Climate Change and the Financial Crisis
Klaus Hasselmann
Max Planck Institut for Meteorology, Hamburg,
and Global Climate Forum
Workshop on Coupled Climate-Economics
Modelling and Data Analysis
ENS, Paris, 22-23 Nov 2012
Or: Where do we stand in Integrated
Assessment modelling today?
-
four years after the financial crisis
-
four years after complete stagnation in
international climate policy
Climate policy impacts of the financial crisis
before
Nov 2008
after
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
after
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
after
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
after
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
Climate highlighted by
all political leaders
(e.g. Obama, Merkel,..)
after
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
Climate highlighted by
all political leaders
(e.g. Obama, Merkel,..)
after
UNFCCC 15 failure
in Copenhagen
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
Climate highlighted by
all political leaders
(e.g. Obama, Merkel,..)
after
UNFCCC 15 failure
in Copenhagen
Pre-occupation of
policy-makers with
financial crisis
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
Climate highlighted by
all political leaders
(e.g. Obama, Merkel,..)
after
UNFCCC 15 failure
in Copenhagen
Pre-occupation of
policy-makers with
financial crisis
No clear statements
from scientists
Climate policy impacts of the financial crisis
before
Nov 2008
High expectations in
UNFCCC 15, Dec 2009
Copenhagen
2007, Nobel peace prize,
IPCC and Al Gore
2007, Stern Report
Climate highlighted by
all political leaders
(e.g. Obama, Merkel,..)
after
UNFCCC 15 failure
in Copenhagen
Pre-occupation of
policy-makers with
financial crisis
No clear statements
from scientists
Climate becomes a
political no-word (cf.
Obama-Romney debates)
In fact, the two problems cannot be separated
climate policy
financial crisis
In fact, the two problems cannot be separated
climate policy
financial crisis
1. The resolution of the recession and sovereign debt
problems following the financial crisis requires major
new public and private investments
In fact, the two problems cannot be separated
climate policy
financial crisis
1. The resolution of the recession and sovereign debt
problems following the financial crisis requires major
new public and private investments
2. Renewable energy technologies and enhanced
energy efficiency provide ideal opportunities for
investment
- creating many new jobs
- with wide support in the public
In fact, the two problems cannot be separated
climate policy
financial crisis
1. The resolution of the recession and sovereign debt
problems following the financial crisis requires major
new public and private investments
2. Renewable energy technologies and enhanced
energy efficiency provide ideal opportunities for
investment
- creating many new jobs
- with wide support in the public
So how did this disconnect between logic and
the political process arise?
An explanation:
Climate scientists and economists have lost
credibility with policy-makers and the public in
their recommendations of the appropriate policy
response to climate change
An explanation:
Climate scientists and economists have lost
credibility with policy-makers and the public in
their recommendations of the appropriate policy
response to climate change
because:
1. economists failed to predict the financial crisis,
through their belief in the self-rectifying forces
of the free market
An explanation:
Climate scientists and economists have lost
credibility with policy-makers and the public in
their recommendations of the appropriate policy
response to climate change
because:
1. economists failed to predict the financial crisis,
through their belief in the self-rectifying forces
of the free market
2. most integrated-assessment models have
similarly been based on the efficient-market
paradigm - ignoring the instabilities that led to
the financial crisis. So how can they be relevant
for solving the financial crisis and initiating a
green transformation?
Thus, we need a new generation of integrated
assessment models.
Ideas: see set of papers in forthcoming Thematic Issue
“Innovative Approaches to Global Change Modelling”
of Ecological Modelling and Software
With lead article by Carlo Giupponi, Mark Borsuk, Bert
de Vries and KH
(based on two workshops of the Global Climate Forum –
formally European Climate Forum - in Bekkjarvik, 2009
and Utrecht, 2010)
For impact on stakeholders and climate policy, the
models would need to incorporate the following
features:
• simple, easily understandable, addressing the current
political debate
For impact on stakeholders and climate policy, the
models would need to incorporate the following
features:
• simple, easily understandable, addressing the current
political debate
• realistic representation of the coupling between the
real economy and the financial system
For impact on stakeholders and climate policy, the
models would need to incorporate the following
features:
• simple, easily understandable, addressing the current
political debate
• realistic representation of the coupling between the
real economy and the financial system
• inclusion of the inherent instabilities of the coupled
system
For impact on stakeholders and climate policy, the
models would need to incorporate the following
features:
• simple, easily understandable, addressing the current
political debate
• realistic representation of the coupling between the
real economy and the financial system
• inclusion of the inherent instabilities of the coupled
system
• representation of the conflicting strategies between
different economic actors that give rise to the
instabilities – in particular, public-private conflicts
For impact on stakeholders and climate policy, the
models would need to incorporate the following
features:
• simple, easily understandable, addressing the current
political debate
• realistic representation of the coupling between the
real economy and the financial system
• inclusion of the inherent instabilities of the coupled
system
• representation of the conflicting strategies between
different economic actors that give rise to the
instabilities – in particular, public-private conflicts
• system-dynamic evolution rather than utility
optimization
An example:
MADIAMS: Multi-Actor Dynamic Integrated Assessment
Model System
MADIAM: Weber et al, Ecolog, Econ. 2005;
MADIAMS: KH and Voinov, in “Reframing the Problem of
Climate Change”, Earthscan, 2011
KH and Kovalevsky, Environ. Mod. Softw, in press,
KH, Tellus, submitted
An example:
MADIAMS: Multi-Actor Dynamic Integrated Assessment
Model System
MADIAM: Weber et al, Ecolog, Econ. 2005;
MADIAMS: KH and Voinov, in “Reframing the Problem of
Climate Change”, Earthscan, 2011
KH and Kovalevsky, Environ. Mod. Softw, in press,
KH, Tellus, submitted
MADIAMS: S = system: the model is designed as a
hierarchical model family.
