Transcript Evaluation with stylized facts - at www.ampere

Evaluation with stylized facts
AMPERE Subgroup on IAM Validation
Valeria Jana Schwanitz
Potsdam Institute for Climate Impact Research
27. Mai 2013
Content
Fundamental laws and stylized facts
Systematic evaluation of IAMs with stylized facts
Evaluating AMPERE models with stylized facts
Stylized conclusion and outlook
From fundamental laws to observable deep-order patterns
Natural Science:
Controlled experiments confirm fundamental laws.
F =G
m1 m2
r2
Example from Newton, 1686.
Social Science (and coupled complex systems):
Uncontrolled observations suggest some stylized patterns.
1
1
Sch1 Hneg
Zneg
1 1 1 1 4
ib a c A B C ↑
W 4 L1 ↓ V 1 Sch1 H 1 Z 9 = R 4 × 3
sch7 H 7 Z 9
Example from Propp, 1928.
Definition of stylized fact:
Kaldor 1961 (Economic Growth Theory),
Buchanan 2012 (Complex Social Systems)
Systematic evaluation of IAMs with stylized facts
Proposal for a community-wide list of stylized facts.
Criteria for selection:
I
Evaluation value:
acceptance, relevance, endogenous and exogenous model results,
transperancy
I
Completeness:
capturing important system processes and scales
I
Applicability:
to a broad class of IAMs of global climate change
Identifying relevant system processes
Use of PIRT-Tables
PIRT - Phenomena Identification and Ranking Tables
0
.
0
!
&1*+230
4!4
%56,%7
*
0
!"#
#
*%
8#0
*
.
0%0
"
#$
0
$
$
$
%!
#%%%!
9!"
0
"%%0
Proposal: List of stylized facts
Focus on endogenous and quasi-endogenous model results
I
Economic development
SF 1: Consumption ∝ economic growth
SF 2: Economic growth ∝ investment
I
Energy transition
SF 3: Output intensity of final energy ∝ 1/(per capita income)
SF 4: Consumption of primary energy per capita ∝ per cap income
SF 5: Share of residential sector in FE ∝ 1/per capita income.
U-shape relationship for industry share. Service sector share ∝ per
capita income. Agriculture is small.
SF 6: Increasing share in modern energy technologies, solids
decrease at the same time.
I
Energy transition/Climate change
SF 7: Trend towards decarbonization.
I
Technological change
SF 8: Extent of technology diffusion ∝ duration of tech diffusion
SF 9: Spacial acceleration of technology diffusion.
Testing stylized facts in AMPERE models: Two examples
Testing stylized facts: Consumption and GDP
Acemoglu 2: Correlation between consumption and GDP
data from PWT 7.0, year: 2000
5
linear regression, slope: 0.89
linear regression, slope: 1.03
log ( per capita consumption )
4.5
USA
JPN
EUR
USA
ISL
GBR
CHE NOR
BMU
AUT
NLD
CAN
AUS
GER
SWE
FRA
DNK
BEL
JPN
ITA
IRL ARE
HKG
ESPFIN
BHS
GRC
NZL
PLW
BRB
TWN
MLTISR
PRT
PRI
SGP
KWT
CYPSVN
BRN
CZEKOR
BHR
MAC
HUN
KNAPOLSVK
GRD
LBN MEX
SYC
TTO
URY
EST
LTU
ARG
HRV
TUR
JAM
MHL
BLZ
CRI LCA
BIHTON LVA
CUB
BRA CHL
SAU
MKDDOM
ATG OMN
SLV
WSMBGR MUSRUS
LBY
ROM
GTM
COL
BLR
ZAF PAN VEN MYS
MNE
IRN
PER
KAZTHA
ECU
DMA
FJI
EGY
PRY
VUT
TUN
ALB
NAM
JOR
BWA GAB
SWZ
VCT
FSMUKR
BOL
ARMGEO
AZE
GUY
HND
SYR
LKA
CPV IDN KIR
DJI PHL
MAR
TKMDZA
MDA NIC
SUR
PAK
HTI SDN
BTN CH2
KGZ
MDV
MNG
CMR
INDYEM
LSO
CHN
LAO
SENCIVVNM PNG
STPKEN
MRT
KHM
TJK
BEN UZB
TLS
IRQ
NPL
BGDNGA
COM
GHA
TGO
GNQ
MDG
BFA
UGA
TZA
ZMB
MLI
GMB
SLB
GIN
COG
AGO
ERI
SLE CAF
RWA
LBR
4
ROW
LUX
QAT
LAM
RUS
3.5
OAS
MEA
IND CHN
3
AFR
MOZ
NER
GNB
BDI ETH
AFG
MWI
SOM
2.5
ZAR
2
2
TCD
ZWE
2.5
3
3.5
log( per capita GDP )
4
4.5
5
Testing stylized facts: Consumption and GDP
IMAGE, AM3S1
log per capita consumption [$2005 PPP]
6
5.5
RUS
CHN
UKR RSAM
STAN
SEAS
RCAMBRA
RUS
NAF CEU
SAF USA
UKR
INDIAINDO
CAN
CHN
ME MEX
RSAM
JAP
TURKOR
STAN World
WEU
USAOCE
SEAS
RSAS
RCAM
RUS
BRA CAN
CEUSAF
JAP
METURMEX
UKRNAF INDIA
WEU
USA OCE
INDOKOR
CHNWorld
RSAM
RSAF CAN
STAN
CEU
JAP
EAF
USA OCE
RCAM
MEXWAF
WEU
SAF
TUR
BRA
MERSAS
5
4.5
UKR
4
NAF
SEAS
NAF
KOR
World
CAN
INDIA
RUS
OCE
CEU INDO
RSAF
WEU
JAP
EAF
RSAM MEX
RCAM TUR
BRA ME
SAF
RSAS
SEAS
CHN
RSAF
STAN
EAF WAF
INDO
WAF
KOR
World
INDIA
RSAS
RSAF
3.5
EAF
3
3
WAF
3.5
4
4.5
5
log per capita GPD [$2005 PPP]
5.5
6
Testing stylized facts: Consumption and GDP
IMACLIM, AM3S1
log per capita consumption [$2005 GDP]
6
5.5
CAN JANZ
USA
JANZ FSU
RAL
EUR
USA
CHN
FSU
5
CAN
CAN
JANZUSAEUR
RAL
MEA
4.5
FSUUSA World
BRA
EUR RAS MEA
BRA
RAS
World
MEA
CHN
IND
RALJANZCAN
World
CHN
BRA
EUR
MEA
4
IND
RAS
AFR
RAL
FSU
World
AFR
IND
BRA
RAS
3.5
AFR
