Presentations of the OECD 2nd CIRCLE technical workshop (2-3 Oct. 2014)

Thursday 2 October 2014 (Day 1)
09:30 – 10:00 Opening session
Speakers Shardul Agrawala (OECD)
 This short opening session presents the background for the workshop. It informs
participants of the general progress made so far in the CIRCLE project and the guidance
given by EPOC.
Background
material
• “CIRCLE: Assessing environmental feedbacks on economic growth and the benefits (and
trade-offs) of policy action; Scoping Paper”, ENV/EPOC(2013)15
• “CIRCLE: Overview, approach and update”, ENV/EPOC(2014)7
10:00 – 11:30 The land-water-energy nexus
Speakers Ton Manders, Netherlands Environmental Assessment Agency (PBL)
Rob Dellink (OECD)
Key questions  How are the biophysical linkages between water, energy and land use represented in the
IMAGE model?
 How can these biophysical aspects be coupled to an economic model?
 Which biophysical aspects of the land-water-energy nexus are most crucial for economic
growth?
Background
material
“Economic impacts of the land-water-energy nexus; exploring its feedbacks on the global
economy”, ENV/EPOC(2014)15
11:30 – 12:00 Coffee break
2
CIRCLE Worshop Outline – Day 1 (AM)

Second ad-hoc technical workshop on
CIRCLE, 2-3 October 2014, OECD, Paris
3
Economic Impacts of
the Land-Water-
Energy Nexus
Exploring its feedbacks on
the global economy

The land-water-energy nexus
Fritz Hellman, Tom Kram, Ton Manders
4
Content
• What is the nexus?
• Main bottlenecks
• Modelling framework
• Preliminary results

Land-Water-Energy nexus
 Strong linkages between land, water and energy
 Competition for the same resources
 Tension grow over time
 An integrated analysis is needed
 A desaggregated analysis is needed
6

Main bottlenecks
linkage importance
Water for agriculture
Water for energy
Agriculture for energy
Agriculture for water
Energy for agriculure
Energy for water
Land for agriculture
7
Table 1 Existing links in IMAGE and ENV-Linkages

Bottlenecks: water use
8

Water stress matters
9

Bottlenecks: bioenergy
10

Bottleneck: land-use
11

Bottlenecks: land-use
12

Feedbacks between IMAGE and Env-Linkages
ENV-Linkages
Economy (agricultural
demand)
population
IMAGE
Land supply, yield
(water supply)
(health)
(biodiversity)
OECD-CIRCLE 13 Workshop October 21 -22, 2013 | Ton Manders

Nexus in modelling framework
NEXUS-links: IMAGE ENV-Linkages CIRCLE
Water for agriculture Yes No Yes
Land for agriculture Yes Yes Yes
Agriculture for water Yes No No
Energy for agriculture No Yes Yes
Agriculture for energy Yes Yes Yes
Water for energy No No No
Energy for water No No No
14

Preliminary results: groundwater & irrigation
 Step 1:
– Baseline with plenty groundwater for irrigation
 Step 2:
– Simulation without groundwater for irrigation.
– Agricultural production losses (IMAGE)
– “Shock” ENV-Linkages with production losses
– Economic impact of poduction losses (ENV-Linkages)
 Step 3:
– Compare regional + sectoral production, trade, GDP, etc.
between baseline and simulation variant-> cost of inaction!
15

IMAGE water & irrigation:
16

IMAGE water & irrigation:
17
Lower irrigation
yields
Reallocation
irrigated
agriculture
Increase area
rainfed
agriculture
Lower overall
yields
Production
losses to ENV-Linkages

World
Rice (yield)
18

Rice yield: India Rice yield: Indonesia
19

Next: other simulations
 Bottlenecks regarding water availability:
– Water allocation variant
– Water efficiency techniques variant
 Bottlenecks regarding land availability
– Land degradation variant
– Land supply variant
 Other bottlenecks:
– Ozone variant
– Climate change variant

Thank you
fritz.hellman@pbl.nl
ton.manders@pbl.nl
www.pbl.nl
21

IMAGE
Energy supply/demand
Drivers
Land use Emissions
Carbon cycle
Crops
Natural vegetation
Earth system
Atmosphere Water cycle
Impacts
Agricultural
demand/production
22

THE LAND-WATER-ENERGY NEXUS:
CONSEQUENCES FOR ECONOMIC
GROWTH
Rob Dellink
Environment Directorate, OECD
CIRCLE Ad-hoc expert workshop
Paris, 2 October 2014

• Soft-linking different models
– Using the output of one model as input to another
– Using a common baseline so models all share the same set of
underlying common drivers (plus a set of model-specific drivers)
– Harmonise on other elements in the scenario storyline where
possible
• Staged modelling approach
– ENV-Growth provides macroeconomic projections
– ENV-Linkages provides sectoral economic projections and
emissions
– IMAGE provides biophysical impacts and bottlenecks
– Economics feedbacks to ENV-Linkages where possible
24
Linking different modelling tools

The first stages of the modelling track
Macroeconomics:
ENV-Growth
Structural economics & environmental pressure:
Land-water-energy
nexus:
IMAGE model
suite
ENV-Linkages
25
Stand-alone
modules for
e.g. natural
resources
Climate change:
ENV-Linkages
climate module
Air pollution:
range of models

26
The ENV-Linkages model
• Computable General Equilibrium (CGE) model
• Multi-regional, multi-sectoral
• Full description of economies
• All economic activity is part of a closed, linked system
• Simultaneous equilibrium on all markets
• Structural trends, no business cycles
• Dynamics
• Solved iteratively over time (recursive-dynamic)
• Capital vintages
• Link from economy to environment
• Greenhouse gas emissions linked to economic activity
• Other pollutants forthcoming…
• Potential future work on water use?
… and back

• Make use of the details of the CGE model where possible
– sectoral disaggregation
– explicit production function
– captures both direct and indirect effects
– relatively well-established for climate change damages, but for
other environmental challenges the links to economic variables is
much less clear
• Keep separate where needed
– Valuation of non-market damages
27
Incorporating feedbacks into a general
equilibrium model

28
Linking IMAGE output to ENV-Linkages
• The direct impacts are included in the IMAGE model
• ENV-Linkages calculates macroeconomic costs, which
includes indirect impacts
Impacts on
economic
growth
Indirect impacts
Direct
impact
Sector
Agricul-ture
Changes
in crop
product-ivity
Changes
in crop
prices
Changes in food prices
Changes in trade specialization
of agriculture / food products
Changes in prices and demands
of other goods
Changes in household income
and government revenues
…
Change
in GDP
Change
in
welfare

THANK YOU!
For more information:
www.oecd.org/environment/CIRCLE.htm
www.oecd.org/environment/modelling
rob.dellink@oecd.org

Thursday 2 October 2014 (Day 1 - Continued)
12:00 – 13:00 Biodiversity and ecosystem services
Speakers Anil Markandya (BC3)
Key questions  What is the state-of-the-art knowledge on the consequences of the loss of biodiversity and
ecosystem services for economic growth?
 How to link loss of biodiversity and ecosystem services to economic growth?
 What are the main opportunities and obstacles in including biodiversity and ecosystem
services into a dynamic CGE model?
 Is it worthwhile to pursue this theme in the project through large-scale economic modelling
and if so, what should be the next steps?
Background
material
“The economic feedbacks of loss of biodiversity and ecosystems services”, ENV/EPOC(2014)16
30
CIRCLE Worshop Outline - Day 1(Cont.)

