What to Do? Does Science have a Role? Klaus Hasselmann Max-Planck-Institut for Meteorology, Hamburg,...

What to Do? Does Science have a Role?Klaus Hasselmann Max-Planck-Institut for Meteorology, Hamburg, European Climate Forum

Heraeus Seminar Energy and Climate

A Physics Perspective onEnergy Supply and Climate ChangePrediction, Mitigation and Adaptation

26 - 29 May 2008, Physikzentrum Bad Honnef,

Discussion topicsInterconnections:

mitigationadaptation

policy

Climate change

What to Do? Does Science have a Role?

Hasselmann and Barker, Climatic Change, in press:• IPCC Working Group 3 (in contrast to WG1)

has had very little political influence• The influential Stern Report, for example,

developed its political recommendations independently

• Needed is a new UN “Climate Policy Panel” that interacts continuously with

policymakers• But to be effective a Climate Policy Panel will need to develop a new suite of Integrated Assessment (coupled climate-socio- economic) models

No longer disputed:• Climate change is real• The costs of unregulated climate change greatly

exceed the costs of mitigation• There exist various technologies that, in combination, could limit global warming to acceptable levels (< 20C above pre-industrial)• The estimated costs (-1% to 4% of GDP), although appearing high today (a few trillion $), are quite affordable in the long term (a delay in long-term global growth, if at all, of a few months to a year)

Strongly disputed: • How best transform our present unsustainable global economic system based on fossil fuels into a sustainable carbon-free system?

• Do scientists have the right tools to provide useful signals that will be heard in the noisy debate over conflicting stakeholder interests, divergent national goals and the stresses of globalization?

Answers:Traditional (main stream) economists: Yes, the available standard general-

equilibrium macro-economic models are fine. Physics-based economists: No, we need a new generation of dynamic multi-agent dynamic models.

Overview

• Available technologies for closing the wedge between the BAU (Business as Usual) emissions trajectory and the sustainable emissions goal

• Proposed strategies for closing the wedge

• Traditional versus multi-agent economic models - with three examples of the latter:

1) Ginti’s model of the “invisible hand”

2) A Multi-Actor Dynamic Integrated Assessment Model (MADIAM) of climate policies

3) A climate-policy evolution model

• Conclusions

Business as Usual

sustainability path

Energy efficiency: zero mean cost

High fruits (solar, and unproven or controversial options: CCS, nuclear, fusion, … )

Low fruits renewables

Filling the wedge between projected BAU emissions and a sustainable emissions path (T< 20C)

Overview







• Conclusions

Basic climate policy instruments:1.Whip: internalization of external costs (carbon

price)2.Carrot: subsidies (societal investments that

are unprofitable for individual investors – bridging the difference between low discount rates appropriate for public investments and high discount rates demanded by private investors)

3.Regulatory framework: for sectors that are not amenable or sufficiently responsive to market-based instruments (automobile emissions, building insulation, etc.)

4.Technical and financial transfer from rich to poor countries

fossil energy low-fuits renewables

high-fruits renewables (solar energy)

energy costs

climate damage costs

1. whipfossil energy

(Kyoto, carbon price: internalize external costs)

low-fruits renewables

energy costs



remain non-competitive

fossil energy1. whip

energy costs


high-fuits renewables (solar energy)

low-cost renewables become competetive



problem: limited abatement capacity!



energy costs




remain non-competitive


both become competitive!

2. carrot(Post-Kyoto: subsidies)

price reduction



energy costs





Basic climate policy instruments:1.Whip: internalization of external costs (carbon

price)2.Carrot: subsidies (societal investments that

are unprofitable for individual investors – bridging the difference between low discount rates appropriate for public investments and high discount rates demanded by private investors)

3.Regulatory framework: for sectors that are not amenable or responsive to market-based instruments (automobile emissions, building insulation, etc.)

4.Technical and financial transfer from rich to poor countries

2000 2050 2100

2

8

6

4

TC/yr

World

USA

EU+Japan

China

India

USA

EU+ Japan

China India

Sustainability GOAL

World

BAU per capita emissions (speculative)

2000 2050 2100

2

8

6

4

TC/yr

World

USA

EU+Japan

China

India

USA

EU+Japan

China Indien

USA

EU+ Japan

China India

Convergence and contraction paths

World Sustainability GOAL

Achievable only with significant N-S transfer of investments and technology

Challenge for global climate policy: arrive at an equitable international agreement structured on a combination on the four basic instruments:

1. carbon price2. subsidies3. regulatory framework4. technical and financial transfer from developed to emerging and developing countries

Task for science: Which type of coupled climate-socio-economic (IA) models should one apply to assess the impact of alternative climate policies?

Overview







• Conclusions

climate system

economic system

climate policy

ghg emissions

impacts on production,welfare,…

regulatory instruments

scenario predictions

Single-actor “invisible hand“ establishes market equilibrium

Traditional coupled climate-economic (integrated assessment-IA) model

Shortcomings of economic equilibrium models:

• exclusion of important dynamical processes (technological change, structural unemployment, rich-poor inequalities, business cycles, financial instabilities, globalization adjustments, ……)

• inadequate representation of divergent interests between different actors (“tragedy of the commons” conflict between individual goals and societal responsibilities – in particular: climate , actor-dependent discount factors, business-labor relations, trade agreements,,....)

• inadequate treatment of equity issues (burden sharing, rich-poor inequalities, conflict potential, terrorism, …)

climate system

economic system

climate policy

ghg emissions

impacts on production,welfare,…

regulatory instruments

scenario predictions

Multi-actor integrated assessment model

Multi-actor dynamic evolution, market response actor dependent

Actors: governments, voting public, media, CEOs, consumers, firms, workers, …

Historical interjection: Four stages in the development of economic theory (a physicist’s view).

1. Verbalisation (story telling)_ Adam Smith (1723-1790), David Ricardo (1772-1823) Karl Marx (1818-1883), John Maynard Keynes (1883-1946) Joseph Schumpeter (1883-1950), Milton Friedman (1912-2006),...

2. Optimization (marginalization) Leon Walras(1834-1910), Kenneth Arrow (1921- ) , Gerard Debreu (1921-2004), Lionell McKenzie (1919-),...

3. Game theory (interactions between a few players) John von Neumann (1903-1958), John F. