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Economic assessment of climate change
impacts and the role of autonomous
adaptation mechanisms
ISPRA, October 6th, 2017
Francesco Bosello
CMCC, FEEM, University of Milan, Department of
Environmental Science and Policy
Ramiro Parrado – CMCC, FEEM
The issue in a nutshell
1
Source: IPCC AR5 (2014)
«Point estimates» of climate change impacts on world GDP
The issue in a nutshell
2 Source: IPCC AR5 (2014)
Examples of reduced-form climate change damage
functions (CCDF)
)("" ,, titi TflossGDP
The issue in a nutshell
3
Climatic
drivers
Environmental
impacts
• Δ Temp.
• Δ Preci.
• Δ SLR
• ………
Social
Economic
impacts
• Δ flood. land
• Δ desert. land
• Δ crop yield
• Δ mort./morb.
•……………..
• Δ Agr. Prod.
• Δ Health care
expenditure
• Δ Labour
prod.
• ……………..
Climate
Models “Impact”
Models
Translation
phase
CGE
model
Economic
Assessment
This methodology has been extensively used since the beginning of
2000, see e.g.: Deke et al. (2001); Darwin and Tol (2001); Bigano et
al (2008); Aaheim et al., (2010); Bosello et al. (2006, 2007, 2014);
Eboli et al, (2010); Roson and Van der Mensbruegghe (2010); Ciscar
et al, (2011, 2013), ADB (2015) OECD (2016).
Main strenght: ability to capture the role of market adjustments or of
market driven adaptation triggered by climate «shocks» due to the
multi-sector/multi-country nature of CGE models, their explicit
representation of domestic-international market exchanges, and
endogenous price formation.
An alternative approach
The issue in a nutshell
4
But economic assesments of
climate change impacts conducted
with CGE models tend to
«produce» low damage estimates
The issue in a nutshell
5
The issue in a nutshell
6
Many reasons for that (Patt et al 2011, Pindick, 2013, Stern 2013):
Unability to capture «non market» losses referred to non
marketable items (e.g. ecosystem services, changes in
mortality/morbidity), institutional «failures» (lack of
adaptive capacity), social conflicts…
The main loss indicator is GDP a «flow» and not a
«stock» measure.
Instantaneous and frictionless recovery after a shock
too optimistic in assuming substitutability across/mobility
of factor of productions.
Try to assess the economic relevance of climate change using a recursive-dynamic CGE model incorporating latest evidence on different impacts categories
Quantify the role of “market driven adaptation” in determining the final impact. Firstly “full market-driven adaptation” is assumed, then limits or frictions in market adjustments is introduced.
Construct reduced-form climate change damage functions starting from the CGE results and compare with those used by well established “hard linked IA models”.
7
Objectives
Recursive dynamic computable general equilibrium (CGE) model
Based on the GTAP 8 database (Narayanan et al. 2012). Calibration
year 2007
Simulation period: 2007-2050 in one-year time steps
25 countries/regions (this study)
19 sectors (this study)
(as standard in CGE) Inter sectoral and international trade flows
explicitly modelled optimizing agents’ endogenous response
to (endogenous) price signals represents «market-driven
adaptation»
8
The model: ICES
9
Summary of scenarios
Economic reference: SSP2 (“middle of the road”) (O’Neill et al. 2012)
Climate change impacts reconstructed for RCPs: 2.6,
6.0 and 8.5 (Van Vuuren et al. 2011)
+ “Full” adaptation (“default” adjustment mechs.)
As above, but with “Limited” adaptation: - Trade (LA-TR): reducing the model’s flexibility to
accommodate international trade flows.
- Labor mobility (LA-LM): limiting workers mobility within
sectors in each region.
- Primary factor substitution (LA-PFS): decreasing the
flexibility to combine production factors (labor, natural
resources, land and capital-energy).