CHN
AFR
IND
3
3
3.5
4
4.5
5
log per capita GDP [$2005 PPP]
5.5
6
Testing stylized facts: Consumption and GDP
MESSAGE, AM3S1
5
PAO
NAM
WEU
PAO
NAM
log per capita consumption [$2005 PPP]
WEU
NAM
PAO
LAM
EEU
CPA
WEU
PAS
NAM FSU
MEA
World
4.5
LAM
PAOCPA
EEU
WEU FSU
PAS
SAS
World
MEA
CPA
EEU
FSU
AFR
LAM
World
SAS
EEU
4
MEA
PAS
AFR
FSU
World SAS
LAM
MEA
PAS
AFR
3.5
CPA
SAS
AFR
3
3
3.5
4
log per capita GDP [$2005 PPP]
4.5
5
Testing SF (extensive): Transition of energy structure
Energy transition - structure
projections by REMIND
World - historical data (1800-2000)
100
Grids (electricity, gases, heat, hydro)
FE structure [% of total FE]
80
LIQUIDS
60
40
EMF27G1
EMF27G17
20
0
1800
SOLIDS (coal, biomass, trad. biomass)
1850
1900
1950
EMF27G9
2000
2050
EMF27G1
EMF27G17
EMF27G9
2100
Testing SF (intensive): Transition of energy structure
data from ENERDATA and PWT 6.3
1
share of solids in final energy consumption
BDI
COD
BTN
COD
NPL
BDI
BTN
BTN
TZA
BDI
TZA
MOZ
BDI
MOZ
TZA
NPL
COD
NER
BTN
NPL
NPL
TZA
LAO
NGA
MOZ
NER
NGA
LAO
NGA
NER
NER
NGA
LAO
XYZ 1990
VNM
MOZ
HTI
ZMB
KEN
ZWE
ZWE
HTI
SDN
MDG
CHN
KEN
SDN
ZMBZWE
KEN
ZMB
SWZ
ZWE
KEN
ZMB
HTI
LAO
VNMLKA
MWI
HTI
SDNCHN
MDG
SDN
GTM SWZ
MWI
IND
MWI
MWI
SWZ
SWZ
0.8
XYZ 1995
XYZ 2000
XYZ 2005
MDGVNM
MDG
BGD
LKA
HND
IND CHN
GTM
LKA
BWA
GTM
HND LKA
IND SLV
CHN
IND
BGD
PAK
IDN
SEN VNM
BWA
0.6
FJI
GTM
PHL
BWA
PAK IDN
SLV
ZAF
HND
SEN PAK
ZAF
SEN
BGD
FJI
IDNSLV
CUB
IDN CUB POL
ZAF
FJI
BIHALB
BWA MUS
SLV
MNG
CRI
TUR
ZAF
PHL
COL
MNG
SEN
HND
BGD
PAK
0.4
THA
CZE
BRA
CUB
BOL DOM
ALB PHL PAN POLBRA
FJICOL BRA
PER
PHL DOM
CHL POL MUS
GEO
TUR
SVK
TUR
KAZ
0.2
0
LUX
BOLGEO
THA
BRA
URY
KAZ CZE
CUB
CHL
COL LVA
PER PAN
BIH
SVK LVA
LVATUR
CZE
POL
THA
PAN
PER THA
KAZ
PER
FIN
AFG MNG
PAN
KOR
CHL
FIN
MRTBOL BIH
FIN
COL
MRT
BIH
URY
PRT CHL
EST
IRL
MKD DOM
BOL UKR
UKR CRI SVK
MNG
CZE
FIN
AFG
SVK PRT
UKR
AUT
AFG
MKD DOM
ROU
MRT KGZ
EST
SWE
SRBCRI
SWE
URY
SWE
SWE DEU
AUT
ROU ESTBGR
ALB
HUN
AUT
URYTWN
TUN
BGR
LTU
GEO LTU
BEL JPN
AUT
AFG
TUN TUN
NZL PRT
AUS NZL AUS
MKD MYSEST
TWN
ROU
MAR
JPN
MUS GRC
FRATWN
AUS
SVN
TWN NZL
TUN
BGR
JPN JPN
LTU
KOR
KOR KOR
NZL
ALB
ESP
RUS
MAR
KGZ
JAM
ROU
HRV
MEX HUN
GRC PRT
