A lo largo de estas jornadas, expertos nacionales e internacionales en el tema analizan la situación actual, tendencias futuras y principales retos que plantean los esquemas de reducción de emisiones y los mercados de carbono como herramientas en la lucha contra el calentamiento global, especialmente después de la cumbre de Copenhague. Antontio Soria, Jefe de la Unidad de Economía, Cambio Climático y Transporte, de IPTS (Institute for Prospective Technological Studies), participa con la ponencia "Análisis económico de algunos impactos del cambio climático en Europa: un enfoque sectorial".

1. Economic Analysis of Climate Change Impacts in
Europe: a Sectoral Approach
Antonio Soria, Juan Carlos Ciscar (JRC, European Commission)
jornadas eoi ‘carbon markets and emission reduction’
3 February 2010, Madrid

2. The IPTS
The Institute for Prospective Technological Studies (IPTS), based in
Sevilla, is one of the 7 scientific institutes of the European
Commission's Joint Research Centre (JRC)
Mission
to provide customer-driven support to the EU policy-making process
by researching science-based responses to policy challenges that
have both a socio-economic and a scientific or technological
dimension

3. Question of Interest:
What are the economic consequences of
climate change in Europe?
- overall order of magnitude
- distribution (space, time, sector)
<Mitigation and Adaptation policies>
White Paper on Adaptation (April 2009)
Literature: few references, mainly based on expert
judgement (G1)

4. What is known: aggregate impacts
TAR IPCC (2001) Stern report (2007)
Source: IPCC 4AR (2007), vol. II, Ch. 20

5. What is known: social cost of carbon
(marginal damage)
Tol (2005) review of literature
• Mean $97/tC
• Standard deviation $203/tC
Key, and controversial, assumptions
• Discount rate
• Equity weighting

6. What is unknown
• Non-market effects
(e.g. biodiversity, ecosystems)
• Extreme weather risks
• Socially contingent effects
• Long-term catastrophic risks

7. Outline
1. Overview of the PESETA project
2. Methodology: the economic CGE model
3. Sectoral results
4. Overall economic impacts
5. Conclusions

8. About PESETA
PESETA stands for: Projection of Economic impacts of
climate change in Sectors of the European union based
on boTtom-up Analyses
Main purpose: Quantitative, multi-sectoral assessment of the
monetary estimates of impacts of climate change in
Europe
JRC funded project
To support policymakers
Largely based on past DG Research-funded projects
(PRUDENCE, DINAS-Coast, cCASHh, NewExt,…)

9. Project partners and scope
Climate scenarios: DMI, CRU
Six sectoral assessments:
Agriculture: U. Politécnica de Madrid
Human health: AEA Technology
River basin flooding: JRC/IES
Coastal systems: FEEM/Southampton U.
Tourism: U. Maastricht-ICIS
Coordination and integration into CGE model: JRC/IPTS

10. Integrated economic impact assessment
Starting point: physical impact estimates
Some sectors provide with direct effects
estimates (e.g. river floods)
Overall effects (direct + indirect) assessed with a
computable general equilibrium model of
Europe

11. Socioeconomic scenario: GDP, population assumptions
Climate model Stage 1:
Modeling
future
climate
Climate data
(T, P, SLR)
Coastal River
Agriculture Tourism
Systems Flooding
model model
model model
Stage 2:
Modeling
physical
impacts
Physical Physical Physical Physical
impacts impacts impacts impacts
agriculture coasts floods tourism

12. impacts
Physical Physical Physical Physical
impacts impacts impacts impacts
agriculture coasts floods tourism
Valuation Valuation Valuation Valuation
agriculture coasts floods tourism
impacts impacts impacts impacts
Stage 3:
Modeling
General Equilibrium model economic
impacts
Economic
impacts

13. Grouping
of countries

14. Climate Scenarios
Data needs: 50 km resolution; daily and monthly
Selection of scenarios
2011-2040 period: A2 IPCC SRES scenario
data from the Rossby Center
2071-2100 period: data from PRUDENCE
A2, B2 IPCC SRES scenarios
2 regional climate models, RCMs (HIRHAM, RCA)
2 global circulation models, GCMs (HadCM3, ECHAM4)