An example:
MADIAMS: Multi-Actor Dynamic Integrated Assessment
Model System
MADIAM: Weber et al, Ecolog, Econ. 2005;
MADIAMS: KH and Voinov, in “Reframing the Problem of
Climate Change”, Earthscan, 2011
KH and Kovalevsky, Environ. Mod. Softw, in press,
KH, Tellus, submitted
MADIAMS: S = system: the model is designed as a
hierarchical model family.
Here, a simple version: 7 actors;
real-economy sector:3 state variables;
financial sector: 11 state variables
Simple version: real economy, state variables
r capital associated with renewable energy technology
k capital associated with conventional energy technology
g consumer goods and services
Simple version: real economy, state variables
r capital associated with renewable energy technology
k capital associated with conventional energy technology
g consumer goods and services
Total production
y = yr + yk + yg with y = y(r,k)
Simple version, real economy, state variables
r capital associated with renewable energy technology
k capital associated with conventional energy technology
g consumer goods and services
Total production
y = yr + yk + yg with y = y(r,k)
Growth path - determined by distribution
yr = r y,
yk = k y,
yg = g y
of y ( = GDP) between three production streams, with
distribution factors r, k, g governed by actor strategies
total production
stocks: capital and
consumer goods
flows: production
flows: depreciation
and consumption
Examples of two real-economy growth paths:
BAU and
GREEN (green transformation)
g
BAU
r = 0
k
GREEN
BAU
GREEN
Conclusion: green policy incurs
negligible long-term loss in GDP
- but has major impact on global warming and welfare
BAU
global warming
GREEN
welfare = y q exp(- 0.1 T2)
GDP
GREEN
BAU
employment level
global warming
Results are consistent with many previous
more detailed investigations (e.g.Stern report).
Results are consistent with many previous
more detailed investigations (e.g.Stern report).
But note: no cost-benefit analysis, no
discounting of future against present, just
common sense, first-order inference of
assumed investment decisions. Value
judgements (e.g. welfare) clearly stated.
Results are consistent with many previous
more detailed investigations (e.g. Stern report).
But note: no cost-benefit analysis, no
discounting of future against present, just
common sense, first-order inference of
assumed investment decisions. Value
judgements (e.g. welfare) clearly stated.
Interaction with the financial sector: A given
real-economy growth curve can correspond to
many different wealth curves of individual
actors in the financial sector
Financial sector
Actors:
household (workers, consumers)
r-firm (renewable-energy based)
k-firm (conventional-energy based)
r-investor (renewable-energy based)
k-investor (conventional-energy based)
government
central bank
State variables:
liquidity for all actors, plus assets for investors
The financial sector: a highly simplified projection of reality, but
already with 11 state variables and innumerable flows and interaction
parameters. The concept of “rational perfectly informed economic
actors” operating in an inherently stable system is clearly unrealistic
BAL
DEF
DEF
BAL
BAL
DEF
DEF
BAL
Two possible evolution paths of the financial sector for the realeconomy growth path R-BAU:
(1)
BAL (all budgets balanced) and
(2)
DEF deficit government budget. Welfare is enhanced, but the
government debt is sustainable only as long as creditors don’t balk.
How is it possible to have to two (or many more)
alternative evolution paths of the financial sector
for the same real-economy growth path?
Should economic systems not always adjust to a
unique equilibrium according to basic economics?
