a global level this is not possible.
With climate change and biodiversity loss, there is no return
to the status quo ante. There is no ‘later’. Extinction is for-
ever, with the Intergovernmental Panel on Biodiversity and
Ecosystem Services (IPBES) suggesting that:
“around 1 million species already face extinction,
many within decades, unless action is taken …. With-
out such action there will be a further acceleration in
the global rate of species extinction, which is already
at least tens to hundreds of times higher than it has
averaged over the past 10 million years.” (IPBES 2019,
pp.2–3).
GEO-6 chronicles a terrible record of environmental
damage from biodiversity loss (including pollinators, coral
reefs and mangroves), climate change and other air pollu-
tion, water pollution, ocean pollution and depletion, and land
Fig. 2 Environmental and
economic impacts of resource
extraction, compared with
households and the rest of the
economy; Source: IRP 2019b,
Figure II, p.16
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954 Sustainability Science (2021) 16:949–965
1 3
use change. As with ecosystem goods and services, these
costs are difficult to express comprehensively in monetary
or other terms, but GEO-6 confirms the level of many of the
costs involved cited earlier (page numbers in what follows
refer to GEO-6): For example, exposure to indoor/outdoor
air and water pollution costs at least 9 million lives annu-
ally (p.78). Millions more suffer from ill-health and loss of
livelihoods. Pollution-related costs have been estimated at
USD 4.6 trillion annually (p.9). 29% of global land area is
classed as a ‘land degradation hotspot’, affecting 3.2 billion
people (p.203) and costing USD 6.3–10.6 trillion (p.374).
While no individual weather event can be attributed to
a warming climate, the frequency and severity of extreme
events are increasing due to a warming climate. As Lomborg
(2020) notes, even similar events to those in the past are now
more damaging because of both economic and population
growth. Between 2010 and 2016, an average of around 700
extreme events each year cost an average of USD 127 billion
per annum (Watts etal. 2017, pp. 615–616). While 90% of
the losses came from high and upper-middle income coun-
tries, the less than 1% of the losses from low-income coun-
tries amounted to around 1.5% of their GDP, a much higher
proportion than in high-income countries, and was almost
all uninsured. Gupta and Ekins in UNEP 2019 (p.xxix) cite
estimates of water-related health costs of about USD140
billion in lost earnings and USD 56 billion in health costs
annually. From 1995 to 2014, 700,000 people died and 1.7
billion people were affected by extreme weather events cost-
ing USD 1.4 trillion (UNEP 2019, Fig.4.1, p.80). As with
biodiversity loss, the committed climate change that exacer-
bates these events is irreversible. They will continue to rav-
age human communities, perhaps with increased intensity,
for the foreseeable future.
There is no doubt the scale of the ‘triple-de’ challenge is
ambitious. Carbon-based fossil fuels have powered most of
the world’s economic activity for more than two hundred
years, since the use of coal to fire steam engines induced the
Industrial Revolution. Oil, gas and coal currently make up
almost 80% of primary energy use. [World Energy Outlook
Special Report 2017: Energy and Climate Change, Inter-
national Energy Agency] It therefore seems reasonable to
ask what will be the cost of decarbonisation, detoxification,
dematerialisation and repurposing infrastructure and behav-
iours to deliver a sustainable economy?
The costs ofenvironmental protection
The focus of this section is the costs associated with the
task of tackling climate change and promoting sustainabil-
ity noting that all environmental concerns are exacerbated
by climate risks. We begin by noting that it is the stock of
greenhouse gases that causes global warming, not the annual
emissions. This means that keeping the global temperature at
any level means transitioning to a net zero emissions world,
because it is by definition the only way to stabilise the stock
so the temperature will stop rising. This means humanity
either manages the transition to temperature stabilisation or
nature does it for us by depopulating and deindustrialising
the planet.
If humanity chooses swift decarbonisation in line with
the target of the Paris Agreement, many of the behaviours,
technological networks and institutions of the last century
look set to be devalued or stranded. Economies which are
disproportionately dependent on fossil fuels in their pro-
duction and trade may have higher transition costs than
others, particularly where they lack flexible and responsive
institutions (this is a problem for some gulf states, but even
for more diversified but still ‘carbon entangled’ states like
Russia, Nigeria, Kazakhstan, Indonesia or Poland). In other
cases, such as coal in India or oil in Venezuela, fossil fuel-
based organisations provide a significant part of the formal
or informal welfare state of a nation or region. Such fossil
fuel–dependent countries represent almost one-third of the
world’s population (Peszko etal. 2020). Many have weak
and inflexible institutions, limited access to global finance
and pressing challenges of poverty, conflict and violence.
Having accepted the imperative of a low-carbon transi-
tion, it is necessary to acknowledge, up-front, that large-
scale change will mean winners and losers and the losers
will suffer dislocation. A quick scan of the global political
economy tells us that these concerns need to be carefully
managed. Because they can lead to delay, backlash, resist-
ance and resource wastage. Indeed, they can make it hard
for any economy to adjust to the forces of technological and
structural change. Understanding the political economy is
therefore necessary to manage change and enable all par-
ticipants to profit from improved economic and social con-
ditions. However, these concerns should not be falsely con-
flated with economic concerns regarding the true potential
of environmental policies if implemented. It is the task of
policymakers to limit the perceived reasons to slow or block
necessary change.