The economic feedbacks of loss of
biodiversity and ecosystems
services
Anil Markandya
Basque Centre for Climate Change
October 2014

Purpose of the Scoping Study
• The cost of past economic growth in terms of loss
of biodiversity and functioning of ecosystems and
has been studies in some detail.
• But less has been done on the effects these
losses have in terms of reductions in economic
performance.
• Or on what the benefits would be of shifting to
green growth paths.
• This study aims to examine the evidence on the
two questions and outline what further work is
needed incorporate losses of biodiversity and
ecosystem services within CGE models.
32

Ecosystem Services: A Key Concept
• The Millennium Ecosystem Assessment set up in 2005
a generic framework of ecosystem services (ESS),
categorising them into four typologies: provisioning
services, regulating services, cultural services, and
supporting services.
• This has been adopted widely, with variations in the
detailed definitions of the different services.
• If our interest is valuation it is useful to focus on final
ecosystem services, while accounting for ecosystem
processes and intermediate ESS as relevant in
determining the final values.
• The categories of final services vary across studies.
33

Categories of ESS in TEEB
Provisioning Services
Food
Water
Raw Materials
Genetic Resources
Medicinal Resources
Ornamental Resources
Habitat Services
Nursery Service
Genetic Diversity
Regulating Services
Air Quality
Climate Regulation
Disturbance Moderation
Water Flow Regulation
Erosion Prevention
Nutrient Recycling
Pollination
Biological Control
Cultural Services
Esthetic Information
Recreation
Inspiration
Spiritual Experience
Cognitive Development
Empirical estimates have been made for all these categories.
34

ESS and Biodiversity
• Biodiversity: “the variability among living organisms from
all sources including, inter alia, terrestrial, marine and
other aquatic ecosystems and the ecological complexes
of which they are part.
• Ecosystem are “a dynamic complex of plant, animal and
micro-organism communities and their non-living
environment interacting as a functional unit” and ESS are
benefits derived from ecosystems.
• Loss of biodiversity affects ecosystems significantly but
links are complex and direct valuation of biodiversity is
difficult.
• For this reason operational focus has been on ESS but
some account of biodiversity loss on ESS has been taken
through measures of Mean Species Abundance (MSA) in
different habitats.
35

Valuation of ESS
• Considerable work on valuing final services by
biome and geographical location.
• TEEB review documented 320 studies across
10 biomes, covering 300 locations. Derived
from many databases such as EVRI, COPI etc.
There are many more “studies” but details are
not sufficient for them to be evaluated.
• Less work on valuing changes in final services
when the ESS is modified or degraded.
36 see www.es-partnership.org for information on most of these databases

Global Studies: 10 Biomes
Biome Biome
Marine (Open Oceans) Freshwater (Rivers/Lakes)
Coral Reefs Tropical Forests
Coastal Systems (1) Temperate Forests
CoastalWetlands (1) Woodlands
Inland Wetlands Grasslands
(1) Coastal systems include estuaries, continental shelf areas and sea grass but
not wetlands such as tidal marshes, mangroves and salt water wetlands
37

Main Valuation Findings for ESS
• Considerable work in reviewing and synthesizing
valuation studies was done in the TEEB report.
• Values are generally expressed in terms of
$/ha./yr.
• Some studies carry out a meta analysis giving
these values as a function of site characteristics.
• The average values across studies are significant
but with large ranges indicating the need to work
at a spatially disaggregated level.
38

How Are the Values Derived?
ESS Direct Market
Values
Cost Based
Methods
Revealed
Preference
Stated
Preference
Provisioning 84% 8% 0% 3%
Regulating 18% 66% 0% 5%
Habitat 32% 6% 0% 47%
Cultural 39% 0% 19% 36%
• Direct Market Values include: market pricing; payment for
environmental services; and factor income/production
function methods
• Cost Based Methods include: avoided cost, restoration cost;
and replacement cost
• Revealed Preference: hedonic pricing and travel cost
• Stated Preference: contingent valuation, conjoint choice and
group valuation
39

What Are the Numbers?
• Values are Int.$/Ha./Yr., 2007 price levels
ESS Mean Median Min/Mean Max/Mean
Oceans 491 135 17% 339%
Coral Reefs 352,915 197,900 10% 603%
Coastal Systems 28,917 26,760 90% 145%
Coastal Wetlands 193,845 12,163 0.2% 458%
Inland Wetlands 25,682 16,534 12% 409%
Rivers & Lakes 4,267 3,938 34% 182%
Tropical Forest 5,264 2,355 30% 396%
Temperate Forest 3,013 1,127 9% 545%
Woodlands 1,588 1,522 86% 138%
Grasslands 2,871 2,698 4% 207%
De Groot et al, Ecosystem Services, 2012.
40

Comments on Values
• The values vary by biome, both means and
ranges.
• Other review studies come up with different
mean values
• Numbers of studies on oceans, coastal systems
and woodlands and grasslands are relatively few
in number. Many more for wetlands and forests.
• Relatively few studies in developing countries
(although there are some in most categories)
• Estimates can be targeted for a given site in a
given location using meta analytical functions.
41

Meta Analytical Functions Estimated
• Unit value as a function of site and user
characteristics have been made for:
– Inland wetlands, Tropical and Temperate forests,
Grasslands, Mangroves, Coral Reefs
• Main explanatory variables include:
– Size of the site, income level in the country, number
of people using the site, NPP in the area around the
site, presence of other sites nearby, method of
estimation used.
– Quality of the site rarely appears as a variable
• Functions not all well determined.
42

Application in Economic Models
• The usual databases are not so useful for
estimating the impact of changes in the quality of
biomes
• We have to look at more detailed studies of
different ESS and how changes in their function
due to external factors can effect the services
they provide.
• A number of studies have attempted to do that
using spatially disaggregated data but economic
valuation is included only in some, and to a
limited extent.
43

Incorporating ESS Values in Economic
Models: Key Questions
• Does the model include ESS in both directions – i.e. the impact of
economic changes on ESS and thereby on welfare as well as the impact of
ESS changes on production possibilities for goods and services and thereby
on growth?
• Does the model take account of the inter-relationships between markets
– i.e. does it have a general equilibrium structure –allowing for market
imperfections such as unemployment, trade barriers etc.?
• Does the model include a spatial dimension so that ecosystems impacts of
growth can be taken into account different depending n where they
occur?
• Is the coverage of ecosystems complete – i.e. are all biomes included in
the system?
44

Models and Approaches Examined
Model Ecosystem Economics Other
GUMBO* 11 biomes, ESS feed
into production and
welfare functions
Economic output based
on capital, labor,
knowledge. Links from
ESS to Economic module
No spatial modeling.
Economic module
not CGE. ESS
valuation sketchy
GLOBIO-IMAGE
ESS from biomes
affected by socio-economic
drivers
LEITAP, extended
version of GTAP, used to
model land use changes
Changes in land for
agriculture affects
different biomes.
Spatially explicit.
InVEST Production
functions linking
LULC type to ESS
Economic production
functions determine
demand for land & ESS
Still developing.
Coverage not global
as yet. Not CGE.
UK NEA ESS from different
biomes spatially
disaggregated scale
Scenarios estimate
changes in ESS
No economic
modeling but ESS
changes valued for
some services
* MIMES, spatial version of GUMBO is being developed
45

Causality from ESS Changes to
Economic Functions
• All the above models examine the implications of
economic development growth on ESS in either
physical or monetary terms.
• However, the only models that explicitly account
for the impact of ESS changes on economic
performance are the GUMBO-MIMES set. In
these ESS services affect the measure of “natural
capital”, which in turns enters as an input to the
production function for other goods and services.
• But modelling is at a very aggregate level and
there is a need to develop it further.
46

Use of a general equilibrium structure
• The only model that has a link with a general
equilibrium structure is the IMAGE-GLOBIO model,
which consists of an economic module which examines
different development scenarios. It also has a spatial
disaggregation.
• Effects of different growth paths on MSA-adjusted ESS
are estimated for a number of services (but not all).
• But ESS do not directly enter the production of goods
and services and so the feedback from a loss of ESS to
the economy cannot be tracked in the model.
• It also does not have money values for ESS, although
some parallel work has been done on these.
47

Inclusion of a Spatial Dimension
• The spatial dimension is incorporated into
GLOBIO-IMAGE, InVEST and the UK NEA but
not in GUMBO (although MIMES is working on
developing that).
• The importance of including this aspect into
the modelling is highlighted by the fact that
the impacts of different scenarios on
ecosystem functioning are found to vary
considerably by location.
48

Coverage of Ecosystems in monetary terms
• The coverage of ecosystem services in
monetary terms is not entirely complete in the
models examined.
• E.g. Those models that do value ESS in money
terms cover marine ecosystems to a limited
extent if at all.
• Focus on valuation tends to be on forests,
wetlands, lakes and rivers and croplands.
49

Need for Further Development
• More work is needed to model the linkages
from changes in ESS to the functioning of the
economy.
• Modelling that exists (e.g. GUMBO) is too
aggregated and does not have a CGE
structure.
• CGE models on the other hand do not have
ESS in the production functions.
50

Possible Steps Forward
• First a soft link can be made between the ESS
value changes and the economic models.
• Alternative growth paths can be evaluated in
terms of the losses or gains they imply for
different ESS and these values can be used to
adjust the estimated GDP growth rate, to give a
“corrected GDP”.
• This work can be based on the IMPAGE-GLOBIO
Model, for example, with valuation work that has
been done using that model, being linked to the
typical OECD growth models.
51

Possible Steps Forward
• At the same time a second approach needs to be developed, in
which the integrated CGE models include ESS as specific inputs into
key sectors and where the output of these sectors affects the
functioning of the ESS.
• The inclusion of ESS into some sectors such as agriculture and
forestry should be relatively straightforward because linkages to
marketed goods are well developed
• It will be more challenging to cover services such as recreation,
tourism, and health (
• It will also be important to take account of connections between
ESS (e.g. the quality of cultural services depend on how well the
regulating services are functioning). This stream of work needs to
be undertaken in conjunction with the dynamic modellers who are
developing the combined framework of the OECD’s ENV-Growth
model as well as the dynamic computable general equilibrium (CGE)
OECD’s ENV-Linkages model.
52

Possible Work Plan?
A. Set up a database of state-of-the-art estimates of the
value of ESS at a spatially differentiated level so it can be
used in the economic models.
B. Calculate the losses of ESS associated with alternative
growth paths and use these figures to calculate an
adjusted GDP figure for each path, indicating the effect
that the losses have on “true GDP”.
C. Initiate work on integrating ESS into the economic models.
This can be done first for agriculture and forestry where
there is considerable information and then go on to
consider the more difficult sectors.
D. Combine the work on adjusted GDP with that on sectoral
production links to produce an integrated system that
includes both the effects of growth on ESS and the effects
of declines in ESS on growth.
53

Useful Readings
• Ten Brink P. (ed.) (2012)The Economics of Ecosystems
and Biodiversity in National and International Policy
Making. London: Earthscan, 352pp.
• De Groot R. et al. (2012) Global estimates of the value
of ecosystems and their services, Ecosystem Services,
1, 50-61.
• Hussain S. et al. (2013) “The Challenge of Ecosystems
and Biodiversity”. in Lomborg B. (ed.) Global Problems,
Smart Solutions, Cambridge University Press.
• Bateman, I. et al. (2013) Bringing Ecosystem Services
into Economic Decision-Making: Land Use in the United
Kingdom, Science, July.
54

Thursday 2 October 2014 (Day 1- PM)
14:00 – 15:30 Water-economy linkages
Speakers Tom Hertel (Purdue University)
Key questions  What are the main economic implications of water scarcity and water stress?
 How can water use and water supply be linked to economic growth?
 What are the main opportunities and obstacles in including water into a dynamic CGE model?
 Is it worthwhile to pursue this theme in the project through large-scale economic modelling and if
so, what should be the next steps?
Based on: “Implications of water scarcity for economic growth”, ENV/EPOC(2014)17
16:00 – 17:30 Resource Scarcity
Speakers Peter Börkey (OECD)
Renaud Coulomb (Grantham Research Institute at LSE)
Alexandre Godzinski (French Ministry of Environment)
Satoshi Kojima (IGES)
Key questions  What are the key research/policy questions in the topical area of resource scarcity that are
relevant from the point of view of environmental protection?
 Is resource scarcity an issue, and if so, what would be the consequences of supply disruptions,
long-lasting high minerals prices, or high price volatility on the economy and geopolitics?
 What role can recycling policies play in helping to mitigate resource scarcity and the associated
impacts on the economy?
 Is it feasible to include these themes into a dynamic CGE model and more generally what further
work could be developed within the CIRCLE framework to support efforts in this area?
Based on: “Critical raw materials in the OECD”, ENV/EPOC(2014)18
55
CIRCLE Worshop Outline – Day 1 (PM)

Water Scarcity and
Economic Growth
Thomas Hertel and Jing Liu
Purdue University
Presented October 2, 2014 to the
OECD CIRCLE Workshop
Paris, France

Three perspectives on water scarcity
and economic growth
• Water as a publicly provided good, with reuse, but
subject to congestion (Barbier, 2004)
• Water as a conventional input into the national
production function (in the tradition of Solow)
• Water in a global CGE model (allocative distortions,
second best effects and terms of trade changes)

Water as a publicly provided good with
congestion
• Optimal growth model
• Firms draw on common pool of water;
however, marginal productivity
declines with increasing withdrawals
(congestion)
• Cost of withdrawal rises at increasing
rate
• Optimal rate of water utilization
maximizes economic growth rate
(Fig.1)
• Empirical results
• Focus on 163 countries during 1990’s
• Positive elasticity of growth wrt water
withdrawals (10% rise boosts growth
rate from 1.3% to 1.33%)
• Most countries could increase growth
rate by boosting water withdrawals
• Just 10% face extreme water scarcity
• However, sub-national story is surely
different

Water as a conventional input into
national production function: y = f(K,W)
• Central issue is the potential for substituting
accumulating human and physical capital for water,
summarized by

• If  
1 then, as K/W rises, water’s share of GDP will rise,
eventually limiting growth
• If  
1 then, as K/W rises, water’s share of GDP will
diminish and growth will not be constrained, as increasingly
abundant capital is used to improve water efficiency as well as
enhance available supplies of water to the economy
• But is an abstract concept – how can this be captured
in a CGE model? It is determined by four different
components:
• Sector level technologies
• Inter-sectoral responses to water scarcity
• Consumers’ willingness to substitute away from water intensive
goods
• Potential for recycling/reuse and desalinization

(Cont. from previous slide…)
Water as a conventional input into national
production function: y = f(K,W)

• Calculating implied value of from CGE-water
models would be a useful component of any
assessment of impact of water scarcity on growth

Water and real income growth in a global
CGE model:
• Direct cost to economy of reductions in water availability depends
on marginal value product of water in the CGE model; appropriate
valuation of water, by sector/use is critical
• In many economies there are large (even 100x!) divergences in
the MVP of water by sector; this opens the way for large second
best effects in the face of any exogenous shock, provided it results
in water reallocation
• Water scarcity can lead to reallocations across distorted sectors
which can improve, or exacerbate losses (Liu et al. find the latter)
• Terms of trade effects can also be significant as the price of water
intensive goods rises; welfare impact depends on geography of
trade

Irrigated Agriculture: The Dominant
Water Use
• Each calorie produced
requires roughly 1 liter of
water through crop
evapotranspiration; feeding
the world each year requires
enough water to fill a canal
10m deep and 100m wide
encircling the globe 193 times!
• Four-fifths is rainwater, one-fifth
is irrigation water;
accounts for 70% of global
freshwater withdrawals
• Irrigated area accounts for
nearly 20% of cropland and
40% of production

Groundwater irrigation has become increa-singly
important
• Accessible without large scale
government initiatives at low
capital cost (although high
operating costs)
• Offers irrigation on demand
• Reliability in time and space:
low transmission and storage
losses
• Drought resilience; surface
water not available during
drought
• If undertaken in areas with
high recharge rates, then it is
also sustainable

But most rapid growth has been in
arid areas with low recharge rates
65
Source: cited in Burke and Villholth

There is substantial scope for increasing
water use efficiency in agriculture, given
appropriate incentives:
• Improving delivery of water to plants: Global irrigation efficiency
= 50%
 But not all losses are really lost – reuse of water further
downstream
 Improved irrigation efficiency can also increase total use:
‘Jevons’ paradox’

There is substantial scope for
increasing water use efficiency in
agriculture, given appropriate
incentives (Cont.)
• Increasing ‘crop per drop’: Water use efficiency of crops
themselves
 Can be achieved by reducing non-beneficial evaporative losses
and limiting deep percolation of rainwater
 Also by boosting grains share of total biomass, limiting pest
damage, and improving drought tolerance
 Small-scale farms can boost production with less than
proportionate rise in water use; for commercial scale
operations, tend to rise in equal proportions

Evidence of conservation in the face
of scarcity:
The Australian experience
• Drought in 2002/3 led to a
29% drop in water usage in
the Murray-Darling Basin
• However, water used in
irrigated rice production
dropped by 70%
Flexibility facilitated by water trading:
when water is available, produce rice.
When it is scarce, sell water rights
instead of growing rice! (Will Fargher,
National Water Commission)

Evidence of conservation in the face
of scarcity:
The Australian experience
(Cont. from previous slide)
• Early modeling work failed:
– predicted only modest declines in irrigation water usage
– Missed the potential for:
• Shifting land to rainfed production
• Shifting rice production to other regions
• Required significant modification of the TERM-H2O CGE model

Increasing irrigation scarcity will alter
the geography of food trade
Red color means potential
irrigation demand is less satisfied
by actual irrigation consumption
Irrigation. reliability index =
actual water consumption / potential irrigation demand
Source: Liu et al. GEC,

Focus on India results…
Source: Liu et al. GEC, As output falls, consumers substitute low cost imports for domestic crops, exports
& production decline

Water use in power generation
• Hydropower consumes water
through evaporative demand
• Water for cooling is key water
demand
• World Bank report highlights
adverse impacts of water
scarcity:
– “In the past five years, more than 50% of
the world’s power utility and energy
companies have experienced water-related
business impacts. At least two-thirds
indicate that water is a
substantive risk to business
operations.”
– In India, South Africa, Australia and the
United States, power plants have
recently experienced shut-downs due to
water shortages for cooling purposes.

