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For ETSAP meeting
Using Genuine Savings for climate
policy evaluation with an integrated
assessement model
Koji Tokimatsu, Tokyo Institute of Technology &
National Institute of Advanced Instrial Science and Technology
Louis Dupuy, APESA & University of St Andrews
Nick Hanley, University of St Andrews
Presentation structure
1. What is “Genuine Savings”
2. Model
ïź Criticism on climate‐economy IAM
ïź Our innovation
ïź Comparisons with other approaches
3. Example of Results
4. Summary
2
Details are in DP from St. Andrews3
same as GS
The World Bank 2011
"The changing wealth of nations: measuring sustainable development in the new millennium"
http://siteresources.worldbank.org/ENVIRONMENT/Resources/ChangingWealthNations.pdf.
4
Difinition of GS/IW
‱ The theory of Genuine Savings (or Adjusted Net Savings) :
– Sustainability as non declining well‐being over time
– Asset and consumption mapping through an economic program
– SD indicator since rate of change in wealth = rate of change in 
instantaneous well‐being
– Definition of Comprehensive/Inclusive Wealth
– GS as the rate of change in total wealth at shadow prices
5LD, KT, NH – Using GS for Climate Policy Evaluation
, , , , , ,
	
5
The Stiglitz Commission Report makes 12 
recommendations on moving from production 
to well‐being. These range from including 
measures of income, consumption, and wealth 
– both market and non‐market, as well as their 
overall distribution – to objective and 
subjective measures of well‐being, such as 
health, education, personal activities, and 
environmental conditions. 
Beyond GDP: Proposals for alternative 
measurement tools
Source: http://www3.weforum.org/docs/WEF_Forum_IncGrwth_2017.pdf
The European Commission, which has worked on the issue for a 
decade, has outlined a roadmap for new indicators that includes up‐
to‐date measures on environmental protection and quality of life; 
distribution between income, health, education, and environmental 
quality; overall sustainability; and social issues.
6
Stiglitz Report 20097
1. State of the art IAM approach
(1) highly aggregated, algebraic damage function
‱ the modeller's choice of a particular algebraic formula
‱ the common assumption of zero damage at the origin
‱ the modeller's estimate of damages at a benchmark change
      2
2111 TTTD  
Pindyck 2013 criticized that 
‱ completely made up, with no theoretical or empirical foundation.
‱ choice of values for these parameters is essentially guess work.
‱ Nordhaus “global mean losses could be 1‐5 percent of GDP for 4℃ of 
warming”
From its own survey of several IAMs. it’s a bit circular.
IPCC AR5  (WG3, 3.9.2 Aggregate climate damages)
‱ A concern may be whether the curvature 
 is adequate. 
‱ The aggregated damage is 
 heroic extrapolations to 
 global scale 
from a sparse set of studies 
 done at particular geographic locations.
8
      2
2111 TTTD  
Our strategy – interlinking our LCIA model
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N: population number
σ: income elasticity
ep end points (human health, resources, biodiversity, photosynthetic NPP)
sbsglobal warming, ozone layer depletion, acid rain, local air pollution,
mining and disposal of mineral resources, land use and its change
marginal willingness 
to pay
Dose‐Response 
relations
Inventory 
release
Environmental 
external cost
‱ face to face,
internet
‱ G20+10 Asian
‱ over 7,800ss, 100
(min) to 600 (max)
9
Japanese version of lifecycle impact assessment modeling (LIME)
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Impact assessment model (LIME3)
Population, GDP 
(driver of demands)
Resource demands 
for energy, minerals, 
biomass (woods 
and foods)
Energy systems 
supply model
GHG emissions
→ temperature rise, 
Sea Level Rise
GHGs, SOx, NOx 
emissions→acid 
rain, air pollution
Resource extraction
Waste disposal
Land use
Land‐use change
external 
environmental cost
Human health
Resource production
Biodiversity
Photosynthetic NPP
Mineral resource 
supply model
Bio‐resource supply 
Land‐use model
Demands to inventories Inventories to external cost
Simplified climate 
model
Supply costs of 
the resources
internal cost  (FC,NFC,LC) external cost  (EXT)
Driver to 
demands
Macro‐economy 
model
H
Y
damage 
assessment
weighting
From inventories release to damages in our model12
input data from other
models to the impact
assessment model
Model name
Contents of the impact assessment model