Ensuring a just transition will be crucial for maintaining
social cohesion and economic justice and enabling the cli-
mate transition to unfold. This requires enabling institutions
that reskill, retool and compensate affected workers. It also
requires policy responses to compensate consumers who
face disproportionately higher costs (for example through
temporary increases in energy or transport bills) and policy
support for people living in towns and peripheral regions
away from more dynamic urban centres better placed to
manage change.
Economic theory and history also suggest that economies
that embrace change, with diversified assets and flexible
institutions are better able to manage structural adjustment
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955Sustainability Science (2021) 16:949–965
1 3
(Zenghelis etal. 2018). Such economies do not inhibit the
flow of resources from declining, low-productivity sectors
to new, more productive sectors. They encourage, manage
and steer it to gain competitive advantage (see Combes and
Zenghelis 2014).
This section builds on this historical evidence and argues
that addressing our resource and environmental challenges
necessitates rapid innovation in technologies, behaviours
and institutions. Section“Innovation, endogeneity and path-
dependency” explains the dynamics of innovation and the
opportunities to profit deliberately from its path-dependent
nature.
As we find better ways of consuming, producing and
living, we are likely to see complementary changes in
behaviour, institutions and social norms (Section“Induced
innovation and learning-by-doing”). In section “Networks,
spillovers and contagion”, we will highlight the numerous
immediate co-benefits associated with a transition. These,
together with incentives from new policy drivers, are key
to pushing early voluntary action on decarbonisation and
resource efficiency based on near-term self-interest. For
example, sprawling, congested, polluted cities with inef-
ficient infrastructure and outmoded energy technologies
do not in general attract highly skilled labour and act as
a drag on GDP growth and wellbeing. This challenges the
fallacy that a transition to a carbon–neutral economy is
bound to make us worse off before it makes us better off.
As expectations overcome inertia, tipping points can lead
to rapid network shifts in key technologies and behaviours
(Section“Feedbacks in preferences, behaviour and expecta-
tions”). This is not the context of standard growth models
(Section“Innovation, endogeneity and path-dependency”)
which struggle to capture structural change and integrate
dynamic, increasing returns. Such models have a struc-
tural bias that tends to systematically overestimate costs of
transition.
Overstating costs undermines the case for early action
(Section“What does this mean for ‘green growth’?”). But
it also delays investment and innovation necessary to facili-
tate a cost-effective transition. When change does come,
governments and businesses caught unprepared risk being
saddled with stranded assets and uncompetitive, outmoded
forms of production. We conclude by showing that the virtu-
ous dynamics associated with an accelerated and productive
transition are unlikely to materialise without leadership to
steer investment and innovation (Section“Ways forward”).
Innovation, endogeneity andpath‑dependency
Innovation is essential in determining our ability to decouple
growth and consumption from environmental degradation
and resource use. Several climate economic models have
attempted to incorporate innovation (see, for example, Popp
2004 and Bosetti etal. 2006). However, these models usually
miss out important firm-level and sector-specific processes,
spillovers and interactions or the role for mission-orientated,
targeted R&D efforts.
Innovation does not just ‘happen’. It relies on path
dependencies of three kinds: (1) research and development,
(2) deployment and uptake, (3) network effects and econo-
mies of scale (Aghion etal. 2014). Strong inertia and high
switching costs make it initially difficult to shift the innova-
tion system from dirty to clean technologies without direct
policy intervention. But once they reach a tipping point
where expectations change rapidly and technologies switch
from one network to another, these effects go the other way
(Krugman 1991; Matsuyama 1991).
Induced innovation andlearning‑by‑doing
Positive and reinforcing feedbacks derived from reduced
technology cost accelerate further deployment and invest-
ment in supporting networks, infrastructure and institutions.
Indeed, this arises specifically because of powerful network
effects and high switching costs. Investments in enabling
infrastructure spur technology tipping points through gen-
erating network externalities. For example, as electric vehi-
cle infrastructure is rolled out, the incentives to conduct
research and development on electric cars increase relative
to combustion engine (or fuel cell) vehicles.
Networks, spillovers andcontagion
Hidalgo etal. (2007) and Mealy and Teytelboym (2017)
used network analysis to demonstrate that it is easier for
countries to become competitive in new green products
that require similar production capabilities and know-how
to existing sectors. As a result, green transitions are highly
path-dependent: countries which successfully invest early in
green capabilities have greater success in diversifying into
future green product markets. This reinforced the findings
of Aghion etal. (2012) who provide empirical evidence that
a firm’s choice whether to innovate clean or dirty is influ-
enced by the practice of the countries where its researchers/
inventors are located and that firms tend to direct innovation
toward what they are already good at.
Braun etal. (2010) use OECD patent data to show that
both wind and solar technologies create knowledge spillo-
vers at the national level. Using data on 1 million patents and
3 million citations, Dechezlepretre etal. (2014) suggest that
spillovers from low-carbon innovation are over 40 percent
greater than from conventional technologies (in the energy
production and transportation sectors). These effects, plus
the cost savings as new networks and institutions are estab-
lished, explain why Acemoglu etal. (2012) make a powerful
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956 Sustainability Science (2021) 16:949–965
1 3
theoretical case to suggest that policy to support clean inno-
vation can be temporary, because once the “clean innovation
machine” has been “switched on and is running,” it can be
more innovative and productive than the conventional alter-
native, with a positive impact on GDP levels and growth.
These findings suggest governments should focus on
areas where they have complementary advantage and pri-
oritise early targeted R&D in these sectors. It also suggests
that low-carbon investment can ‘crowd in’ productive invest-
ment and generate growth. Policy can thereby influence
both the direction and pace of change (Fischer and Newell,
2008; Farmer and Lafond, 2016). Policy should aim to cata-
lyse change in technology networks and behaviours while
generating knowledge spillovers by focusing less on static
market failures and more on dynamic ‘market creation’ and
‘market shaping’. This is likely to require that new policy
frameworks and institutions be re-purposed strategically so
as to steer the economy in a sustainable and resilient direc-
tion, for example through the creation of new low-carbon
regulatory bodies and public investment banks with strong
sustainability mandates.
Feedbacks inpreferences, behaviour andexpectations
A key source of path dependence in socioeconomic systems
is the presence of ‘complementarities’ in expectation forma-
tion. This occurs when the payoff to the whole group from
working together is greater than the sum of the individual
payoffs. In particular, ‘strategic complementarities’ arise
when agents make individual decisions that affect each oth-
er’s welfare and one agent’s greater productivity makes all
the other agents more productive. Research and development
externalities (Romer 1990) and learning spillovers (Arrow
1962) in low-carbon technologies have these features—as
more scientists start thinking about clean energy, more ideas
and innovations emerge that other scientists can use. But
technology is not the only source of rapid change and inno-
vation. Behavioural, institutional and social innovation can
guide demand-side factors relating to consumer preferences
(Boyd etal. 2015).
Social norms can be defined as the predominant behav-
iour within a society, supported by a shared understanding of
acceptable actions and sustained through social interactions
(Ostrom 2000). Social feedbacks help make norms self-rein-
forcing and therefore stable. Formal institutions struggle to
enforce collectively desirable outcomes without popular sup-
port. Acceptable standards of behaviour and social norms
are the sources of law and ultimate drivers of legislative
change (Posner 1997).
Regulations, taxes, subsidies or infrastructure investment
such as cycle lanes or dense housing and public transport
can aid the process of shifting norms. Build cycle lanes and
people will buy bicycles. A potentially powerful role for
policy is to provide reasons for people to change their expec-
tations and behaviours (Young 2015). Social psychologists
have long understood that solving coordination problems
requires building expectations into models and generating
‘common knowledge.’ (Thomas etal. 2014). In low and
middle-income countries, this can take the form of politi-
cal processes that confer authority and capacity on public
institutions not only to diffuse new innovations but also to
generate agglomeration hubs (Collier 2017). This can help
implement the legal and fiscal frameworks, as well as skills
and infrastructure, to attract international knowledge through
multi-national inward investment, trade and foreign finance.
Institutional development is central to enable technological
innovation, adoption and growth (Easterly and Levine 2003).
It also allows domestic innovation to be diffused through
universities, research institutes and high value-added urban
employment. Far from acting as a constraint, decarbonisa-
tion may afford low-income countries an opportunity to
accelerate growth by breaking new ground without relying
on incremental change to legacy infrastructure which they
lack. Analogous to the spread of mobile telephony, devel-
oping countries can leapfrog developed economies and
increase access to basic electricity services by bypassing
expensive and inefficient centralised electricity grid infra-
structure and investing instead in distributed energy plat-
forms (Alstone etal. 2015; Levin and Thomas 2016).
In all countries of all income levels, local technology
clusters create positive spillover effects of lowering infor-
mation, transaction and installation costs (Porter 2000). One
study showed how social networks and dwelling proximity
explained the clustering of photovoltaic panel installation
by homeowners (Rogers 2010). Changing social norms can
also add to the costs of polluting by putting pressure on
legislators, as well as influencing strategic decision-making
contexts, such as in the financial sector.
Investment norms can also shift as investors begin to per-
ceive risk in high-carbon resource-intensive sectors previ-
ously deemed safe, for fear that assets (resources, physical
infrastructure, human capital and intangible know-how)
might become devalued or stranded in coming decades.
Meanwhile, the risk premium attached to investment in clean
sectors, previously considered exotic, falls as these are seen
as more resilient to a low-carbon resource-constrained future
(Bradshaw 2015; Zenghelis 2016). Pension funds and insur-
ance companies are correspondingly cutting support for coal
projects (Financial Times 2018). Meanwhile clean sectors
outperform their peers in terms of financial returns (Friede
etal. 2015; Clark etal. 2015). Governments should work to
push firms and public institutions to better integrate climate
risk assessment into investment decisions, through mandated
disclosure standards and scenarios for stress-testing resil-
ience to rapid future decarbonisation.
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957Sustainability Science (2021) 16:949–965
1 3
The point here is that actual or expected changes in pol-
icy, technology and physical risks—as well as the threat of
litigation for loss and damage from climate change—could
prompt a rapid reassessment of the value of a large range of
assets as changing costs and opportunities become appar-
ent (Stern and Zenghelis 2016). For many low- and middle-
income countries, failure to act early could mean: markets
are closed off to their products because they do not meet
new standards and regulations in export markets, or they
face border tax adjustments; higher costs of capital as mul-
tilateral and other investment banks withdraw from carbon-
intensive sectors, and competitiveness declines as a result
of being saddled with less productive or redundant legacy
technologies. This raises the cost of ‘pollute now clean up
later’ strategies and enhances the risk of early yet avoidable
financial loss and the locking in to stranded assets, while
accelerating the cost-effective transition to a clean economy.
Co‑benefits andopportunities asatrigger
Changing expectations hold the key to overcoming inertia
and unblocking a waiting game. This is underpinned by a
growing appreciation of additional opportunities associated
with a low-carbon transition (Hale 2018). These include
not only commercial opportunities associated with deploy-
ing (and fabricating and exporting) cheap and increasingly
competitive new clean technologies, but also benefits from
reductions in waste and inefficiency, improved energy secu-
rity and reduced particulate pollution and congestion from
clean compact cities.
Not only are pollution externalities not priced, but envi-
ronmentally degrading activities continue to be actively
encouraged by policy. IEA estimates that in 2015 subsidies
to fossil fuels were twice as large as those to renewables (van
Asselt and Kulovesi 2017). Coady etal. (2015) estimate that
eliminating subsidies for fossil fuels would have reduced
global carbon emissions in 2013 by 21% while boosting net
public revenues by 4% and reducing deaths from local air
pollution by 55%.
The Global Commission on the Economy and Climate
(2014) found that more than half and as much as 90% of the
global emissions reductions required to meet an ambitious
climate target could generate net benefits to the economy.
These include health benefits from reductions in urban pol-
lution, falls in traffic congestion, increases in efficiency or
improvements in energy security and supply. Hallegatte
etal. (2012) argue that compared with business-as-usual,
green growth would mean immediate positive effects on the
economy, such as co-benefits (e.g. reduced local pollution),
growth in new ‘green’ sectors, and less energy price volatil-
ity via reduced dependence on fossil fuel imports. Higher
income generates resources for investment in environmental
quality and poverty eradication (Hepburn and Bowen 2013).
Complementarities, cascades andtipping points
Changes in expectations can overcome the burdens of history
to become self-fulfilling. As enough players shift investment
to deploy new technologies, learning and experience will
push their price down, making further investment increas-
ingly attractive relative to conventional technologies, where
the gains from additional learning or scaling are smaller.
Very quickly, an economy can switch from one tech-
nology network to another as a newcomer becomes more
attractive than the incumbent, until incumbent technologies,
products and networks become obsolete. (Otto and Donges
2019).
Fig. 3 IEA renewable capac-
ity forecasts, ex-hydropower;
Source: Metayer, Breyer and
Fell, 2015 (https ://www.lut.
fi/docum ents/10633 /70751 /
The-proje ction s-for-the-futur
e-and-quali ty-in-the-past-of-the-
World -Energ y-Outlo ok-for-solar
-PV-and-other -renew able-energ
y-techn ologi es-EWG-WEO-
Study -2015.pdf)
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958 Sustainability Science (2021) 16:949–965
1 3
Failure to model the dynamics and positive feedbacks
associated with structural change, not only in terms of econ-
omies of scale from production and discovery, but also the
complementarities and feedbacks associated with contagion
and systems tips, are the reasons why most economists have
been caught out by the rapid nature of the early phases of the
post-carbon transition. Figure3 shows forecasts made by the
International Energy Agency (IEA) for the deployment of
renewable technologies compared with actual outturns. The
IEA is arguably the leading authority on energy technolo-
gies, yet they systematically and repeatedly underestimate
the deployment of renewables and correspondingly overes-
timate the costs.
The IEA are not alone. Few economists predicted the pre-
cipitous fall in the price of renewable technologies. Solar
photovoltaic (PV) costs fell 44 per cent2 in the two years to
the end of August 2017 and have fallen by 83 per cent since
2010,3 a period over which the price of wind turbines has
dropped 35 per cent.4 They have already become the cheap-
est source of energy in many world regions (Fig.4). And
the rate of change shows no sign of slowing. Regardless of
the impact on emissions, the world now faces the prospect
of cheaper energy and transport costs than would otherwise
have been the case. The market alone would not have deliv-
ered this and no models predicted it. These opportunities
can crowd-in resources to pay for more expensive but nec-
essary technologies, such as large-scale direct air capture
technologies.