• Projections for India
suggest that power
sector’s share of water
use could rise from 4%
today to 20% in 2050 –
primarily for cooling;
abstracts from potential
for installation of water
efficient capacity

• Hydropower consumes water
through evaporative demand
• Water for cooling is key
power demand
• World Bank report highlights
adverse impacts of water
scarcity:
– “In the past five years, more than 50% of
the world’s power utility and energy
companies have experienced water-related
business impacts. At least two-thirds
indicate that water is a
substantive risk to business
operations.”
– In India, South Africa, Australia and the
United States, power plants have
recently experienced shut-downs due to
water shortages for cooling purposes.
• Projections for India suggest
that power sector’s share of

Residential, commercial & industrial
uses
• Residential demands well-studied:
– Average price elasticity of demand in industrialized
countries = -0.4
– In developing countries, households draw on multiple
sources of water: tap, wells, tankers, vendors, rain and
surface water – it is complicated!
• Urban formal: tap water – as with rich countries
• Urban slums: inadequate water and sewage svces; price is often
time
• Rural consumption: household labor required to collect water

Residential, commercial & industrial
uses
(Cont. from previous slide)
• Commercial sector is heterogeneous, difficult to
assess: assume same behavior as residential
demands
• Industrial demands vary greatly by industry:
– Water often self-supplied – hard to monitor
– Industrial steam is important source of demand for both
water and energy; conservation of energy leads to
reduced water use
– Scope for water savings, given incentives: elasticity= -
0.15 to -0.6 depending on sector

Environmental demands (in-stream
use)
• Requirements depend on total volume as well as high/low flows
• Portion of flow reserved for environmental purposes varies
from 10% (IFPRI’s IMPACT-WATER model) to 50% (IWMI
– see map below)

Water Supply
• What is the relevant spatial unit for supply?
• Global models focus on river basin; take inputs from
hydrological model
• Reuse of water is key:
– Seckler et al. suggest that reuse will be one of the
most important sources of supply in the coming
decades
– Main barrier to reuse is pollution; therefore
pollution control is source of water supply

Water Supply
• Luckman et al study reduced water availability in
Israel emphasizing reuse
– seven different types of water separately, breaking
out: freshwater, seawater, brackish groundwater
(all natural resources), which can be converted to
potable water, brackish water and reclaimed water
via some production process; also allow for
desalinization
– 50% reduction in freshwater costs economy
0.2%GDP
• Rules for allocation across sectors are critical

Research Challenges & Priorities
• Main barrier to global CGE modeling of water scarcity
is data availability: not broken out in the typical social
accounting matrix:
– Break out activities by river basin
– Identify physical volumes by use – draw here on
hydrological models
– What price? Marginal value product varies widely
across and within sectors
• Important to distinguish different types of water:
endowments, outputs, byproducts and intermediate
inputs along with associated technologies
• Putty-clay treatment to capture impact of new
investments on efficiency

Research Challenges & Priorities
• Need to establish links to hydrological models which:
– Ensure that laws of gravity are enforced!
– Incorporate impacts of infrastructure development
and depreciation
– Deal with temporal and spatial variation
• Important to accommodate alternative allocation rules
(e.g., M-D Basin water reforms)
– How will scarcity be accommodated?
– Which sectors have priority?
– Will scarcity lead to institutional reforms?

RESOURCE SCARCITY
– WHAT ARE THE KEY
ISSUES?
Peter Börkey – OECD Environment
Directorate

Decoupling trends, 2000 to 2011
Index 2000=100
150
125
100
75
50
GDP
material
consumption
OECD
2000 2002 2004 2006 2008 2010
Index 2000=100
150
125
100
75
50
GDP
material
consumption
World
2000 2002 2004 2006 2008 2010

Copper mine grades and recoveries
Source: Citigroup (2011)

Commodity prices are increasing

Reserves and cumulative output - Copper

CO2 per tonne of metal production

So what is resource scarcity?
• Physical scarcity is unlikely
• But it can be politically induced
• Rising opportunity costs appear likely
• A stronger constraint may come from a
scarcity of environmental sinks

What are the policy questions?
• What is the potential impact of resource scarcity on
the economy?
– Increasing commodity prices
– Supply disruptions
• What are the potential environmental impacts from
resource scarcity?
• What is the role that circular economy policies can
play?
– Growth
– Jobs
– Material security
• What is the impact that the transition towards green
growth will have on resource scarcity?

Three presentations
• Out of model approach
1. LSE – the critical materials approach (is
resource scarcity real?)
• Macro-economic modelling
2. France – how to represent the circular
economy in a CGE framework
3. IGES – how to include resource scarcity in a
CGE framework

Questions for discussion
• What are the key research/policy
questions?
– Is resource scarcity an issue, and if so, what is
its impacts the economy and geopolitics?
– What role can circular economy policies play?
• Is it feasible to include these themes into a
dynamic CGE model?
• And more generally what further work
could CIRCLE develop in this area?

CRITICAL
MATERIALS
IN THE OECD TO 2030
Renaud Coulomb, Post Doctoral Researcher
r.coulomb@lse.ac.uk

AGENDA
I. The Challenge
II. Analytical Framework
a) Economic Importance
b) Supply Risk
III. Static Findings
a) Sectors Affected
IV. Introducing Dynamics
a) Sectorial Changes
b) Production shifts
V. Policy efforts

I) THE CHALLENGE
Raw materials are economically important as sectors such as
energy, transportation, and communications crucially rely upon
them.
Three mega trends:
1) Increasing demand driven by emerging markets
(see Krausmann, 2009)
2) New technologies require large amounts of rare materials
(DERA, 2012)
3) A slowdown in high-grade deposits discoveries after 2000
The current and future criticality of individual materials will depend
on their economic importance and how likely they are to face
supply disruptions.
In order to inform effective policy we set out to map material
criticality for 54 materials in the OECD countries up until 2030.

II) ANALYTICAL FRAMEWORK
Our methodology draws on the previous research: EU (“Critical Raw
Materials” 2010, 2014), US (“Minerals, Critical Minerals, and the US
Economy” 2007), UK (“Material Security” 2008), etc., focusing on a
new scope of countries and adding dynamics.
Criticality is assessed across two dimensions:
• Economic Importance determined by:
• Use of materials across sectors
• Value added of these sectors
• Supply Risk determined by:
• Concentration of production
• Distribution of reserves
• Political stability of major producers/holders of reserves
• Recycling rates
• Substitutability

II-A) ECONOMIC IMPORTANCE
퐸푐표푛표푚푖푐 퐼푚푝표푟푡푎푛푐푒푖 =
1
푠 푄푠
푠
퐴푖푠푄푠
i – material
s – sector
• 퐴푖푠 - The share of consumption of material i in end–use sector s
• 푄푠 - GVA of sector s
A material that is used heavily in a sector that constitutes a large part
of the economy will have a relatively high Economic Importance index
value.
Index is calculated for 54 materials in 17 Megasectors (Q) with total
GVA of 20% GDP.
Data sources: share of consumption (EU 2014, USGS 2014, etc), GVA
(OECD).

II-B) SUPPLY RISK
i – material
s – sector
c – country
푆푢푝푝푙푦 푅푖푠푘푖 = 휎푖 1 − 휌푖
푐
(푆푖푐 )2푃표푙푆푡푎푏푐
• 휎푖 - Substitutability = 푠 퐴푖푠휎푖푠
• 휌푖 - Recycling rate
• 푆푖푐 - Production shares by countries
• 푃표푙푆푡푎푏푐 - Political stability by countries
The Supply Risk index is high if a material has few substitutes, low
recycling rates, and production is concentrated in politically unstable
countries.
Data sources: substitutability and recycling (EU 2014, USGS 2014 etc),
production (BGS 2014, WMD 2014 etc), political stability (WGI 2014)

III) STATIC FINDINGS
*Natural Rubber

III-A) SECTORS AFFECTED
21 critical materials are:
Antimony, Barytes, Beryllium, Borate, Chromium, Cobalt, Fluorspar,
Gallium, Germanium, Indium, Magnesite, Magnesium, Natural
Graphite, Niobium, PGMs, Phosphate Rock, REE (Heavy), REE
(Light), Silicon Metal, Tungsten, Vanadium.
The following Megasectors are affected (number of critical
materials affecting each Megasector):
Metals (Basic, Fabricated & Recycling) (18), Other Final Consumer
Goods (16), Chemicals (12), Electronics & ICT (10) ,Electrical
Equipment (7), Road Transport (7), Plastic, Glass & Rubber (6),
Mechanical Equipment (5), Construction Material (4), Refining (2), Oil
and Gas Extraction (2), Aeronautics, Trains, Ships (1), Beverages (1)

IV) INTRODUCING DYNAMICS
The project entails making projections up until 2030.
To meet this requirement the framework should be modified to
account for the underlying dynamics of material supply and
demand.
The team suggests that:
• The dynamics of Economic Importance are captured by
incorporating the OECD forecast of sectorial composition into
the analysis.
• The dynamics of Supply Risk are incorporated by introducing
three supply scenarios based on current production shares and
reserves.
Other factors that can affect criticality in the future: exploration
of land to increase reserves and lower concentration, new
extracting technologies etc.