10
CC Impacts Sources Available
Scenarios
Agriculture PIK - LPJmL ISIP-MIP runs RCPs 2.6, 6.0,
and 8.5
Health Tol (2002) 1°C
Sea level Rise Diva model - Vafeidis et. al (2008)
CLIMATECOST project A1B
Tourism Hamburg Tourism Model - Bigano et. al
(2007) CLIMATECOST project A1, B2
Energy demand POLES model - Criqui (2001), Criqui et.
al (2009) CLIMATECOST project A1B
Forestry PIK - LPJmL Bondeau et. al (2007),
Tiejten et al (2009) CLIMATECOST
project A1B
Fisheries Cheung et. al (2010) SESAME project A1B
Ecosystem Warren et al (2006) 1°C
Climate change impacts: Sources
Climate Change Impact on Gross World Product
11
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
0.1
20
08
20
10
20
12
20
14
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
% c
han
ge w
rt b
asel
ine
RCP 2.6
RCP 6.0
RCP 8.5
CC impacts on GDP in 2050 – regional breakdown
12
-5
-4
-3
-2
-1
0
1
USA
No
rth
_Eu
rop
e
No
rth
_EU
15
Med
_EU
15
Med
_EU
12
East
_EU
12
Ro
Euro
pe
Ru
ssia
Ro
FSU
Sou
thK
ore
a
Au
stra
lia
Sou
thA
fric
a
Can
ada
Jap
an
New
Zeal
and
NA
F
MD
E
SSA
SASI
A
Ind
ia
Ch
ina
EASI
A
Ro
LAC
A
Bra
zil
Mex
ico
Wo
rld
% C
han
ge w
ith
res
pe
ct t
o B
asel
ine
RCP 8.5 RCP 6.0 RPC 2.6
CC impacts on GDP in 2050 – decomposition RCP 8.5
13
-5
-4
-3
-2
-1
0
1
2
-5
-4
-3
-2
-1
0
1
2
USA
No
rth
_Eu
rop
e
No
rth
_EU
15
Med
_EU
15
Med
_EU
12
East
_EU
12
Ro
Euro
pe
Ru
ssia
Ro
FSU
Sou
thK
ore
a
Au
stra
lia
Sou
thA
fric
a
Can
ada
Jap
an
New
Zeal
and
NA
F
MD
E
SSA
SASI
A
Ind
ia
Ch
ina
EASI
A
Ro
LAC
A
Bra
zil
Mex
ico
Pe
rce
nta
ge c
han
ge w
ith
re
spe
ct t
o b
ase
line
Tourism
Sea level rise
Health
Forestry
Fisheries
Energy Demand
Ecosystems
Agriculture
All impacts
“Limiting” adaptation: CC impacts on GWP (RCP 8.5)
14
-1
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0
20
08
20
11
20
14
20
17
20
20
20
23
20
26
20
29
20
32
20
35
20
38
20
41
20
44
20
47
20
50
% c
ha
nge
wit
h r
esp
ect
to
ba
seli
ne
Full Market Adaptation
Labour Mobility
Trade
Factor substitution
All Rigidities
Reduced-form climate change damage functions (CCDF)
Using the different RCPs to obtain different (namely 3)
temperature increases and impacts and GDP effects in
the same year for each region, we then interpolate the
function (To “clean” or control for the social economic
factors we selected as reference one single year (2050))
We did this first accounting for just smooth market
impacts.
Then including a catastrophic damage component
following Nordhaus and Boyer (2000) and Nordhaus
(2007).
Finally adding limits to adaptation
15
Reduced-form CCDF, «smooth impacts»
16
-20
-15
-10
-5
0
0 1 2 3 4 5
Pe
rce
nta
ge
of
GD
P
Temperature change °C
EUROPE
USA
RoANNEX-I
LACA
MENA
WORLD
CHINA
RoASIA
SSA
INDIA
Reduced-form CCDF, «smooth + catastrophic impacts»
17
-10
-8
-6
-4
-2
0
0 1 2 3 4 5
% o
f G
DP
Temperature change °C
EUR-FA
WORLD-FA
CHN-FA
Reduced-form CCDF, «smooth + catastrophic impacts + lim. ad.»