15. Four 2080s Scenarios
Scenarios
2.5°C 3.9°C 4.1°C 5.4°C
World population in 2100 (1012) 10.4 15.1 10.4 15.1
12
World GDP in 2100 (10 , 1990US$) 235 243 235 243
CO2 Concentration (ppm) 561 709 561 709
∆ Temperature (ºC)*
World 2.4 3.1 2.3 3.1
EU‡ 2.5 3.9 4.3 5.4
Northern Europe 2.9 4.1 3.6 4.7
British Isles 1.6 2.5 3.2 3.9
Central Europe North 2.3 3.7 4.0 5.5
Central Europe South 2.4 3.9 4.4 6.0
Southern Europe 2.6 4.1 4.3 5.6
∆ Precipitation (%)*
EU‡ 1 -2 2 -6
Northern Europe 10 10 19 24
British Isles -5 -2 10 5
Central Europe North 3 1 6 -1
Central Europe South 2 -2 -4 -16
Southern Europe -7 -15 -13 -28
Sea Level Rise (high climate sensitivity) (cm) 49 56 51 59
*Increase in the period 2071–2100 compared to 1961–1990. ‡European regions: Southern Europe (Portugal, Spain,
Italy, Greece, and Bulgaria), Central Europe South (France, Austria, Czech Republic, Slovakia, Hungary, Romania, and
Slovenia), Central Europe North (Belgium, The Netherlands, Germany, and Poland), British Isles (Ireland and UK), and
Northern Europe (Sweden, Finland, Estonia, Latvia, and Lithuania).

16. Temperature
3.9°C (A2 Hadley) 5.4°C (A2 Echam)

17. Precipitation
3.9°C (A2 Hadley) 5.4°C (A2 Echam)

18. Methodologies for Physical Impacts Assessment
Detailed process modelling
Agriculture, DSSAT crop model
River basin flooding, LISFLOOD hydrological model
Coastal systems, DIVA model
Reduced-form exposure-response functions
Tourism
Human Health

19. Economic impact assessment
Starting point: physical impact estimates
Some sectors provide with economic direct effects
estimates (e.g. river floods)
Overall effects (direct + indirect) assessed with a
computable general equilibrium model of Europe:
GEM-E3 model

20. 2. The general equilibrium economic model
The GEM-E3 Model:
General Equilibrium Model for
Energy-Economics-Environment
interactions

21. General equilibrium
• Neoclassical framework
• Each agent pursues its own interest
• Decentralised information (preferences of
consumers and technology of firms)
• Simultaneous optimal behaviour
• Interaction of all markets
• Interaction of all agents (consumers, firms,
government, rest of the world)

23. Advantages of CGE modelling
• Consistency
• Theory (microeconomics foundations, within a consistent
macroeconomic framework)
• Data (Input-output, National Accounts, SAM)
• Structural model (versus reduced-form models): explain
behaviour of agents in markets, taking into account
institutions
• Transparency
• Systematic analysis; not mechanical
• Flexibility
• Can address a broad range of policy issues

24. Criticisms / disadvantages of CGE modelling
• Weak empirical validation (calibration versus
econometric estimation)
• The critical role of functional forms
• Simplification of exogenous elements of the model
• Data requirements
• Heavy computational load

25. The GEM-E3 model: European model version
Computable General Equilibrium model
Representing multiple production sectors and countries
Integrating energy and environment in the economy
GEM-E3: Standard Version
24 countries, 18 sectors (Eurostat)
Perfect competition for all commodity markets
Environmental module fully incorporated (All GHGs
included)

26. The GEM-E3 model: Production
Production (output)
• Perfect
competition Level 1
Reserves Labour
• Nested CES Capital Energy
production Materials bundle
function Agriculture
• Fully flexible Ferrous, ore, metals Electricity
Level 2
coefficients chemicals
Other en. intensive
• EU Electrical goods
Coal Labour
econometric Transport equip.
Oil Fuels Materails
Fuels bundle
evidence on Other equipment
Gas
elasticities Consumer goods Labour
Level 3
Building/Constr.
Telecommunication
Credit & insurance Materials
Credit & insurance
Market services
Non-market services
Level 4

27. The GEM-E3 model: Consumption Total Income
Disposable
income
Leisure Savings
Intertemporal maximization of
consumer’s utility Labour Supply
Investment in Monetary
involving consumption, dwellings Assets
savings, leisure Consumption
labour supply also derived
from utility maximization
Durable goods Non-durable goods and
steady state solution used services
LES with durable and non-
durable goods • Cars • Food
• Heating Systems • Clothing
• Electric Appliance • Housing
• Housing furniture and
operation
• Medical care and health
expenses
• Purchased transport
• Communication
• recreation, entrertainment etc.
Consumption of non-durables • Other services
linked to the use of durables • Fuels and power
O ti ft t

28. 3. Sectoral results

29. Agriculture

30. Modelling of physical impacts and link
to general equilibrium model
Site-evidence on average yield change across Europe,
DSSAT model
Yield changes (t/Ha)
Interpreted as TFP change
Y = TFP CES(K, LEM)

31. Agriculture
Crop yield
changes
(t/Ha),
production
losses and
gains

32. Agriculture: crop yield changes (%)
compared to 1961-1990
B2 HadAM3h A2 HadAM3h B2 ECHAM4 A2 ECHAM4
2025
2.5°C 3.9°C 4.1°C 5.4°C
Northern Europe 37 39 36 52 62
British Isles -9 -11 15 19 20
Central Europe North -1 -3 2 -8 16
Central Europe South 5 5 3 -3 7
Southern Europe 0 -12 -4 -27 15
EU 3 -2 3 -10 17