A decade ago, to the authors’ knowledge, no one pre-
dicted that renewables would become the dominant source
of energy investment by the second decade of this century,
surpassing coal, oil, gas, nuclear and hydro combined.5 Few
predicted the expansion in LED lighting from less than 5 per
cent to more than 40 per cent of the global market in the past
6years.6 Yet the processes underlying these developments
are predictable, and may be expected to apply to some of
today’s frontier technologies such as green hydrogen.
All this suggests that structural shifts, when they hap-
pen, can progress surprisingly fast following a long period
of apparent inaction and inertia. This further highlights
the importance to policymakers of explicitly integrating
co-benefits, uncertainties, path dependencies and irrevers-
ible thresholds into their comprehensive project assess-
ments, recognising the limitations of standard cost–benefit
analysis.7
The limitations ofstandard economic models
The prevalence of reinforcing feedbacks and tipping dynam-
ics largely invalidates traditional analytical approaches based
on assumed patterns of incremental change taking the world
as given as embodied in IAMs. As a result, not only are
models’ power to inform policy limited, for example by
missing the effect of credibility on the formation of expec-
tations, but also the expected costs of decarbonisation will
likely be overstated.
Fig. 4 Renewables, levelized cost $/MWh, 2018 real. Source
Bloomberg NEF: country weighted average using latest capacity
additions. Storage based on utility-scale Li-ion battery running at a
daily cycle and includes charging costs assumed to be 60% of whole-
sale power price in each country
4 https ://about .bnef.com/new-energ y-outlo ok/.
5 See: https ://www.bloom berg.com/news/artic les/2019-09-05/clean
-energ y-inves tment -is-set-to-hit-2-6-trill ion-this-decad e.
6 https ://www.strat egyr.com/Marke tRese arch/marke t-repor t-infog
raphi c-chip-on-board -light -emitt ing-diode s-cob-leds-forec asts-globa
l-indus try-analy sts-inc.asp.
7 Standard social cost–benefit analysis is often limited to a narrow
market failure framework, omitting broader spill overs and dynamic
interactions. The UK Green Book, used by officials to assess public
projects, for example, states that:
‘5.5 Social CBA and Social CEA are “marginal analysis” tech-
niques. They are generally most appropriate where the broader envi-
ronment (e.g. the price of goods and services in the economy) can be
assumed to be unchanged by the intervention. These techniques work
less well where there are potential non-marginal effects or changes
in underlying relationships. This is due to the difficulties inherent
in pricing such changes. It is possible to adapt Social CBA in these
cases, for example when appraising the cumulative impact of inter-
ventions on Natural Capital. Significant non-marginal issues which
cannot be reflected in Social CBA need to be appraised and consid-
ered at the long-list stage.’ – The Green Book.
2 https ://about .bnef.com/new-energ y-outlo ok/.
3 https ://www.linke din.com/pulse /scena rios-solar -singu larit y-micha
el-liebr eich/.
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959Sustainability Science (2021) 16:949–965
1 3
Most conventional approaches to determining the effi-
cient path for coping with climate change, including stand-
ard Integrated Assessment Models (IAMs), need to presup-
pose the technologies, tastes, preferences and behaviours
that will dominate in the decades and centuries ahead to
give the model structure (Zenghelis 2018a, b). But these
imposed structural assumptions are precisely the things we
want to know when predicting the costs of transitioning to
low-carbon networks, processes and behaviours. Marginal
static analysis techniques, which assume the wider world is
unchanged by the intervention, are inappropriate for non-
marginal, structural changes of global proportions.
Consider, for instance, the neoclassical DICE and RICE
models8 of Nordhaus. These are among the models most
widely used to quantify the costs and benefits of climate
policy. In this framework, capital and labour are used to
produce a single consumption good. The total productivity
of these factors depends upon a single technology parameter,
which is imposed and grows exogenously over time. Emis-
sion intensity of production also grows exogenously. This
leaves little of real interest that the model can tell us.
That said, simplified models like DICE can be useful for
transparent sensitivity analysis of key parameters. Grubb
and Wieners (2020), for example, challenge the assumption
of temporal independence whereby abatement costs in one
period are assumed unaffected by prior abatement. They use
DICE to illustrate how a ‘slow carbon price ramp’ approach
is inefficient in the case where carbon abatement costs are
shaped by innovation. They use the model to illustrate how
once a technology becomes sufficiently competitive, it starts
to change the entire environment in which it operates. In
such cases, the optimal strategy involves much higher initial
investment in abatement. For the same reasons, rather than
working along an abatement cost schedule picking off the
cheapest options first, it might make better sense to start with
some of the most expensive technological options to bring
their costs down faster (Vogt-Schilb etal. 2018).
More complex Computable General Equilibrium (CGE)
models, commonly used in IAMs, are no better equipped
to handle multiple equilibria and the transition from one
equilibrium to another (Mitra-Kahn 2008). Dynamic CGE
models rely on ‘backward-looking’ adaptive expectation for-
mation or ‘forward-looking’ rational expectation formation
to generate a smooth, efficient, balanced equilibrium path-
way. Both fail to account for the importance of expectations
in driving equilibrium shifts.