18
-10
-8
-6
-4
-2
0
0 1 2 3 4 5
% o
f G
DP
Temperature change °C
EUR-FA
EUR-LA
WORLD-FA
WORLD-LA
CHN-FA
CHN-LA
Conclusions (1)
In 2050 total costs roughly amount to 0.64% of GWP in RCP 8.5 (2.5°C increase).
Aggregate figures hide important regional asymmetries: higher vulnerability of developing countries to climate change impacts. (South Asia and India lose more than 4% of their GDP, Eastern Asia and Sub Saharan Africa roughly 2% of their GDP in 2050 in RCP 8.5).
Introducing rigidities in market adjustments increases climate change costs (by roughly 30%), but does not change substantively the picture. Key is the modelling of catastrophic outcomes
In the shorter term, trade is a more important source of impact smoothing, in the longer term it is the lower degree of substitutability across primary factors.
19
Conclusions (2)
When the comparison is “even” CGE models do not provide
lower estimates of climate change damages compared to “hard
linked” IA models
More research is needed, at least:
Investigate the role of the social economic context (the
structure of the economy) in impact determination
Better define the range of uncertainties on key parameters
More observations to calibrate the reduced-form damage
functions (very limited knowledge “beyond 3°C”)
20
The need for a precutionary approach
With a doubling of CO2 concentration there is the 5% probability of
experiencing increases of temperature > 5 °C
The need for a precautionary approach
22
10-30% global GDP loss (Weitzman, 2014)
?
Both RCP 8.5 and 6 (more
than doubling CO2 conc.)
will lead us there
Support from econometrics
Source: Burke et al (2015) 23% median global GDP
loss in RCP 8.5
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
Thanks!
This research is based on the outcome of the European Union’s Seventh Framework Programme (FP7/2007-2013) under the grant agreement n°266992 (Global IQ)
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
25
Climate change impacts assessed and modelling strategy
Sea-Level Rise
Energy Demand
Tourism
Fishery
Health
Ecosystems
Δ in land and physical capital stock
Δ residential demand of oil, gas, electricity
Δ in households’ demand for recreational services (part of market services) and in expenditure
Δ labour productivity as well as private and public expenditures
Δ natural resource stock used by the fishing industry
Δ services from physical capital stock
Agriculture (Δ crop yields) Δ land productivity
Forestry Δ in productivity of natural resource stock used by the wood processing sector
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
26
Macro economic drivers of SSP2
World population SSPs (Million) World GDP SSPs ($ Billion)
Regional population trends SSP2
(% ch wrt 2007-2050)
Regional GDP trends SSP2
(% ch. wrt 2007-2050)
Source: https://secure.iiasa.ac.at/web-apps/ene/SspDb/dsd?Action=htmlpage&page=welcome
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
27
Temperature increase in the different RCPs
Source: Rogelj et al (2012)
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
Climate Change Direct Impacts (selected)
28
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
29
«Limiting Adaptation»
• “Trade more difficult” (Armington elasticities reduced to 75%): LA-TR
• “Primary factor substitution more difficult” (substitution elasticity reduced to 75%): LA-PFS
• “Moving labour more difficult” -- Limited labor mobility allowing for wage differences: LA-LM
• All rigidities (TR, LM, PFS): LA-AR
We set the limited adaptation values for elasticities based on:
Armington elasticities: ratio of mean elasticity to the lower end of the 68% confidence interval: μ/(µ- 1σ).
Factor substitution: ratio of short term to medium term elasticities.
