F. Bosselo

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Explore the Potential of
Economic Models to Assess
Climate Change Impacts
Francesco Bosello and Paulo A.L.D. Nunes
Road Map
 Selection of a modelling framework, anchor of the
economic analysis and valuation exercise
Goal is to explore the use of the market price mechanism, rooted in
the demand and supply forces – the so called invisible hand (Adam
Smith, “The Wealth of the Nations, 1776)
 Proposed framework  Computable General Equilibrium
CGE modeling is used to describe and evaluate in welfare terms
alternative allocations in the input and output markets. Recently
assessment of “environmental facts” (e.g. climate change impacts
via induced changes in demand and supply)
Potential extension to evaluate changes in natural
resources qual./qt. and ecosystem services
The aim of the exercise
 assess and value the “environmental facts (impacts)” in
terms of GDP changes, since the CGE analysis is anchored
at a macro economic perspective, for the economies under
consideration.
 consider both direct and indirect (cost) effects – since
economic systems “adapt” in response to any “shock” under
consideration (substitution mechanisms)
 highlight transmission channels within and between
domestic and international “markets”, across all the economic
sectors under consideration, since all the markets are
“linked”.
Sketching a CGE
Consumers
(households, government)
Maximise welfare
from consumption
demand
supply
Income
Demand and supply
functions “mimic”
observed economic
systems: parameters
Output markets
are calibrated on “real”
Goods and
data
services
Input markets
K, L, Land, NR
Income
demand
Producers
(firms, government)
supply
Constrained
by income
Constrained
by technology
Minimise cost
of production
CGE with climate change
Consumers
(households, government)
Maximise welfare
from consumption
demand
supply
Goods and
services
Income
Constrained
by income
Climate change
and other environmental
pressures
Constrained
by technology
K, L, Land, NR
Income
demand
Producers
(firms, government)
supply
Minimise cost
of production
An illustration: sea level rise due to climate
change
Global Circulation Model
(Reduced form K. Hasselmann model
dvlp. Max Plank Institute
Hamburg, G. Hoos, 2002)
Environmental
Impact Model
(Tol, 2003)
• T = + 0.93 °C. in 2050
• SLR= + 25 cm. in 2050
• Data set 1: Sq. Km. of land lost due to erosion, if
there is no protection. Country detail.
• Data set 2: The costs of full protection. Country detail.
• Basis is the 1993 Global Vulnerability Analysis
by Delft Hydraulics and Nicholls and Leatherman,1995.
• The former provides estimates for all countries,
the latter additional information for some countries
interpolated for all.
The economic model
GTAP-EF
(Extended Version of GTAP-E Burniaux and Truong 2002)
8 Regions:
17 Economic Sectors:
USA:
EU:
EEFSU:
Rice
Wheat
Cereal Crops
Vegetable Fruits
Animals
Forestry
Fishing
Coal
Oil
Gas
Oil Products
Electricity
Water
Energy Intensive industries
Other industries
Market Services
Non-Market Services
JPN:
RoA1:
Eex:
CHIND:
RoW:
United States
European Union
Eastern Europe and Former
Soviet Union
Japan
Oth. Annex 1 countries
Net Energy Exporters
China and India
Rest of the World
(Further extension possible to 66
countries and 57 sectors)
Calibrated in 1997
The baseline
Starting point: equilibrium calibrated in 1997.
Re-calibration process in order to get a future reference
case “without climate change”.
This refers to obtaining a picture of the future world economy. In
practice, long-run estimates of primary inputs (land, labour, capital
and natural resources) stocks and productivity used to:
Shock the model 1997 calibration equilibrium to obtain new
equilibrium that will emerge before sea level rise effects are
considered.
The data
•
Population: World Bank.
•
Labour stock: G-Cubed model Version48E (McKibbin,
2001).
•
Labour productivity: G-Cubed model Version48E
(McKibbin, 2001).
•
Land productivity: IMAGE 2.2, B1 Scenario (RIVM, 2001).
•
Natural resources stock: endogenised s.t. Pnr = PIGDP
Sea Level Rise: Model Operationalization
No protection: Land is “simply” lost, negative “supply-side”
shock on the endowment LAND.
Total protection: No LAND is lost, but defensive investment
has to be undertaken  Imposing “new” investment behavior.