Structural macroeconomic models lack the restrictive
‘micro-foundations’ and optimisation assumptions of CGE
models, but they are reliant on estimated historical time
series to inform behavioural parameters. This also renders
them inadequate in making ex ante predictions of future
structural change which, by definition, will look very dif-
ferent from the past.
Grubb (2018)points out that if technology substitution
in a structural transformation is intrinsically dynamic and
irreversible, with technologies “striving” for dominance,
new technological systems can rapidly scale-up and dis-
place older ones in a way that cannot be determined from
examining past data in that sector (Fig.5). In such cases,
technological penetration is best described in the form of a
logistical substitution or S-curve:
Models applying ‘historical futures’ analysis by way of
incremental improvements in energy and carbon efficiency,
or which focus exclusively on what policies have worked in
the past, are often doomed to under-predict the scope and
pace of change simply because when it comes to structural
transitions, the past is no guide to the future.
deployment at time(t)
=
MAX
1+ae
−k(t−t0)
.
Fig. 5 Systemic network transi-
tions Source: Grubb 2018
8 https ://sites .googl e.com/site/willi amdno rdhau s/dice-rice
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960 Sustainability Science (2021) 16:949–965
1 3
Incorporating features of path-dependent phenomena—
switching costs, inertia, knowledge spillovers, network
effects, feedbacks, and complementarities—into economic
models leads to a multiplicity of ‘equilibria’, each dependent
on a different development path (Aghion etal. 2014).
This makes it very hard to predict costs and benefits
over the next few decades, and explains why conventional
economic models, even though they often make unrealistic
assumptions about optimal policies (such as the application
of a uniform global carbon price) which ought to under-
state the costs of decarbonisation, in general systematically
overstate the costs of decarbonisation. It also means that
the answer to the net cost of decarbonisation question is
endogenous. Innovation in technologies, behaviours and
institutions is shaped by action which will determine costs
and benefits. Traditional economic models have their place,
but their limitations need to be understood.
What does this mean for‘green growth’?
Spurious model projections have spawned often diametri-
cally opposed and mostly flawed assessments of our ability
to live sustainably. One set of authors uses the high-cost
projections to question whether ambitious mitigation offers
value for money. Integrated assessment models like RICE,
DICE and FUND conclude global carbon prices should start
low and follow a ‘slow policy ramp’. In his Nobel Prize
speech, William Nordhaus, the architect of RICE/DICE,
described global temperatures of 3 or 4 degrees above prein-
dustrial levels—levels climate scientists view as potentially
catastrophic—as ‘optimal’ given the high costs of adjust-
ment in his models. This is a view most recently endorsed
by Lomborg (2020).
A second camp draws the reverse conclusion. They
argue that if absolute decoupling between consumption and
emissions is prohibitively expensive, then the only feasi-
ble approach to decarbonisation and living within planetary
limits is reduced consumption and output—often termed
‘degrowth’ (Jackson 2016; Hickel and Kallis 2019).
Prosperity and wellbeing is about more than just GDP
growth. But it is important not to mistake output growth with
growth in material inputs such as fuels, minerals, ecosystem
services and capital equipment. This ignores the dynamic
scale economies associated with innovation. Unlike mate-
rial resources, knowledge is weightless and when used is
hard to deplete (Quah 1999). Indeed, knowledge builds on
knowledge: one of the sources of endogenous growth is that
constant or increasing returns to ideas can overcome dimin-
ishing returns to physical capital (Weitzman 1996; Hepburn
and Bowen 2013).
Innovation can reduce material throughput for each unit
of GDP value created and will do so more as electricity
generation is decarbonised. This is reflected in the increas-
ing importance in national income of intangible,knowl-
edge-products—computersoftware, new media, electronic
databases and libraries, and online services. Endogenous
growth theory developed by Romer (1990) highlighted how
increasing returns to ideas overcome the diminishing returns
to factors like labour and capital generating resources for
further investment.
Degrowth is not the place to start when there are so many
untapped opportunities associated with sustainability, espe-
cially as history suggests that declining economies are nei-
ther efficient in their use of resources nor clean. In any case,
economic contraction would be among the most expensive
solutions, significantly undermining welfare (Zenghelis
2019).
From a practical perspective, degrowth is likely to prove
a hard sell, particularly in parts of the rapidly developing,
populous world where growth is (rightly) seen as a pri-
mary means to eradicate poverty. In any case arguments for
‘degrowth’ overlook the extent to which the loss of natural
capital is already constraining economic growth, in line with
the perception that natural capital, rather than manufactured
capital, is now the scarce production factor (UNEP 2011).
The approaches adopted by both the degrowth and wait-
for-technology camps serve to delay action, using models
which overstate the costs of decarbonisation and discour-
age businesses and policymakers from investing in new
technologies and infrastructure. The problem is worse than
one of spurious precision and bad forecasts. Those who use
static models not only get the future wrong, they make the
future wrong by generating what game theorists call an infe-
rior Nash equilibrium.9 To the extent that such models are
believed, they become self-fulfilling, reflecting once again
the key role of expectations.
Paul Romer, a key architect of the endogenous growth
framework, focused on the dynamics of growth embodied in
innovation, network effects and complementary feedbacks.
