four main strands of socio-economic modeling: 1.agent-based, system dynamic models (ecf, madiams)...
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Four main strands of socio-economic modeling:
1. Agent-based, system dynamic models (ECF, MADIAMS)
2. Participatory agent-based models (FEEM, Carlo Giupponi)
3. General equilibrium models, including induced technological change (FEEM )
4. Regional, sector-based models focusing on Arctic (Russian, Norwegian and other partners)
CLIMARES – possible contributions from ECF and other partners to socio-economic modeling of the Arctic regions
Klaus Hasselmann, Max Planck Insitute of Meteorology and ECF
CLIMARES – possible contributions from ECF and other partners to socio-economic modeling of the Arctic regions
Klaus Hasselmann, Max Planck Insitute of Meteorology and ECF
Four main strands of socio-economic modeling:
1. Agent-based, system dynamic models (ECF, MADIAMS) New modeling trend, but exists so far only in global version
2. Participatory agent-based models (FEEM, Carlo Giupponi) Experience in regional applications (river basin areas), but not yet in
larger areas such as Arctic
3. General equilibrium models, including induced technological change (FEEM)
Reduced credibility through global financial crisis and recession, but important as reference to main stream
4. Regional, sector-based models focusing on Arctic (Russian, Norwegian and other partners)
Essential for bringing all strands together
CLIMARES – possible contributions from ECF and other partners to socio-economic modeling of the Arctic regions
Four main strands of socio-economic modeling:
1. Agent-based, system dynamic models (ECF, MADIAMS) New modeling trend, but exists so far only in global version
2. Participatory agent-based models (FEEM, Carlo Giupponi) Experience in regional applications (river basin areas), but not yet in
larger areas such as Arctic
3. General equilibrium models, including induced technological change (FEEM ?)
Reduced credibility through global financial crisis and recession, but important as reference to main stream
4. Regional, sector-based models focusing on Arctic (Russian, Norwegian and other partners)
Essential for bringing all strands together
Traditional coupled climate-economic (integrated assessment-IA) model
climate system
economic system
climate policy
ghg emissions
impacts on production,welfare,…
regulatory instruments
scenario predictions
climate system
economic system
climate policy
ghg emissions
impacts on production,welfare,…
regulatory instruments
scenario predictions
“invisible hand“ establishes market equilibrium
Traditional coupled climate-economic (integrated assessment-IA) model
climate system
economic system
climate policy
ghg emissions
impacts on production,welfare,…
regulatory instruments
scenario predictions
MADIAM (Multi-Actor Dynamic Integrated Assessment Model)
Dynamic evolution, governed by agent strategies
Actors: governments, public, media, consumers, firms, workers, …
k
kdummy
hhat
g
yk
ykdummy
yh
yg
kdeprec
hdeprec
gdecrease
hlnbydo
lambdaL
totconsum
kinit
hinit
ginit
y
lambdak
lamdah
Main routine: production outputs in physical goods units
<rhok>
<rhoh>
<rhog>
<yA>
<shconsum><weconsum>
(Vensim diagram)
The “real economy”: Production output in physical units
k
kdummy
hhat
g
yk
ykdummy
yh
yg
kdeprec
hdeprec
gdecrease
hlnbydo
lambdaL
totconsum
kinit
hinit
ginit
y
lambdak
lamdah
Main routine: production outputs in physical goods units
<rhok>
<rhoh>
<rhog>
<yA>
<shconsum><weconsum>
(Vensim diagram)
The “real economy”: Production output in physical units
y: total production
, invested in:
k: physical capitalh: human capitalg: consumer goods and
services
Monetary subroutines 3: money circulation
fmliquidity hsliquidity
reserves
fminterest
fmcreditupt
w
consum$
moncreatrate<fmcredituptA>
<wA>
hsinterest
hssavrate
<moncreatrateA>
<hssavrateA><hsinterestA>
<consum$A>
<fminterestA>
The “virtual economy” (financial system): money circulation between firms, banks and households
Extensions to analyze impact of climate policies
1. Governments, with policies for carbon taxes, subsidies and recycling of tax income
2. Investment strategies: capital investments subdivided into fossil and renewable energies and energy efficiency
3. Consumer preferences for climate friendly and climate hostile goods
4. Assessment of climate change damages
Model M3a. BAU / MM (Moderate Mitigation)
Model M3a. ITC (Induced Technological Change)
Model M3a. Relative demand Good1(climate-friendly)/Good2(climate-hostile)
Emissions
0
5
10
15
20
25
30
0 20 40 60 80 100
time [y]
Emis
sion
s [G
t C] BAUw
m
s
Production
0
5
10
15
20
0 20 40 60 80 100
time [y]
norm
aliz
ed p
rodu
ctio
n
BAU
w
ms
(a) (b)
Model M3a. mitigation measures: w: weak, m: moderate, s:
strong
Is climate change mitigation affordable?