33. Coastal Systems

34. Coastal systems: the method
DIVA model
Impact categories: sea floods, migration, other
Integration into the CGE model:
Interpretation of sea flood cost as capital loss
Interpretation of migration cost as additional obliged
consumption (welfare loss)

35. Coastal
systems
- No
adaptation
- With
adaptation

36. Coastal Systems
people flooded (1000s/year) in main scenarios with
high climate sensitivity, without adaptation
B2 HadAM3h A2 HadAM3h B2 ECHAM4 A2 ECHAM4 A2 ECHAM4
2.5°C 3.9°C 4.1°C 5.4°C high SLR
Northern Europe 20 40 20 56 272
British Isles 70 136 86 207 1,279
Central Europe North 345 450 347 459 2,398
Central Europe South 82 144 85 158 512
Southern Europe 258 456 313 474 1,091
EU 775 1,225 851 1,353 5,552

37. River Floods

38. River Floods: the methodology
LISFLOOD model; integration of damages for various
return periods (from several ‘representative basins’)
Economic valuation: projection of change in 100-year flood
damage for the scenario (relative to control)
Integration into the GEM-E3 model:
Damage to residential buildings (additional obliged
consumption)
Damage to productive sectors (industry, services,…):
Capital loss
Production loss

39. River Floods
Change in
Economic
damage
(note red
means a
decrease)

40. River floods
expected economic damage (million €/year)
B2 HadAM3h A2 HadAM3h B2 ECHAM4 A2 ECHAM4 simulated
2.5°C 3.9°C 4.1°C 5.4°C 1961-1990
Northern Europe -325 20 -100 -95 578
British Isles 755 2,854 2,778 4,966 806
Central Europe North 1,497 2,201 3,006 5,327 1,555
Central Europe South 3,495 4,272 2,876 4,928 2,238
Southern Europe 2,306 2,122 291 -95 1,224
EU 7,728 11,469 8,852 15,032 6,402

41. Human health

42. Human Health
average annual heat-related (left) and cold-related (right)
death rates (per 100,000 population) 3.9°C scenario
Note: using climate-dependent health functions (no acclimatisation)

43. Tourism

44. Tourism
TCI scores in summer
5.4°C
control
Ideal
Excellent
Very good
Good
Acceptable
Marginal
Unfavourable
4.1°C

45. Tourism
Change in expenditure receipts (million €)
B2 HadAM3h A2 HadAM3h B2 ECHAM4 A2 ECHAM4
2.5ºC 3.9ºC 4.1ºC 5.4ºC
Norhern Europe 443 642 1,888 2,411
British Isles 680 932 3,587 4,546
Central Europe North 634 920 3,291 4,152
Central Europe South 925 1,763 7,673 9,556
Southern Europe -824 -995 -3,080 -5,398
EU 1,858 3,262 13,360 15,268

46. 4. Overall economic impact
• Effects of 2080s climate
• On European economy as of today
• Assuming there is no public adaptation, so that
priorities for adaptation within the EU can be
explored

47. Annual damage
in terms of GDP changes (million €)
10000
0
-10000
-20000
-30000
-40000
2.5°C
-50000
3.9°C
4.1°C
5.4°C
-60000
5.4°C, 88 cm SLR
-70000
Southern Central Europe Central Europe British Isles Northern EU
Europe South North Europe

48. Annual damage
1.0
in terms of Welfare changes (%)
0.5
0.0
-0.5
-1.0
2.5°C
3.9°C
4.1°C
-1.5
5.4°C
5.4°C, 88 cm SLR
-2.0
Southern Central Europe Central Europe British Isles Northern EU
Europe South North Europe

49. Sectoral decomposition
1.0%
of welfare changes (%)
Tourism
River floods
Coastal systems
0.5%
Agriculture
0.0%
-0.5%
-1.0%
-1.5%
-2.0%
2.5oC
3.9oC
5.4oC
5.4ioC
2.5oC
3.9oC
5.4oC
5.4ioC
2.5oC
3.9oC
5.4oC
5.4ioC
2.5oC
3.9oC
5.4oC
5.4ioC
2.5oC
3.9oC
5.4oC
5.4ioC
2.5oC
3.9oC
5.4oC
5.4ioC
Southern Europe Central Europe South Central Europe North British Isles Northern Europe EU

50. 5. Conclusions
• Integration of various disciplines, consistency
requirements
• Further research is needed, concerning:
• Costs and benefits of adaptation
• Cross-sectoral consistency
• Land use modelling
• Monte Carlo analysis

51. http://peseta.jrc.ec.europa.eu/

52. Muchas gracias !