Textbook view of equilibrium established between
supply, demand and price (e.g. Samuelson and
Nordhaus, Abel and Bernanke)
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)
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)
General result: A Lorenz-type system of three 1st order differential equations can have many solutions:
• a damped periodic or monotonic transition to an
equilibrium point
• a stable convergence to a periodic attractor
• an unstable trajectory diverging to infinity
• a bounded, non-periodic chaotic trajectory
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)
General result: A Lorenz-type system of three 1st order differential equations can have many solutions:
• a damped periodic or monotonic 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
Example 1: Stable actor behavior assumed in the standard supplydemand diagram, yielding equilibrium in supply, demand & price.
Demand
Price
Demand = stabilizing feedback loop
Example 2: low-confidence consumer-producer behavior leading to
business cycles (see mental models of many classical economists).
Demand
Supply
Demand = destabilizing feedback
Example 3: Speculative demand and supply behavior in asset markets,
leading to a boom-and-bust limit cycle (e.g. the dot.com bubble)
Price
Demand
Price = destabilizing feedback
Other examples of non-equilibrium financial
imbalances:
Over-exposed banking sector through enhanced risk
taking of investors stimulated by innovative financial
products such CDSs (credit default swaps) and CDOs
(Colaterized Debt Obligations)
Other examples of non-equilibrium financial
imbalances:
Over-exposed banking sector through enhanced risk
taking of investors stimulated by innovative financial
products such CDSs (credit default swaps) and CDOs
(Colaterized Debt Obligations)
(claimed by proponents to distribute risk, but actually
enhances overall risk by encouraging investors to
take risks they would otherwise not have taken)
Other examples of non-equilibrium financial
imbalances:
Over-exposed banking sector through enhanced risk
taking of investors stimulated by innovative financial
products such CDSs (credit default swaps) and CDOs
(Colaterized Debt Obligations)
(claimed by proponents to distribute risk, but actually
enhances overall risk by encouraging investors to
take risks they would otherwise not have taken)
Persistent sovereign debt – as in the example shown
(e.g. Euro crisis)
Government policies that prevent these instabilities
is a pre-condition for creating the confidence in the
economy needed to encourage long-term
investments in the green transformation.
Thus:
financial stabilization
green transformation
Government policies that prevent these instabilities
is a pre-condition for creating the confidence in the
economy needed to encourage long-term
investments in the green transformation.
Thus:
financial stabilization
green transformation
but also
green transformation
financial stabilization
Government policies that prevent these instabilities
is a pre-condition for creating the confidence in the
economy needed to encourage long-term
investments in the green transformation.
Thus:
financial stabilization
green transformation
but also
green transformation
financial stabilization
Applied to our example: sovereign debt
BAL
SAV
DEF
REC
DEF
SAV
BAL
REC
REC
employment
REC
DEF
SAV, BAL
SAV
BAL
REC
REC
Alternative assumptions on impacts of a savings strategy to
re-adjust the DEF trajectory to the BAL trajectory:
SAV: assumes self-stabilizing forces of the free market
REC: predicts a major recession and unemployment
through unstable feedbacks
The data for Southern Europe clearly favours the
recession model over the stable-market-response
model.
Alternative to austerity model:
Keynes - combine savings (if at all) with government
sponsored investments in the real economy – for
example, in green technologies.
Comparison of the pure savings, recession creating,
strategy REC with a combined savings plus Keynes-type
enhanced green investment strategy GR-INV. Also shown:
the reference non-feedback green strategy GREEN
Conclusions:
• None of these examples are new, but in contrast to many
integrated assessment models in the literature, they reflect
the current political debate
Conclusions:
• None of these examples are new, but in contrast to many
integrated assessment models in the literature, they reflect
the current political debate
• The models are very simple, easy to understand and
communicate, and can be constructed in a few days
Conclusions:
• None of these examples are new, but in contrast to many
integrated assessment models in the literature, they reflect
the current political debate
• The models are very simple, easy to understand and
communicate, and can be constructed in a few days
• In contrast to their simplicity, they often reveal unexpected
dynamics through their stocks-and-flows time separation
of input and response
Conclusions:
• None of these examples are new, but in contrast to many
integrated assessment models in the literature, they reflect
the current political debate
• The models are very simple, easy to understand and
communicate, and can be constructed in a few days
• In contrast to their simplicity, they often reveal unexpected
dynamics through their stocks-and-flows time separation
of input and response
• The models should be constructed interactively with
stakeholder and policy-makers in a participatory mode
Conclusions:
• None of these examples are new, but in contrast to many
integrated assessment models in the literature, they reflect
the current political debate
• The models are very simple, easy to understand and
communicate, and can be constructed in a few days
• In contrast to their simplicity, they often reveal unexpected
dynamics through their stocks-and-flows time separation
of input and response
• The models should be constructed interactively with
stakeholder and policy-makers in a participatory mode
• The models need to be calibrated against data. The
examples given here were calibrated only against mean
growth “stylized facts”. Interaction parameters were
guessed
Thanks for listening
Discussion welcome