MEX
JAM
JAM
FRA
SVN IRL
BEL
SVN
AUSNOR
MUS
CRIMEX MYS
BGR
BEL
MYS
FRA FRANOR
GRCGBR
RUS
MAR
MYS
SVN
JAM
MEX
DEU
MDA
DEU
ESP
LBNMKD
DEU
BLRHUN
RUS
DNK
EGY
CAN
KGZEGY
LBN
LBN
USA
BEL
BLR HRV RUS
CAN
CAN
MDA
CAN
DNK GRC
HRV
BLR
HRV
IRL
GBR
ARG
HUN
CYP
DNK
MDAEGY
DNK
CHE
LBN
ESP
MAR
CHE
CHE USACHE
ARG ARG
ESP
CYP
EGY
ITA NLD
ITA NLD
ISL NLD
GBR
VEN
ITA
ITA
ARG
ISL
UZB
GBR NLD
DZA
DZA
CYP ISL
VEN
CYP
DZADZA
VEN
IRN IRN IRN IRN
HKG
UZB
UZB
HKG HKG
UZB ARM
MAC
ISR MAC MAC
ISR
SGP
ISR SGP
ARM AZE ARM
SYR
ISR
SYR
SYRAZE
AZE
SYR
SGP
0
20000
LUX
NOR
NOR
HKG
IRL
USA
ISL
USA
MAC
AREARE
SGP
ARE
LUX
LUX
ARE
40000
per capita GDP [$2005 PPP]
60000
80000
Testing SF (intensive): Transition of energy structure
AM3S1
AFR
EAF
REMIND 2100
REMIND 2070
REMIND 2040
REMIND 2010
POLES 2100
POLES 2070
POLES 2040
POLES 2010
MESSAGE 2100
MESSAGE 2070
MESSAGE 2040
MESSAGE 2010
IMAGE 2100
IMAGE 2070
IMAGE 2040
IMAGE 2010
IMACLIM 2100
IMACLIM 2070
IMACLIM 2040
IMACLIM 2010
0.8
RSAF
share of solids in final energy
SSAF IDT
WAF
EAF
0.6
AFR
SASCHN
CHN
INDIA
NDECHN
IND
CHN
CHN
AFR
CPA
0.4
CHN
SAF
AFR
RCAM
SEAS
OAS
KOR
SSAF IDT
EAF
TUR
CHN
RJAN
IDT
BRA RASIA
NDE
BRA
CEAM IDT
World
MIEA IDT
USA
CHN
COR
JPN
World OAS
INDPAS
INDIA
RJAN
RSAM
INDIA
OCIS IDT RSAMJAP
WRD
World
TUR IDT
RASIA IDT
OCIS IDT
BRA
TUR IDT
UKR
WRD
World
WAF
WRDUKR
World
IDT
RSAS
CPA
LAM
USA
WRD IDT
World
World IND EEU
COR
RSAS
EU15
IDT
RSAM
EU12
IDT
EU12
IDT
JAP
IND
ROW
CEAM
IDT
RUS
UKR SSAF IDT
OCIS IDT
CEU
RJAN TUREU12BRA
IDT
AFR
SAS
EU15
IDT
CHN
CAN
RCAM
AFR World
CAN
CHN
RCEU
IDT
SAF
CHN
INDIA
KOR
EU12
IDT
JPN
RCAM
SSAF
IDT
MIEA
IDTIDT
RCEU
IDT
CEURSAFWorld
EEU
TUR
RASIA IDT
JPN
BRA
RCEU IDT
EU15
NDE
RUS
WAF
TUR
SAF
OCIS
IDT PAS
LAM
EEU
RSAS
TUR
COR
World
World JAP MEX IND
JPN
CEAM
IDTNOAF IDT
EEU
EAF
CEAM
IDT
IND
RCEU
IDT
WEU
World
CAN
World
COR
KOR
RCAM
FSU
CHN
RSAM
TUR
RUS CAN
KOR
SEAS
CPA
CEU
LAM RJAN
RAS
World USA NOAF IDT
BRA
NAFRSAM
JAP
FSU INDO
RASROWE
PAS JANZPAO
CEU
World
INDO IDT
JPN
PAS
CAN
JANZ
ROWRSAF
RASSAS
PAOLAM
BRA
MEXSAFROWE IDTCHN
PAO World
RUSOCE
STAN
PAO
World
RAS
NOAF
IDT EUR
ROWE
IDT
NDE
BRA
MEX
SEAS
AFR
OCE
JANZ
BRA
OCE
MEX
JPN FSUMEA
STAN