Coastal protection requires additional regional investment.
Regional households need to save more  In each region
regional savings increase uniformly to meet the
increased investment demand.
Private consumption is crowded out  share of income
devoted to consumption decreases
No protection: selected results
Investme
CO2
Land lost
GDP
Value of
nt (%
Emissions
(% change
(% change
land lost
(% change change
w.r.t.
w.r.t.
w.r.t.
w.r.t.
baseline) % of GDP baseline)
baseline) baseline)
USA
EU
EEFSU
JPN
RoA1
EEx
CHIND
RoW
-0.055
-0.032
-0.018
-0.153
-0.006
-0.184
-0.083
-0.151
Inputs
0.0002
0.001
0.01
0.0001
0.003
0.101
0.003
0.06
-0.002
-0.001
-0.002
-0.001
0
-0.021
-0.030
-0.017
0.01
0.012
0.005
0.035
0.015
-0.008
-0.024
-0.012
0.008
0.008
-0.013
0.031
0.022
-0.066
-0.172
-0.043
Price of primary inputs (%
change w.r.t. baseline)
Land
Labor
Capital
0.534
0.514
0.532
1.019
0.607
0.804
0.467
0.802
-0.051
-0.051
-0.059
-0.002
-0.026
-0.123
-0.196
-0.108
-0.051
-0.048
-0.061
-0.001
-0.025
-0.127
-0.212
-0.112
Outputs
= biggest loosers
Full protection: selected results
USA
EU
EEFSU
JPN
RoA1
EEx
CHIND
RoW
Coastal
protection
expenditure
(% of GDP)
Investment
induced by
coastal
protection
(% change
w.r.t.
baseline)
GDP
(% change
w.r.t.
baseline)
0.01
0.025
0.332
0.032
0.799
0.185
0.106
0.148
0.151
0.302
3.179
0.242
9.422
2.235
1.254
1.817
0.001
-0.022
0.049
-0.009
0.103
0.015
0.003
0.009
Inputs
Household
CO2
Private
utility
expenditure
Emissions
index (%
(% change
(% change
change
w.r.t.
w.r.t.
w.r.t.
baseline)
baseline)
baseline)
-0.189
-0.262
-0.143
-0.569
-0.315
-0.274
-0.961
-0.355
-0.206
-0.296
0.033
-0.605
-0.009
-0.223
-0.889
-0.31
Outputs
= highest (absolute) values
-0.069
-0.16
-0.133
-0.344
-0.13
-0.069
-0.116
-0.115
Challenges for the future
Extend this modelling framework to evaluate in economic terms the impact of
climate change on biodiversity, on ecosystem services or of carbon
sequestration, their distributional effects and welfare implications.
Translate
environmental
changes into changes in
quality, quantity or type of
production factors
Changes in firm production
patterns, in households’
possibility to consume
Translate environmental changes
into changes of consumers’
preferences
Changes in households’
preferences to consume
Then these information (supply and demand changes)
are suitable to be evaluated “economically”
In practice: integrated assessment and
modularity
Global
Circulation
Models
(Or other)
Environm.
Impact
Models
Climate Change
and Variability
(or other changes in
environmental system)
• Temp. increase
• Temp. rate of change
• Precipitation
• Ecosystem change
Disentangle Climate/
(ecosystem) Change in
(some) Physical Impacts
• Loss of land (sq. Km.)
• Health
(mortality/morbidity)
• Changes in crop yields
• Ecosystem services
Translation in meaningful economic format e.g.:
loss in labour productivity, in tourism flows, fish stock
Economic
(GE)
Model
Provides “post-adaptation”
(GE) welfare
evaluation of physical
impacts
+
Feedback
on the environment
(e.g. emissions)
In sum:
 Translation: of environmental pressures in a supply
and demand “format”  multidisciplinarity.
 Downscaling: integration or consistency of the macro
level computation with micro level evaluation studies.
 Existence of non-market values: often effects are not
market priced  urgency to integrate CGE model
computations (macro level) with non-market valuation
studies (micro level).
Contact:
francesco.bosello@feem.it
paulo.nunes@feem.it
Campo S. Maria Formosa
30122 Venezia - Italy
tel
+39 | 041 | 27 11 400
fax +39 | 041 | 27 11 461
web http://www.feem.it
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