IV-A) SECTORIAL CHANGES
Tomorrow’s economy will be different from today’s, criticality of
materials will be affected by changes in sectorial composition
driven by:
1) Emerging technologies
• Thin layer photovoltaics (gallium, indium), fibre optic cable
(germanium), seawater desalination (palladium, titanium,
chromium), micro capacitors (niobium, antimony), etc
2) General economic trends
• Diminishing share of agriculture
3) Policy focus
• Green policies

IV-B) PRODUCTION SHIFTS
The producers of the materials currently used in the OECD are likely
to change over time as reserves are depleted.
This should be accounted for in Supply Risk estimates and the team
therefore suggests evaluating three scenarios of future production:
1) production sources are assumed constant at current levels
(i.e. the countries of origins and their respective share of total supply
does not change over time)
2) production converges towards reserves distribution as stocks
deplete (i.e. the countries with abundant reserves become more
important for global supply in the future)
3) reserves distribution only matters (i.e. supply risk depends on the
origins of reserves NOT where current production occurs)

V) POLICY EFFORTS
To mitigate supply risk either recycling efforts need to increase
or new substitutes will have to be found.
The following changes will suffice to make materials non-critical:

A1. PRODUCTION CONCENTRATION
S = 0.77
R = 0
S = 0.93
R = 0
*S – substitutability, higher S -> higher risk
*R – recycling, higher R -> lower risk

A2. SUBSTITUTES AND RECYCLING
Potash
S = 0.32
R = 0
HHI = 2300
Barytes
S = 0.98
R = 0
HHI = 2603
Natural Graphite
S = 0.72
R = 0
HHI = 7300
Cobalt
S = 0.71
R = 0.16
HHI = 4600

A3. POLITICAL STABILITY INDEX
The main index used for Political Stability is the Worldwide
Governance Indicators (WGI) calculated by WB in 2014.
The index consists of six dimensions of governance:
• Voice and Accountability
• Political Stability and Absence of Violence
• Government Effectiveness
• Regulatory Quality
• Rule of Law
• Control of Corruption

A4. POLITICAL STABILITY VS WGI

A6. POLITICAL RISK AND
CONCENTRATION IN OECD
• Average WGI among OECD countries – 2,7, among the rest
– 5.3.
Share of production
Mexico
Fluorspar 18%
Silver 21%
Greece
Perlite 19%
Turkey
Borate 45%
Feldspar 21%
Perlite 18%
0 1 2 3 4 5
WGI_final
FINLAND
SWEDEN
NEW ZEALAND
NORWAY
DENMARK
SWITZERLAND
NETHERLANDS
LUXEMBOURG
CANADA
AUSTRALIA
AUSTRIA
GERMANY
IRELAND
UNITED KINGDOM
BELGIUM
United States
JAPAN
CHILE
FRANCE
ESTONIA
PORTUGAL
SLOVENIA
CZECH REPUBLIC
SPAIN
POLAND
SLOVAKia
S. KOREA
HUNGARY
ISRAEL
ITALY
GREECE
TURKEY
MEXICO

A7. SUBSTITUTABILITY
VS RECYCLING

A8. SUBSTITUTABILITY
VS CONCENTRATION

A9. RECYCLING VS
CONCENTRATION

A11. ECONOMIC IMPORTANCE
USA VS OECD

JAPAN VS OECD

EU VS OECD

A14. STATISTICAL APPENDIX
Variable Mean
Std.
Dev. Min Max
Correlation matrix
Supply
Risk Subst. Recycling HHI HHI_wgi EI
Supply risk 1.11 1.04 0.1 4.61 1
Substitutability 0.69 0.18 0.32 0.98 0.27 1
Recycling 0.09 0.12 0 0.51 -0.16 0.25 1
HHI 3327 2344 629 9801 0.88 0.07 -0.14 1
HHI_wgi 1.73 1.51 0.22 5.99 0.95 0.09 -0.08 0.91 1
Economic
Importance 0.07 0.02 0.03 0.11 0.14 0.13 -0.04 0.14 0.14 1

A15. DATA ISSUES
• Economic importance index
• Sectorial composition (GVA of Megasectors)
• Data is currently available in GTAP breakdown
• Higher level of disaggregation is desirable for more accurate
results (ISIC up to 4 digits)
• Breakdown of end-uses of materials can differ by
countries and for OECD
• Data used currently is based on data in EU report (2014),
USGS (2014)
• Supply risk index
• Input data may differ for the OECD countries: breakdown
of end-uses, substitutability, recycling rates
• Alternative measures can be used: political risk (WGI vs
PRS)

A.16 REFERENCES
DERA Rohstoffinformationen, 2012, Energy Study 2012, Reserves,
Resources and Availability of Energy Resources, Germany.
Krausmann, 2009, Growth in global materials use, GDP and population
during the 20th century
EU, 2010, Critical Raw Materials for the EU, Report of the Ad-hoc
Working Group on defining critical raw materials, 30 July
EU, 2014, Report on Critical Raw Materials for the EU
NRC, National Research Council, 2008, Minerals, Critical Minerals, and
the U.S. Economy, National Research Council of the National Academies
UK, 2008, Material Security Board Ensuring Resource availability for the
UK economy
U.S. Geological Survey, 2014, Minerals Yearbook 2010
World Mining Congress, 2014 World Mining Data
World Bank, 2014, World Governance Indicators

121
Circular Economy:
A Computable
General Equilibrium
Approach
2 October 2014
Second ad-hoc technical workshop
on CIRCLE
Alexandre Godzinski
French Ministry of Sustainable Development

122
Model: why, how and what for
• Motivation: explore and evaluate different instruments related to material
efficiency and waste treatment in France
• Computable general equilibrium model which includes:
– Material flows (virgin ore extraction, material in final products, waste, scrap
metal)
– Material stocks (ore in the ground, productive capital stock, landfill stock)
• Stylized tool to assess policies related to material efficiency and waste
management, which are usually studied separately
• Model under construction! At the moment:
– World divided into two regions: France and the rest of the world
– Only one material: steel
• Output variables:
– Waste treatment (recycling rate, volume going to landfill…)
– Material efficiency (material productivity…)
– Usual economic outputs (GDP, consumption…)

123
Linear economy
Household
Investment
Generic good
Mines
Consumption
Primary material
Waste
treatment
service
Recycling Landfill
Waste treatement
Physical flows

124
Circular economy
Household
Investment
Generic good
Mines
Consumption
Recycling Landfill
Waste treatement
Waste
treatment
service
Secondary material
Physical flows

125
Model structure
Household
Investment
Generic good
Mines
Consumption
Primary
material
Secondary
material
Waste
treatment
service
Capital Labor
Recycling Landfill
Waste treatment

126
Application: reducing the volume of waste
going to landfill
We consider two polar strategies:
• Taxing materials (both primary and
secondary), so that final goods contain less
material.
• Taxing landfill, so that more waste is
recycled.