2000 2100
1% BAU growth
2 -GDP (log Scale)
1 -
3 -
4 -
2000 2100
1% GDP loss corresponds to a delay of 1 year over a period of 100 years–an affordable insurance premium to avoid the risk of dangerous climate change! (see also Azar and Schneider,2002)
2 -
1 -
3 -
4 -
BSP (log Skala)
Is climate change mitigation affordable?
1% BAU growth
Extensions to analyze impact of climate change in Arctic:
1. Include instabilities related to actor behaviour (e.g. financial crisis, business cycles, investment booms and busts)
Textbook view of equilibrium in supply and demand in relation to price (Samuelson and Nordhaus)
System dynamics representation of supply-demand-price interdependence dS/dt = F (S,D,P) (S = supply)
dD/dt = G (S,D,P) (D = demand)
dP/dt = H (S,D,P) (P = price)
dS/dt = F (S,D,P) (S = supply)
dD/dt = G (S,D,P) (D = demand)
dP/dt = H (S,D,P) (P = price)
General result: A system of three first-order ordinary differential equations can have solutions representing:
• a damped periodic, monotonic or non-monotonic (e.g. boom-bust) transition to an equilibrium point
• a stable convergence to a periodic attractor
• an unstable trajectory diverging to infinity
• a bounded, non-periodic chaotic trajectory
Which type of solution is realized depends on the initial conditions and the behaviour of the economic actors
System dynamics representation of supply-demand-price interdependence
supply
2
1.5
1
0.5
0
0 1 2 3 4 5 6 7 8 9 10Time (Year)
supply : Talk 4 M1 good/Yearsupply : Talk 3 M1 good/Yearsupply : Talk 2 M1 good/Yearsupply : Talk 1 M1 good/Year
demand
2
1.5
1
0.5
0
0 1 2 3 4 5 6 7 8 9 10Time (Year)
demand : Talk 4 M1 good/Yeardemand : Talk 3 M1 good/Yeardemand : Talk 2 M1 good/Yeardemand : Talk 1 M1 good/Year
price
2
1.5
1
0.5
0
0 1 2 3 4 5 6 7 8 9 10Time (Year)
price : Talk 4 M1 $/goodprice : Talk 3 M1 $/goodprice : Talk 2 M1 $/goodprice : Talk 1 M1 $/good
General equilibrium model: evolution to joint equilibrium in supply, demand and price for four different initial conditions
supply
4
3
2
1
0
0 2 4 6 8 10 12 14 16 18 20Time (Year)
supply : Run 3a-M5 good/Yearsupply : Run 3c-M5 good/Year
demand
4
3
2
1
0
0 2 4 6 8 10 12 14 16 18 20Time (Year)
demand : Run 3a-M5 good/Yeardemand : Run 3c-M5 good/Yearprice
4
3
2
1
0
0 2 4 6 8 10 12 14 16 18 20Time (Year)
price : Run 3a-M5 $/goodprice : Run 3c-M5 $/good
Boom-bust model:
Equilibrium model:
Business cycle model: two-feedback loops, one postive (unstable), one negative (stabilizing)
consumption decrease delcons
production decrease delypositive loop
negative loopwage decrease delw employm. increase
increase
demand
supply
price
Extensions to analyze impact of climate change in Arctic:
1. Include instabilities related to actor behaviour (e.g. financial crisis, business cycles, investment booms and busts)
2. Regionalization: different countries, different geographic regions
3. Sector resolution: different economic sectors (fishing, transportation, resources, tourism)
4. Feedbacks of consumer behaviour
5. Assessment of climate change damages
6. Uncertainty and risk assessment
Strategy:
Develop hierarchy of models with gradually increasing complexity
Strategy:
Develop hierarchy of models with gradually increasing complexity
And apply Occam’s razor:
use the simplest model that explains the phenomenon!