He emphasised path-dependency and the power of decisions
today to profoundly shape and reshape the future. Romer
states:
“What the theory of endogenous technological pro-
gress supports is conditional optimism, not compla-
cent optimism. Instead of suggesting that we can relax
because policy choices don’t matter, it suggests to the
contrary that policy choices are even more important
than traditional theory suggests.”
Models that fail to understand this will consistently get
(and make) the future wrong. Our ability to cost-effectively
9 https ://www.benne ttins titut e.cam.ac.uk/blog/mind-over-matte
r-how-expec tatio ns-gener ate-wealt h/.
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961Sustainability Science (2021) 16:949–965
1 3
transition to a sustainable economy will be a function of the
decisions we take today.
Ways forward
All this suggests that the economic toolkit can be put to
better use helping policymakers understand and steer path-
dependent processes. Economics will need to draw from a
range of disciplines, integrating perspectives from the social,
physical, and natural sciences as well as the humanities. This
needs to include history, spatial geography, planning and
social psychology, game theory, anthropology, epidemiol-
ogy, computer and network science and sociology to derive a
richer and more valuable understanding with which to guide
decision-makers (Haldane and Turrell 2018).
One approach suggests that, in addition to theoretical and
network-based analysis, dynamic models of the economy
should be coupled with models of opinion dynamics and
behaviour by use of agent-based models. These explicitly
reflect interactions between heterogeneous, networked indi-
viduals in place of conventional ‘representative agents’
(Farmer and Foley 2009). As a result, they offer insights into
the probability and processes through which economies shift
from one equilibrium to another (Mealy and Hepburn 2019).
A number of authors now recognise that better under-
standing the processes and innovations which generate the
cascades of tipping described above is more valuable to
policymakers than speculative projections of costs. By tak-
ing advantage of the inherent domino effect of rapid, self-
amplified and contagious change, policymakers can leverage
highly sensitive “tipping interventions” that deliver outsized
impact (Schellnhuber etal. 2016; Farmer etal. 2019) which
could hasten global decarbonisation (Tàbara etal. 2018)10.
Rather than focus on predictions based on ‘historical
futures’, information on innovation processes can be gleaned
by looking at historical transitions, such as the change from
kerosene use to electricity, horse and cart to combustion
engines and photographic film and records to digital photos
and music (Zenghelis etal. 2018).
The trigger could be, for example, a specific climate or
energy policy or a breakthrough technology (such as cheap
and effective energy storage). The point is that policies,
institutions, and technologies reinforce each other in a posi-
tive feedback loop precipitating take-off and diffusion of
sustainable forms of production. Targeted tipping interven-
tions could simultaneously precipitate mutual reinforcement
and overcome barriers to decarbonisation (Rickards etal.
2014). Our analysis of strategic complementarities in sec-
tion“Feedbacks in preferences, behaviour and expectations”
showed how agents base their decisions on how they antici-
pate others will act (van der Meijden and Smulders 2017).
This collectively underscores the importance of leadership
and clear credible policies to guide investors (Aral 2011)
and kickstart the green innovation machine through public
investment, guarantees and risk sharing.
The low-carbon transition is likely to have influence
beyond rich-world economies, with many developing coun-
tries encountering significant structural shifts of their own.
Rapid change in technologies, policy frameworks and mar-
kets are rendering traditional industrial development routes
less viable. Development agencies and multilateral financi-
ers are seeking to diversify assets and lock into profoundly
different sustainable pathways (Peszko etal. 2020). Multi-
lateral funding supported by enhanced technological diffu-
sion can promote both development and decarbonisation and
allow countries to leverage global finance to deploy green
technologies and generate capacity in new technologies
(Hidalgo etal. 2007; ECA 2016).
None of this is to say that a managed low-carbon transi-
tion is inevitable. Political economy barriers and effective
lobbying by incumbents could continue to slow progress in
hard-to-transition sectors such as industry (in particular met-
als, ceramics, chemicals cement and plastics), aviation, ship-
ping and haulage (Energy Transition Commission 2018).
This could prevent a shift to net zero in time to avoid critical
climate risks. But, in line with Paul Romer’s conditional
optimism, the fact that we may not profitably do what is nec-
essary in time does not mean we cannot do so. A prerequisite
for doing sowould be leadership and a common understand-
ing of the costs and opportunities, a role facilitated by the
appropriate application of the economists’ toolkit.
On a final note, shortly after the publication of the GEO-6
report, and after this paper was first drafted, the world was
transformed by the Covid-19 pandemic. A number of stud-
ies have highlighted the fact that the move from pandemic
lockdown and rescue to post-pandemic recovery offers an
opportunity to ‘build back better’ so as to secure resilient,
inclusive and sustainable growth (Hepburn etal. 2020).
There is a growing realisation that the growth model that
followed the great financial crash marked a wasted opportu-
nity (Stern etal. 2020).