127
Tax on materials
20
18
16
14
12
10
8
6
4
2
0
0% 50% 100% 150% 200%
Tax rate
Volume of waste (million tons of steel)
Volume of waste recycled
Volume of waste going to landfill

128
Tax on landfill
20
18
16
14
12
10
8
6
4
2
0
0% 50% 100% 150% 200%
Tax rate
Volume of waste (million tons of steel)
Volume of waste recycled
Volume of waste going to landfill

129
Thank you for your attention
Comments welcome

Institute for Global
Environmental Strategies
CGE-MRIO analysis reflecting
resource production costs, recycling and
resource footprint
An input for the resource scarcity session
Satoshi Kojima, Ph.D.
Principal Researcher, Institute for Global Environmental Strategies (IGES)
Second Ad-hoc Technical Workshop on CIRCLE
OECD, Paris, 2-3 October 2014

Basic idea
Economic impacts of resource scarcity of non-critical resources
 Increasing resource production costs (low-hanging fruits first)
 Historical decline of EROI (Energy Return On Investment)
Estimate economic impacts of not only resource scarcity but also
“actions”
 CGE (computable general equilibrium) model has advantages in
assessing impacts of actions (policies)
 Resource footprint can measure resource use based on the
consumer responsibility principle ⇒ MRIO (multi-regional input
output) model serves for this purpose
Various policy options for sustainable resource use
 Economic instrument such as natural resource tax
 Recycling
 Investment for resource saving/resource efficiency improvement
Environmental Strategies 131

Empirical estimation of increasing mining costs
Mine cost database, World
Mine Cost Data Exchange Inc.
(Operation cost data of 66
major iron ore mines in the
world)
Estimated total cost curve for
iron ore mining (fitted by
cubic function)
Reference:
Murakami S., Adachi T. and Yano T.
(2012) An economic evaluation of
resource supply constraint and its
verification on material balance.
Presentation at SEEPS 2012.
132

CGE-MRIO modelling: Progress
Develop global MRIO (and social accounting matrix for CGE)
 Based on GTAP version 7
 Iron-steel sectors (iron ore mining, pig iron, blast furnace steel,
electric arc furnace steel) and steel scrap recycling sectors are
disaggregated using national IO tables, UN-Comtrade, etc.
Develop recursive dynamic CGE model
 Introduce sector-specific capital accumulation to reflect sector
specific investment
 Introduce substitutability between intermediate use of blast furnace
steel and electric arc furnace steel
Conduct test run of CGE-MRIO linkage
 Give policy shocks to CGE model and update MRIO based on the CGE
simulation results
Acknowledgement: This research is a part of the research
project funded by the Ministry of the Environment, Japan.

CGE-MRIO modelling: Test run results
134
Policy impact on iron ore use: Japanese natural resource tax on iron ore
use by pig iron producers (Source: Simulated results by the authors)
Note: I_M: Indonesia & Malaysia, EOG: Major exporters of oil & gas

Discussion for further research
Elaborate modelling of increasing resource production costs
 Reflect impacts of declining EROI
 Reflect per unit energy input for resource production may be
increasing (analogous to EROI)
 Reflect environmental costs (e.g. ecosystem destruction at mining
sites)
 Other channels?
Can we reflect physical limit of resource supply?
 In the short run (e.g. a time step of simulation), resource supply
capacity is effectively fixed ⇒ physical limit of resource supply
 In case of scrap recycling, scraps are also limited resources. Scrap
stock dynamics may set upper limit of available scrap for recycling.
 But setting upper limits for resource stock in CGE may cause
infeasibility problem …

Thank you for your attention!
kojima@iges.or.jp
http://www.iges.or.jp/

137
CIRCLE Worshop Outline – Day 2
Friday 3 October 2014 (Day 2)
9:00 – 10:30 Climate change
Speakers Rob Dellink (OECD)
Juan-Carlos Ciscar (IPTS)
Key questions  What are the main policy insights from the preliminary analysis?
 How can the analysis of the covered impacts be improved?
 How can the analysis be extended to other climate impacts?
 How to best evaluate the benefits of mitigation and adaptation policy action?
Background
material
“Consequences of climate change damages for economic growth – a dynamic quantitative
assessment”, OECD Economics Department Working Paper 1135.
11:00 – 12:45 Air pollution
Speakers Elisa Lanzi (OECD)
Mike Holland (EMRC)
Milan Ščasný (Charles University)
Key questions  What is the state-of-the-art knowledge on the consequences of air pollution for economic
growth?
 How can the health impacts from increased emissions of local air pollutants be projected for
major world regions?
 How can these impacts be monetised and linked to specific economic activities and what
additional work is required to do so?
Based on: “CIRCLE progress report; local air pollution”, ENV/EPOC(2014)19
12:45 – 13:00 Closing session
Speakers Shardul Agrawala
Key questions  What are the key synergies and trade-offs between the various themes that deserve priority
attention in the project?
 What are the research priorities and next steps for the project?
 What contributions by governments, experts and project partners can be further explored?

IMPACTS OF
CLIMATE CHANGE:
GROWTH
Rob Dellink

• 1st results published
– Economics Department
Working Paper
– Used in OECD@100 and
NAEC reports
• Continued support from
EPOC
– Request to further
improve analysis
– Request to prepare
report in time for COP21
139
Current status: climate change

Climate change impacts and damages
Sea level rise
• Coastal land losses and damages to capital
Health
• Changes in mortality & morbidity and demand for healthcare
Ecosystems
• Changes in productivity of production sectors
Crop yields
• Changes in agricultural productivity
Tourism flows
• Changes in productivity of tourism services
Energy demand
• Changes in the demand for energy from cooling and heating
Fisheries
• Changes in catchment
Not included
• Extreme weather events, water stress, catastrophic risks, …
140

Global GDP impacts (% change wrt no-damages baseline)
Likely uncertainty range
equilibrium climate sensitivity (1.5°C - 4.5°C)
Likely Wider uncertainty uncertainty range
range
equilibrium climate sensitivity (1.5°1°C C - 6°- 4.5°C)
C)
Central projection
141
Global assessment
0.0%
-0.5%
-1.0%
-1.5%
-2.0%
-2.5%
-3.0%
-3.5%
-4.0%
2010 2020 2030 2040 2050 2060
Source: Dellink et al (2014)

142
Stylised analysis post-2060
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
0%
-1%
-2%
-3%
Global damages as percentage of GDP
Likely uncertainty range (Business as Usual)
Likely uncertainty range (Committed by 2060)
Central projection (Business as Usual)
Central projection (Committed by 2060)
Central projection (highly nonlinear damages)
-4%
-5%
-6%
-7%
-8%
-9%
Likely uncertainty range (Business as Usual)
Likely uncertainty range (Committed by 2060)
Central projection (Business as Usual)
Central projection (Committed by 2060)
Central projection (highly nonlinear damages)

143
Regional results (central projection)
2%
1%
0%
-1%
-2%
-3%
-4%
-5%
-6%
OECD America OECD Europe OECD Pacific Rest of Europe
and Asia
Latin America Middle East &
North Africa
South & South-
East Asia
Sub-Saharan
Africa
World
Global GDP impact (% change wrt no-damages baseline, 2060)
Agriculture
Sea level rise
Tourism
Health
Ecosystems
Energy
Fisheries

Preliminary analysis of benefits of policy
action
• Assessment of benefits of policy action require
insight into stream of future avoided damages
– Not straightforward to assess with ENV-Linkages
– Lack of sectoral adaptation information is also an issue
• As first step, use the AD-RICE model which is
especially suited for this (as perfect foresight
model)
– AD-RICE is an augmented version of Nordhaus’ RICE
model, with explicit representation of adaptation
• Look at both adaptation and mitigation policies,
and their interactions
144

145
Preliminary results: adaptation policies
0%
-1%
-2%
-3%
-4%
-5%
-6%
-7%
-8%
-9%
-10%
% change wrt no-damage baseline
Likely uncertainty range - Optimal adaptation Central projection - Optimal adaptation
Central projection - Flow adaptation Central projection - No adaptation
Likely uncertainty range - Flow adaptation Central projection - Optimal adaptation
Likely uncertainty range - No adaptation Central projection - Optimal adaptation
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Preliminary results; not to be cited or quoted

146
Preliminary results: mitigation policies
0%
-1%
-2%
-3%
-4%
-5%
-6%
-7%
-8%
-9%
-10%
Likely uncertainty range -No mitigation Likely uncertainty range -Optimal mitigation
Central projection -No mitigation Central projection -Optimal mitigation
Weitzman damage function -No mitigation Weitzman damage function -Optimal mitigation
Likely uncertainty range -No mitigation Likely uncertainty range -Optimal mitigation
Central projection -No mitigation Central projection -Optimal mitigation
Weitzman damage function -No mitigation Weitzman damage function -Optimal mitigation
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

147
Preliminary results: discounting
0.0%
-0.5%
-1.0%
-1.5%
-2.0%
-2.5%
Likely uncertainty range -Nordhaus discounting Central projection -Nordhaus discounting
Central projection -UK Treasury discounting Central projection - Stern discounting
Likely uncertainty range UK - Stern Treasury discounting discounting Central projection -Nordhaus discounting
discounting
Central projection -UK Treasury discounting Central projection - Stern discounting
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

148
Preliminary results: interactions
0%
-1%
-2%
-3%
-4%
-5%
-6%
-7%
-8%
-9%
-10%
Optimal adaptation - No mitigation Optimal adaptation - Optimal mitigation
Flow adaptation - No mitigation Flow adaptation - Optimal mitigation
No adaptation - No mitigation No adaptation - Optimal mitigation
Optimal adaptation - No mitigation Optimal adaptation - Optimal mitigation
Flow adaptation - No mitigation Flow adaptation - Optimal mitigation
No adaptation - No mitigation No adaptation - Optimal mitigation
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

How to expand the list of impacts that
are covered?
• Extreme precipitation events
– Floods, hurricanes
• Extreme temperature events
– Heatwaves
• Water stress
– But impacts on agriculture already largely included
• Large-scale disruptions
– Shut-down of Gulf Stream, collapse of West-Antarctic
ice sheet
• Other discontinuities and tipping points
149

• Q4 2014 / Q1 2015
– Finalise expanded baseline
– Revise agricultural impacts
– Carry out stand-alone assessment of the literature on
some of the major missing impacts (incl. heatwaves)
– Finalise first stylised assessment of benefits of action
– Updated report available in time for COP21
• Rest of 2015
– Develop policy simulations in ENV-Linkages
– Carry out integrated policy analysis for climate change
and air pollution
– If possible extend the range of impacts covered in the
analysis
150
Timeline

THANK YOU!