AFR
AFR
USA
LAM
UKR BRABRA
FSU
JPN USA
JPN
RSAM
World
IDT
EUR
RSAM
NAF
WEUFSU
RUS AFR MIEA
OAS
FSU
BRA
RUS
CAN
NAM
EU15
IDT
CHN
CAN
FSU
AFR
RUS
RUS
INDO
EUR
ROWE
IDT
WEU
SEAS
WEU
ROW
ROW
JANZ
RUS
STAN
IND
NAM
RSAM OCE
RUSWEU
NAFUSA
USA
USA
USA World
NAF
SAS
NAM
NOAF IDT
CAN
CHN
LAM
STAN
USA EUR
USA RAL LAM RUS
OAS
LAM
USA
NAM
MEA
ME
RAL CAN EURUSAWEU
RUS
USA
World
RAL WEUEUR
RAL
MEA
USA
USA
CAN
INDCAN
MEA
MEA
ME
WEU
ME
AFR ME CPA
EUR
CAN
EUR
MEA
MEA
MEA
MIEA
IDT MEA
MEA
MEA
MEA
FSU
0.2
0
CHN
RSAF
RSAS
INDO
WAF
RASIA IDT
0
50000
1e+05
1.5e+05
per capita GDP [$2005 PPP]
2e+05
Testing SF (intensive): Transition of energy structure
AM3S1
AFR
EAF
REMIND 2100
REMIND 2070
REMIND 2040
REMIND 2010
POLES 2100
POLES 2070
POLES 2040
POLES 2010
MESSAGE 2100
MESSAGE 2070
MESSAGE 2040
MESSAGE 2010
IMAGE 2100
IMAGE 2070
IMAGE 2040
IMAGE 2010
IMACLIM 2100
IMACLIM 2070
IMACLIM 2040
IMACLIM 2010
0.8
RSAF
share of solids in final energy
SSAF IDT
WAF
EAF
0.6
AFR
SASCHN
CHN
INDIA
NDECHN
IND
CHN
CHN
AFR
CPA
0.4
CHN
SAF
AFR
RCAM
SEAS
OAS
KOR
SSAF IDT
EAF
TUR
CHN
RJAN
IDT
BRA RASIA
NDE
BRA
CEAM IDT
World
MIEA IDT
USA
CHN
COR
JPN
World OAS
INDPAS
INDIA
RJAN
RSAM
INDIA
OCIS IDT RSAMJAP
WRD
World
TUR IDT
RASIA IDT
OCIS IDT
BRA
TUR IDT
UKR
WRD
World
WAF
WRDUKR
World
IDT
RSAS
CPA
LAM
USA
WRD IDT
World
World IND EEU
COR
RSAS
EU15
IDT
RSAM
EU12
IDT
EU12
IDT
JAP
IND
ROW
CEAM
IDT
RUS
UKR SSAF IDT
OCIS IDT
CEU
RJAN TUREU12BRA
IDT
AFR
SAS
EU15
IDT
CHN
CAN
RCAM
AFR World
CAN
CHN
RCEU
IDT
SAF
CHN
INDIA
KOR
EU12
IDT
JPN
RCAM
SSAF
IDT
MIEA
IDTIDT
RCEU
IDT
CEURSAFWorld
EEU
TUR
RASIA IDT
JPN
BRA
RCEU IDT
EU15
NDE
RUS
WAF
TUR
SAF
OCIS
IDT PAS
LAM
EEU
RSAS
TUR
COR
World
World JAP MEX IND
JPN
CEAM
IDTNOAF IDT
EEU
EAF
CEAM
IDT
IND
RCEU
IDT
WEU
World
CAN
World
COR
KOR
RCAM
FSU
CHN
RSAM
TUR
RUS CAN
KOR
SEAS
CPA
CEU
LAM RJAN
RAS
World USA NOAF IDT
BRA
NAFRSAM
JAP
FSU INDO
RASROWE
PAS JANZPAO
CEU
World
INDO IDT
JPN
PAS
CAN
JANZ
ROWRSAF
RASSAS
PAOLAM
BRA
MEXSAFROWE IDTCHN
PAO World
RUSOCE
STAN
PAO
World
RAS
NOAF
IDT EUR
ROWE
IDT
NDE
BRA
MEX
SEAS
AFR
OCE
JANZ
BRA
OCE
MEX
JPN FSUMEA
STAN
AFR
AFR
USA
LAM
UKR BRABRA
FSU
JPN USA
JPN
RSAM
World
IDT
EUR
RSAM