The post-Covid recovery marks an opportunity to invest
surplus desired saving into a broad range of productive com-
plementary assets, including physical, human, knowledge,
social and natural capital, to secure future prosperity (Agar-
wala etal. 2020). Because these investments in society’s
comprehensive wealth utilise a surplus of desired global
savings, which has pushed global real risk-free interest
rates below zero, the benefits of public investment based on
mounting public debt are likely to exceed the costs, for most
countries able to borrow in their own currency (Zenghelis
etal. 2020). As part of a coordinated and strategic policy
10 See Oxford Martin School, “Programmes: Post-carbon Transi-
tion,” www.oxfor dmart in.ox.ac.uk/resea rch/progr ammes /post-carbo n.
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962 Sustainability Science (2021) 16:949–965
1 3
framework, they also have the potential to leverage in far
larger sums of private investment (Green Finance Taskforce
2018). Low- and middle-income countries have less scope to
rely on public borrowing and are likely to need augmented
support from high-income countries to access finance and
technologies necessary to secure sustainable growth, once
the pandemic has been brought fully under control.
Conclusions
Given limited time and resources available to address
mounting concerns, traditional economic approaches to
assessing our response to environmental challenges are not
only flawed, they are dangerous. Physical science shows the
threat posed by complex adaptive systems surpassing critical
thresholds and irreversible tipping points.
A key conclusion of this analysis is that starting early
by credibly steering expectations, inducing innovation and
directing investment is in all cases better than delay. Actively
managing a transition to a low-carbon, sustainable economy
means strong policy signals which allow governments and
businesses to avoid investing in high-carbon, resource-inten-
sive infrastructure, technologies and assets that are liable to
become stranded, devalued or redundant before the end of
their working lives. For all these reasons, we conclude that
‘grow now, clean up later’ is the second highest cost option
(assuming ‘clean up’ is possible). Only the existential costs
of never cleaning up are higher.
This paper has shown why delay is triply bad:
1. Climate damages mount as the stock of greenhouse
gases go up, and challenges from depleted and degraded
resources mount, especially when such degradation,
such as in respect of land and marine ecosystems, is
irreversible.
2. Climate and resource depletion damages mount much
more quickly as productivity growth is eroded through
endogenous effects of devalued and destroyed capital
(Dietz and Stern 2015)
3. Lock-in of resource- and carbon-intensive infrastruc-
ture, behaviour and institutions and reduced innovation
in substitutes increases the cost of attaining sustainable
pathways.
Early action can induce creativity and innovation and
generate tipping points as feedbacks and dynamics become
reinforcing. This is why the correct answer to the ques-
tion ‘what will it cost to decarbonise in the long run?’ is
‘it is endogenous’. It depends on the choices and actions
we take today and in the future. A common understanding
that a managed low-carbon transition is both imperative and
affordable is the most effective way to induce a rapid transi-
tion at least cost.
But understanding the endogeneity of the system and the
role of expectations in determining the evolution of costs
and competitive advantage suggests the whole notion (and
associated industry) of forecasting the cost of decarbonisa-
tion is somewhat misplaced. The economic toolkit needs to
be put to more creative use to help policymakers understand
and steer path-dependent processes.
This paper concludes that analytical insights can poten-
tially allow policymakers to leverage highly sensitive “tip-
ping interventions”, by taking advantage of the inherent
domino effect of self-amplified and contagious dynam-
ics. We are already seeing increasing returns to scale in
discovery and production, and we are seeing very power-
ful complementarities and positive feedbacks in systems.
Transformative change is gripping key global energy and
transport sectors after decades of inertia: new networks,
behaviours and institutions are replacing old. Policymakers
and businesses are increasingly adopting risk management
and hedging strategies that limit investment in conventional
technologies and behaviours that may be rendered stranded
or devalued. This is not the context of standard growth
models, yet policy is needed to support and accelerate this
momentum.
Recent evidence suggests the short-term GDP impacts
of well-designed environmental action could be positive,
crowding-in rather than ‘crowding out’ the drivers of future
growth. Moreover, much environmental harm is irreversible,
most obviously biodiversity loss and tipping points associ-
ated with a changing climate. This paper provides evidence
that not only makes the environmental case for action, in
terms of its benefits for human health and welfare, it also
shows how such action can generate economic returns in
terms of productivity, jobs and income and reduce the costs
of meeting any emissions and resource use targets. A cost-
effective low-carbon, resource-efficient transition can gener-
ate a cleaner, quieter, more secure, innovative, and produc-
tive economy for all countries at all stages of development.
But our optimism is conditional. It requires credible and
ambitious action in the near term to avoid catastrophic and
irreversible environmental risk by overcoming continued
inertia in unsustainable activities, and time is not on our
side. There is no room for fatalism and complacency. Using
the wrong economic tools to assess the costs of systemic
technological and behavioural transformation to address
climate change delays action. Understanding the dynamic
process of innovation, on the other hand, means putting
investment, innovation and technical change at centre stage.
Open Access This article is licensed under a Creative Commons
Attribution 4.0 International License, which permits use, sharing,
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
963Sustainability Science (2021) 16:949–965
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included in the article’s Creative Commons licence and your intended
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use, you will need to obtain permission directly from the copyright
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