IMPACTS OF
LOCAL AIR POLLUTION:
GROWTH
Elisa Lanzi

153
Impacts of air pollution
• Air pollution is one of the most serious
environmental health risks
– WHO (2014) estimates that in 2012 around 7
million people died as a result of air pollution
exposure
– OECD (2014) finds that the total economic costs of
deaths from ambient air pollution amount to 1.6
trillion USD in 2010 in OECD countries
• Impacts also to crop yields, biodiversity and
cultural heritage

154
The CIRCLE project approach
• Macroeconomic cost of the impacts of air pollution
– Include impacts of air pollution to the economy in the
ENV-Linkages model
• Labour productivity
• Increased health expenditures
• …
– Adjustments take place in the model to finally give the
final macroeconomic cost of air pollution
• Non-market costs
– Premature deaths
– Pain and suffering

Methodological steps Project partners
155
Methodology
1. PROJECTIONS OF AIR POLLUTANTS EMISSIONS
2. CONCENTRATIONS OF AIR POLLUTANTS
3. IMPACTS OF AIR POLLUTION ON HEALTH
4. ECONOMIC CONSEQUENCES OF HEALTH IMPACTS
5. MACROECONOMIC IMPACTS OF AIR POLLUTION
OECD, IIASA
EU JRC (Ispra)
EMRC
EMRC
OECD

156
1. Projections of air pollutants emissions
• Emission data from the sectoral GAINS model (IIASA)
– SO2, NOx, PM2.5, OC, BC, NH3
– Projections for Current Policy Scenario of IEA’s WEO 2012
• Link emissions to production activities in different key
sectors
– Combustion of fossil fuels in energy and industrial sectors
– Production of goods
• Sector and region specific emission coefficients
• Projections of coefficients calculated using the WEO
2012 to 2035 and then linear extrapolation to 2060

• Calculating concentrations requires
– Downscaling from macro regions to local level
– Data on regional emissions, climatic and geographical variables
(e.g. altitude, location of industrial areas, temperatures…)
• Calculations will be done by the EU JRC (Ispra)
– FAst Scenario Screening Tool (FASST), which describes relations
between precursor’s emissions and pollutant’s concentrations
– Output:
• Concentrations of PM2.5, including from primary (BC and OC) and
secondary (SO4 and NO3) emission sources
• SO2 and NOx
• Ozone
157
2. Concentrations of air pollutants

• Concentrations are used to calculate the
impacts on health
• Demographic variables also needed as input
– Population growth
– Ageing
– Fertility rates
• Impacts that would ideally be included are
– increased mortality (premature deaths)
– increased morbidity (number of sick days,
hospital admissions…)
158
3. Impacts of air pollution on health

• Once the health impacts are calculated, they need to be
evaluated
• Market impacts
– Additional health costs (from hospital admissions or healthcare)
– Changes in labour productivity
• Non-market impacts
– Cost of premature deaths
– Costs of pain and suffering
• The challenge
– Break down morbidity costs between market and non-market costs
159
4. Valuation of health impacts

160
5. Macroeconomic impacts of air pollution
• Health impacts will be modelled directly in the CGE
model, as much as possible
• Production function approach
– increased mortality: loss of labour supply
– increased morbidity: decreased labour productivity,
increased demand for healthcare
• Aspects that cannot be captured in CGE models
– Presented separately from the macroeconomic impacts
– Economic costs of premature deaths, costs of ‘pain and
suffering’
– Challenge: how to combine market and non-market
impacts?

• Policies can improve air quality and reduce the impacts on health
– Adoption of end-of-pipe technologies
– Shifting of economic activity away from polluting to less polluting sectors
– Improvements in production processes, e.g. energy efficiency
improvements, fuel switching
• Potential air pollution scenario: Maximum Technically Feasible
Reduction (MTFR) scenario, which reflects the implementation of the
best available end-of-pipe technologies to reduce air pollution
– Need data on the costs of implementation of the policies, i.e. the costs of
the adoption of new and more efficient technologies
• Interactions between air pollution and climate change mitigation
policies
161
Benefits of policy action

• Model Marginal Abatement Cost Curves
– Identify how policies affect technology choice and then specify the
position on the MACC
– The MACC reflects investments in abatement as a consequence of
policies such as
• mandating specific end-of-pipe techniques
• incentives to adopt improved technologies
• road pricing schemes
• air quality targets
• Consider other impacts
– Agricultural yields
– Biodiversity
162
Possible future developments

• Q4 2014
– Finalise the modelling of air pollutants in ENV-Linkages
– Calculate concentrations
– Finalise the methodology to calculate and evaluate impacts
• Q1 2015
– Calculate and evaluate impacts
• Q2 2015
– Quantitative assessment of the economic consequences of the health
impacts of air pollution
– Develop relevant policy scenarios
• Q3 2015
– Calculate benefits of policy action
• Q4 2015
– Finalise the work and draft a report, which should be ready in early 2016
• Q1 2016
– Finalise the report
163
Next steps and timeline

THANK YOU!
elisa.lanzi@oecd.org

Calculating indicators for health
impacts of air pollution for
ENV-Linkages
Mike Holland mike.holland@emrc.co.uk
September 2014
165

Tasks
• Calculate mortality and morbidity
indicators for SO2, NOx, PM2.5 emissions
• Quantify economic costs
– Health expenditure
– Labour productivity
– Non-market damage (pain, suffering,
premature mortality)
• Assess feasibility of extending quantitative
assessment to non-health pollution
impacts 166

Starting point for analysis
• Pollutant concentrations (PM2.5, others?)
• Previous studies
– Global burden of disease, USEPA, European
Commission, UN/ECE LRTAP Convention,
Chinese work
• Data on GDP, population, population
structure from OECD
• OECD recommendations on VSL
167

Same approach everywhere?
• Possible standard approach
– GBD for all, using cause specific mortality
functions
– 10% added for morbidity
• HRAPIE
– All cause mortality more reliable for Europe
(and USA)
– Detailed analysis of morbidity already
undertaken
168

Defining health endpoints
169
• Morbidity, Europe and USA, €2012

Quantifying outside Europe,
USA
• Quantification
at higher
concentrations?
• Incidence,
prevalence data?
• Valuation data?
• Treatment
options?
170
Concentration
Response

Air pollution and healthcare
• EU, French, US studies
• Completeness? CV morbidity
• High costs associated with mortality in US
and French studies
171

Valuation of healthcare costs
172

Air pollution and productivity
• Functions for work loss days
– Limited, aged research
– How complete?
– ‘Presenteeism’?
173

Summary
• Quantification at global scale is possible
• Key decisions
– Treatment of morbidity
– Use of common
– Interpretation of effects
174

Health Benefits of
Air Pollution
Milan Ščasný
Charles University in Prague
Second Ad-hoc Technical Workshop on CIRCLE
2-3 October 2014, OECD Paris

Contribution
Agenda: How can air pollution impacts be monetised and linked to specific
economic activities and what additional work is required to do so?
• Linking the economic model with AQ-benefit assessment:
Drivers of the pressures
• Identifying impacts:
Going from pressure to impacts
• Deriving benefits:
Moving from (health) impacts to monetary valuation
• Linking the modeling approaches on the top:
Economic assessment within a general equilibrium framework

From econ model to AQ-benefits
< Impact pathway approach >
POLLUTANT
& NOISE
EMISSIONS
MONETARY
VALUATION
TRANSPORT
& CHEMICAL
TRANSFORMATION
DIFFERENCES OF
PHYSICAL IMPATS
177

From econ model to AQ-benefits
Drivers
Output-linked
coeff
Fuel-linked
coeff
Fuel-linked
projections
(CIRCLE?)
Scale
The change in performance of the
whole economy
  
Composition The change in relative sizes of sector   
Fuel Intensity
The change in fuel consumption per
unit of value added
 