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
RCP 8.5 impacts on regional GDP with limited adaptation
30
-6
-5
-4
-3
-2
-1
0
1
2
USA
No
rth
_Eu
rop
e
No
rth
_EU
15
Med
_EU
15
Med
_EU
12
East
_EU
12
Ro
Euro
pe
Ru
ssia
Ro
FSU
Sou
thK
ore
a
Au
stra
lia
Sou
thA
fric
a
Can
ada
Jap
an
New
Zeal
and
NA
F
MD
E
SSA
SASI
A
Ind
ia
Ch
ina
EASI
A
Ro
LAC
A
Bra
zil
Mex
ico
Wo
rld
% c
han
ge w
rt B
asel
ine
All Rigidities Trade Factor substitution Labour mobility CC - Full Market Adaptation
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
RCP2.6: climate-change impact on macro-regional GDP
31
-5
-4
-3
-2
-1
0
1%
ch
ange
wrt
to
Bas
elin
eUSA
North_Europe
North_EU15
Med_EU15
Med_EU12
East_EU12
RoEurope
Russia
RoFSU
SouthKorea
Australia
SouthAfrica
Canada
Japan
NewZealand
NAF
MDE
SSA
SASIA
India
China
EASIA
RoLACA
Brazil
Mexico
World
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
RCP6.0: climate-change impact on macro-regional GDP
32
-5
-4
-3
-2
-1
0
1%
ch
ange
wrt
to
Bas
elin
eUSA
North_Europe
North_EU15
Med_EU15
Med_EU12
East_EU12
RoEurope
Russia
RoFSU
SouthKorea
Australia
SouthAfrica
Canada
Japan
NewZealand
NAF
MDE
SSA
SASIA
India
China
EASIA
RoLACA
Brazil
Mexico
World
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
RCP8.5: climate-change impact on macro-regional GDP
33
-5
-4
-3
-2
-1
0
1%
ch
ange
wrt
to
Bas
elin
eUSA
North_Europe
North_EU15
Med_EU15
Med_EU12
East_EU12
RoEurope
Russia
RoFSU
SouthKorea
Australia
SouthAfrica
Canada
Japan
NewZealand
NAF
MDE
SSA
SASIA
India
China
EASIA
RoLACA
Brazil
Mexico
World
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
Climate change impacts on GWP for RCP 8.5 vs a Full
adaptation baseline
34
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
20
08
20
10
20
12
20
14
20
16
20
18
20
20
20
22
20
24
20
26
20
28
20
30
20
32
20
34
20
36
20
38
20
40
20
42
20
44
20
46
20
48
20
50
% c
han
ge w
ith
re
spe
ct t
o b
ase
line
Full Market Adaptation
Labour Mobility
Trade
Factor substitution
All Rigidities
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
RCP 8.5 impacts on regional GDP with Limited adaptation vs a
Full adaptation baseline
35
-22
-20
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
2
USA
No
rth
_Eu
rop
e
No
rth
_EU
15
Med
_EU
15
Med
_EU
12
East
_EU
12
Ro
Euro
pe
Ru
ssia
Ro
FSU
Sou
thK
ore
a
Au
stra
lia
Sou
thA
fric
a
Can
ada
Jap
an
New
Zeal
and
NA
F
MD
E
SSA
SASI
A
Ind
ia
Ch
ina
EASI
A
Ro
LAC
A
Bra
zil
Mex
ico
Wo
rld
% c
han
ge w
rt B
ase
line
All Rigidities Trade Factor substitution Labour mobility CC - Full Market Adaptation
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
Temperature increases in different RCPs
36
0
1
2
3
4
5
2000 2025 2050 2075 2100
Tem
pe
ratu
re c
han
ge s
ince
pre
-in
du
stri
al
RCP8.5
RCP6.0
RCP4.5
RCP3-PD
Sources: IIASA GGI Scenario database (Version 2.0.1)
Rogelj et al. (2012)
Corso Magenta 63, 20123 Milano - Italia - Tel +39 02.520.36934 - Fax +39 02.520.36946 - www.feem.it
Thanks!
This research is based on the outcome of the European Union’s Seventh Framework Programme (FP7/2007-2013) under the grant agreement n°266992 (Global IQ)
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