NAF
WEUFSU
RUS AFR MIEA
OAS
FSU
BRA
RUS
CAN
NAM
EU15
IDT
CHN
CAN
FSU
AFR
RUS
RUS
INDO
EUR
ROWE
IDT
WEU
SEAS
WEU
ROW
ROW
JANZ
RUS
STAN
IND
NAM
RSAM OCE
RUSWEU
NAFUSA
USA
USA
USA World
NAF
SAS
NAM
NOAF IDT
CAN
CHN
LAM
STAN
USA EUR
USA RAL LAM RUS
OAS
LAM
USA
NAM
MEA
ME
RAL CAN EURUSAWEU
RUS
USA
World
RAL WEUEUR
RAL
MEA
USA
USA
CAN
INDCAN
MEA
MEA
ME
WEU
ME
AFR ME CPA
EUR
CAN
EUR
MEA
MEA
MEA
MIEA
IDT MEA
MEA
MEA
MEA
FSU
0.2
0
CHN
RSAF
RSAS
INDO
WAF
RASIA IDT
0
50000
1e+05
1.5e+05
per capita GDP [$2005 PPP]
2e+05
To do: Stylized fact about a brain’s capacity to process information
within a 20 min talks??? Stop here.
Testing stylized facts: Investments and GDP
Dosi SF
data from PWT 7.0, year: 2005
5
QAT
linear regression, slope: 1.09, correlation coefficient: 0.96
linear regression, slope: 0.98, correlation coefficient: 0.97
ISL KWT
NOR
AUS
SGPARE
MAC
BHS HKG
CHEUSA
IRL
BHR
BEL
CAN
DNK
KOR
JPN
AUT
SYC ESPFIN
BMU
TTO
SVN
ITA
BRB TWNFRASWE
NLD
NZL
GRD
OMN
GBR
SAU
BRN
PRT ISRGRC GER
KNA
EST
CZE
ATG
MHL
CYPMLT PRI
LVAHRVSVK
HUN
LBN LCA
BWA
GNQ
CHL
KIR
PLW
GAB
MYSMEX
LTU
IRN
POL
MDV
CRI
JAM
THA MUS
KAZ
BGR
BTN JOR
CHN
CH2
ARG RUS
TUR
LBY
BLZ
DZA
URY
BLR
VEN
SRBROM
VCT
ECUCOL
ZAF
ALB
TUN
TON
PAN
DMA
AZE
BRA
CPV
BIH PERMKD DOM
IRQ
MARFSM NAM VUT
GTM
MNE
MRT
UKR
GEO ARM
SLV
LKA
MNG HND
VNM
IDNSYR FJI
IND
YEM
GUYEGY
WSM
PRY
LAONIC
SWZ
STP
MDA
SEN UZB
DJIPHL
SDN COG
BOL
AGO
PNG
PAK
BGDZMB
GMB
GHA
NPL TCD KHMCMR
LSO
CUB
GIN
TZA BEN
TKM
SLB
MLI
MWI AFG
KGZ
UGAKEN
TLS
HTI
BFA
MDG
ERI
NER
TGO COM
ETH
RWA
CIV
TJK
NGA
MOZSLE
SOM
4
log ( per capita investment )
LUX
USA
JPN
EUR
SUR
ROW
CHNMEA RUS
LAM
OAS
3
IND
AFR
2
GNB
ZAR
BDI
LBR
CAF
ZWE
1
2
2.5
3
3.5
log ( per capita GDP )
4
4.5
5
Testing stylized facts: Investments and GDP
EMF27G1, year: 2020
4
linear regression, slope: 0.86, correlation coefficient: 0.95
log ( per capita ESM investments )
3.5
USA
3
ROW
RUS
MEA
2.5
EUR
JPN
CHN
LAM
OAS
IND
2
AFR
1.5
1
3
3.5
4
log ( per capita GDP )
4.5
5
Testing stylized facts: Development of FE/cap over
population
FE/POP vs POP MEA
historic aggregate
EMF27G1
EMF27G9
EMF27G17
QAT
600
per capita Final energy consumption [GJ]
200
150
500