Fuel Mix
The change in fuel-mix used in
production
 
Emission
Intensity
The change in emission volume per unit
of fuel used (affected by end-of-pipe)

1
• MR EE IOTs (EXIOBASE, CREEA) is very rich and useful source on fuel-specific
country-specific emission coefficients, but it describes economy in the past (2007)

From pressures to impacts
CIRCLE:
• mortality, morbidity, pain attributable to airborne pollutants (SO2,
NOx,PM2.5,OC,BC,NH3)
• primarily health benefits, but effect on crop, biodiversity, cultural heritage later
Comments
• building materials soiled or corroded  the ExternE project series
• benefits can be valued only if reliable DRFs/ERFs/CRFs exist
 PMcoarse, NMVOC, heavy metals  ExternE (NEEDS, DROPS, HEIMTSA,…)
 (GHGs health effects included in DICE, FUND, PESETA, GLOBAL-IQ, …)

externalities
External costs from power sector in Czech Rep. (2005)
mil. €
% total
externalities
% classic
pollutants
mortality 956.75 32.4% 54.1%
chronic YOLL 947.43 32.1% 53.6%
acute YOLL 8.30 0.3% 0.5%
infant mortality 1.02 0.0% 0.1%
morbidity 484.89 16.4% 27.4%
chronic bronchitis 150.07 5.1% 8.5%
RAD 98.54 3.3% 5.6%
LRS 82.87 2.8% 4.7%
cough 3.02 0.1% 0.2%
HA 0.95 0.0% 0.1%
broncholidator 0.17 0.0% 0.0%
WLD 149.27 5.1% 8.4%
Work-loss-days
crops 16.07 0.5% 0.9%
materials 75.74 2.6% 4.3%
loss of biodiversity 184.32 6.2% 10.4%
North hemispheric 50.00 1.7% 2.8%
micro-pollutants 16.63 0.6%
climate change (21€/t) 1 171.32 39.6%
TOTAL 2 955.71 100.0%

Valuing benefits
< monetary valuation >
CIRCLE:
• Market and non-market value
• GBD-based?
Comments
• GPD measured via QALY or DALY does not conform to welfare economics 
• quantify welfare changes due to avoiding specific health outcome or risk
MEDCOST - Medical treatment costs
 medical costs paid by the health service (covered by insurance), and any other personal
out-of-pocket expenses
LOSSPROD - Indirect (opportunity) costs in terms of loss productivity
 work time loss, lower efficiency of performance, and the opportunity cost of leisure
DISUTILITY
 welfare loss due to inconvenience, suffer, pain, or premature death

Valuing benefits /2
< Are they any values? WTP for other health
outcomes? >
• benefits can be valued only if monetary values (willingness-to-pay) are available
 …reviews by Mike Holland & Anna Alberini
 respiratory illness  NEEDS (cough, hosp admission, etc.); HEIMTSA
(COPD, chronic bronchitis), ECHA-WTP (asthma)
 fertility  Value of a Statistical Pregnancy of approx. €30,000 in ECHA-WTP
study (Ščasný & Zvěřinová 2014)
 developmental toxicity
 WTP - €4,000 minor birth defects; €130,000 defects of internal organs,
metabolic and genetic disorder; €125,000 very low birth weight  ECHA-WTP
 €5-20,000 loss of earnings due to one point IQ  DROPS
 carcinogens
 VSL as well as VSCC for cancer, controlling for quality of life and pain impact
(Alberini and Ščasný, 2014)
 skin sensitisation and dose toxicity
 WTP for dermatitis and renal failure by Máca and Braun Kohlová (2014)

Valuing benefits /3
< methodological issues >
VSL vs. VOLY (Value of a Statistical Life vs. Value of a Statistcal Life Year)
– due to shorter expected lifespans of elderlies, the VOLY assigns a lower value 
VOLY called as "senior death discount“
– EPA‘s SAB rejected using the VOLY approach (2008), similarly OECD CBA by Pearce
et al. (2006) is recommending using VSL rather than VOLY
– Economic theory suggests to value changes in risk of dying  WTP for ‘a
micromort’  Value of a Statistical Life
– My suggestion:
use WTPs for mortality risk reduction and link it with Risk Rates
estimated in epidemiological studies
 If RR are transferred into Life Losts, use VSL
 If RR are transferred into YOLLs, use VOLY if it was based on WTP for
risk reductions (partly in Desaigues et al. (2007; 2011)
do not link VOLY on QALYs/DALYs, or make it with very caution

Valuing benefits /4
< methodological & normative issues >
• Premiums in a Value of a Statistical Case
 10% ‘malus’ for morbidity associated with mortality risk
 50% bonus for infants
 no strong evidence for such premiums (Alberini and Ščasný 2012 for
‘child’ premium; Alberini and Ščasný 2014 for QoL in cancer risks)
 but, benefits for premature death should include both DISUTILITY
(hence VSL) and Cost-Of-Illness (for instance, MEDCOST of cancer
treatment is €6,000 and LOSSPROD are €40,000 in Czech Rep; Ščasný &
Máca 2008)

Linking the models on the top
MEDCOST and LOSSPROD
• MEDCOST - Medical treatment costs
 medical costs paid by the health service (covered by insurance), and any other
personal out-of-pocket expenses
 both public health service (sector in SAM) and personal out-of-pocket
expenses (final use in SAM)
 Premature death may reduce governmental expenditures on pensions and
health care (final use in SAM)
 public health system may affect the length of sickness leave  LOSSPROD
• LOSSPROD - Indirect (opportunity) costs in terms of loss productivity
 work time loss, lower efficiency of performance, and the opportunity cost of leisure
 average wage, GDP per capita / employee – D(L)
 costs of absenteeism (CBI 1999), direct and indirect – P(L), MPL
 friction costs based on a concept of replacement (Koopmanschap et al. 1995)

< normative issue: social planner
perspective >
One value across countries and regions ?
• WTP for pain, inconveniences, or premature death
consensus
• MEDCOST
 so far one ‘average’ value used, maybe for simplicity
• LOSSPROD
 one value for whole EU, as far as I know, but the value is a
population weighted average, at least for the EU

WTPs in GE framework /2
• One ‘EU-average’ WTP values used in EcoSenseWeb tool (ESW)  using
different values matter
1600
1400
1200
1000
800
600
400
200
0
ESWindex CZ
ESW
ESWindex
ESWwealth
ESWwealth CZ
LITRVindex
LITRVindex CZ
outside of CZ
within the CZ
LITRVwealth
LITRVwealth CZ
mil. €
PPP-adjusted
GDP-adjusted
Based on our literature
review
EU-wide
values
Table: Health-related externalities due to pollution from power sector in the Czech Republic if different
monetary values are used. Source: Máca and Ščasný 2009 (NEEDS project)
• one average value of MEDCOST and LOSSPROD is not consistent with SAM
• using one WTP value of DISUTILITY (pain, mortality, fertility) may be fine because
there is no its counterpart in SAM, and no component in the CGE utility function

• Impacts, and hence benefits, are NOT distributed among emitting-country residents only
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
ESW LITRVindex LITRVwealth ESWindex ESWwealth
% of total externalities
Table: Health-related externalities due to pollution from power sector in the Czech Republic disaggregated according
to the region where the impact would occur, % of total . Source: Máca and Ščasný 2009 (NEEDS project)
• To ensure consistency with SAM, physical impacts (health outcomes) should be derived for
country/regions, as used in CGE regional structure
• Otherwise, one would need to assume that damage attributable to emissions released by
region x are affecting residents from region x only
rest
TR+YU+HR
UA+RUS
HU+RO+SVK
POL
CZ
NL+UK+BE
ITA+FRA+AT
DE

• Keep WTP value over time constant (when income may increase)?
푊푇푃푡 = 푊푇푃 ∙ (1 + 푔푡 ∙ 휀푡)
where g is percentage change in income per capita in period t (i.e. endogenous in CGE), ε is
elasticity of WTP wrt income (invariant in time?)
• present value of WTPt to be consistent with CGE  utility discounting (PRTP)
vs. consumption discounting (PRTP + g*εy), where εy is the elasticity of the
marginal utility of consumption
• consistency between variations (coming from CLI in CGE) and surpluses
(CSU/ESU coming form stated preference valuation studies)
• WTP values reported in FINAL prices, however, expenditures in SAM are
recorded in BASIC prices (i.e. excluding taxes) – to be consistent with
national accounts, WTP values would have to be ‘cleaned’ (taxes put out)

Thank you for your attention.
Milan Ščasný
Univerzita Karlova v Praze
milan.scasny@czp.cuni.cz

Presentations of the OECD 2nd CIRCLE technical workshop (2-3 Oct. 2014)

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