Impact
category endpoints
global mean
temperature rise
(endogenous)
Simplified
climate model
Global
warming
Human
health
Heart disease, diarrhea,
malnutrition, flood, malaria
resources
Crop yield (rice, corn,
wheat)
Sea level rise (flooded
surface)
Energy consumption
(cooling, warming for air
conditioning)
biodiversity
Ozone Depletion
Substances (14 kinds)
(exogenous)
Simplified
climate model
Ozone
layer
depletion
Human health, resources, net
photosynthetic primary productivity
(NPP)
SOX, NOx
(endogenous) Energy model
Acid rain resources
Local air
pollution Human health, resources, NPP
Land use
(endogenous)
Bio resource and
land use model Land use NPP
Land-use change
(endogenous)
Bio resource and
land use model
Land use
change NPP, biodiversity
Copper, lead, zinc,
bauxite, iron ore,
limestone, coal
(endogenous)
Mineral resource
model
Resource
extraction NPP, biodiversity
Mineral resource waste,
scrap of concrete
(endogenous)
Mineral resource
model waste NPP, biodiversity
Disposal
Recovery
Recycling
refinery
conversion
Extraction
Harvesting
Final
demand
Final
products
export & import via global market and regional trade (balanced globally)
Transport
Cost of
extraction,
land use,
harvesting
+
Cost of
transport +
Cost of
refinery,
conversion
+
Cost of
producing
final products
Cost of
disposal,
recycling
+ÎŁ
rg,yr
minimizing discounted sum of cost from 2010 
 2150
‱ coal, oil, gas, uranium
‱ iron ore, bauxite, copper, 
lead, zinc, limestone
‱ logs, wood pulp, timber, 
papers
‱ pork, chicken, mutton, 
beef, rice, wheat, corn
‱ refinery, hydrogen, FT‐synfuel, 
methanol, ethanol, BDF, power, heat
‱ machinery steel, construction steel, 
non‐ferrous metals, cement, concrete
‱ woods (pulp, paper, boards), foods 
(chicken, pork, beef, mutton)
‱ power, heat, transport
‱ vehicle, buildings, 
infrastructure, electricity 
and machinery
‱ fuel log, paper, boards, 
grains, chicken, port, beef, 
mutton
‱ coal ash, plutonium
‱ granulated slag, waste 
concrete, scraps
‱ biomass residue (crop residue, 
garbage, excrement, animal 
waste, logging residue, used 
paper, lumbering residue, 
black liquor
econ (util & 
prod. func)
Energy (or
mineral)
model (+
climate)
3 resource 
models 
(+climate)
3 resources 
+ climate 
+ LCA model 
(LIME3)
1 or 3 
models
5 models 
= Full ‐ econ
Full models
3 resources 
+ climate 
+ LCA model 
(LIME3)
What models can do for sustainability/SD issues14
targets
‱ resource needs
‱ climate change mitigation (energy conversion tech.)
‱ ore degradation (scarce base metal e.g., copper)
SD indicators
‱ Factor-4 (resource productivity or decoupling)
‱ Factor-10 (fairness in per capita material consumption)
targets
‱ cost-benefit; internalizing the externalities (e.g.CC&M)
‱ alternative shadow price of carbon (or SCC)
SD indicators
‱ Genuine Savings, Inclusive Wealth = non declining
wealth (consumption, utility) in capital based approach
targets
‱ external environmental impacts and their costs
SD indicators
‱ Eco-Efficiency = GDP/Externality
‱ Human Appropriated Net Primary Productivity (HANPP)
= carrying capacity
Model type
climate‐
economy IAM 
(Integrated Assessment Model)
bottom‐up 
technology 
type
Couple several systems 
together
Lifecycle
impact 
assessment 
(LCIA)
Ours
Representative
model name
DICE/RICE, 
PAGE, FUND
MARKAL,
MESSAGE
Extern E, LIME
our original, 
unique
Model 
framework
Welfare
maximization
Cost 
minimization
Dose‐
Response, 
economic 
valuation
Welfare
maximization, 
interlinked 
bottom‐up 
technology and 
LCIA
Damage
assessment
aggregated, 
algebraic
damage 
function
Most exclude 
damage 
functions
sector base 
impact 
models, 
choice 
experiments
LCIA
Feedback to 
economy
Yes No No Yes
Natural 
resources
None Various Various various
【results】 GS and breakdowns in the balance growth16
Climate Policy scenario analysis
-2
-1
0
1
2
3
2010 2030 2050 2070 2090
GSnt[%/yr]
GSnt BAU
GSnt Eeff
GSnt CO2
GSnt ZERO
17
Conclusion
‱ We claim Genuine Savings are an effective indicator of the 
overall impact of policy options under climate change
‱ The forward looking nature of GS makes it impossible to 
produce a match for the theoretical concept

‱ 
But even our approximate method based on current 
mechanisms gives consistent results
‱ Using GS in IAM is a useful complement to using GS for 
the diagnosis of past and current performance
18LD, KT, NH – Using GS for Climate Policy Evaluation
18

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