100
400
50
0
0
0.2
0.4
0.6
300
200
0.8
OMN
TJK
GEO
SYR
KAZ
YEM
DZA
AZE
ISR
LBN
LBY
UZB
SAU
ARM
JOR
TUN
IRN
KWT
BHR
MAR
EGY
TKM
ARE
KGZ
100
0
0.0001
0.001
0.01
Population [billions]
0.1
1
Testing stylized facts: Development of FE/cap over
GDP/cap
FE/POP vs GDP/POP EUR
350
300
per capita Final energy consumption [GJ]
historic aggregate
EMF27G1
EMF27G9
EMF27G17
ROU
GRC
DEU
AUT
BGR
MLT
SVK
LUX
ITA
LTU
FRA
EST
CYP
LVA
GBR
SVN
IRL
BEL
POL
FIN
SWE
HUN
DNK
PRT
NLD
ESP
CZE
ANT
1970 - 2100
250
200
150
100
50
0
0
20000
40000
per capita GDP [ PPP D 2005 ]
60000
80000
Testing stylized facts: Distribution dynamics of PE intensity
Testing stylized facts: Substitution of energy technologies
Primary energy consumption, Fisher-Pry plot, EMF27G17
world, data from BP 2011, Smil, and WEO
2
10
oil, own, BP 2011
coal, own, BP 2011
gas,own, BP 2011
nuclear, own, BP 2011
hydro, own, BP 2011
oil, Smil
coal, Smil
gas, Smil
nuclear, Smil
hydro, Smil
biofuels, Smil
oil, WEO
coal, WEO
gas, WEO
nuclear, WEO
hydro, WEO
biofuels, WEO
coal, EMF27G1
oil, EMF27G1
gas, EMF27G1
nuclear, EMF27G1
biofules, EMF27G1
hydro, EMF27G1
wind, EMF27G1
solar, EMF27G1
geothermal, EMF27G1
1
10
0
10
f/(1-f)
-1
10
-2
10
-3
10
-4
10
-5
101800
1900
2000
years
2100
2200
Testing stylized facts: Distribution dynamics of carbon
intensity
Dynamic distribution of carbon intensity of FE
0.07
0.04
Efficiency
Mix
Supply
0.03
0.06
0.05
0.04
0.02
0.03
2010
0.01
2040
0.02
0.01
0
-200
-100
0
100
200
0
-200
-100
0
100
200
0.03
0.08
0.025
density
0.06
0.02
0.04
0.015
2070
2100
0.01
0.02
0.005
0
-200
-100
0
100
200
deviation from average / average in 2005
0
-200
-100
0
100
200
Stylized outlook - What can be done should be done
Possible ex-ante
using stylized facts to evaluate IAMs of global climate change:
I
educated opinion formation about future developments
I
systematic questioning of model behavior (incl. model
inter-comparison)
I
community list of stylized facts could serve as a criteria for model
quality
Only possible ex-post
validating forecasting power:
Marquardt 1981 citing O’Neills 1975
I
2005 Establishing first Marsian mines
I
2040 100 000 people living on Mars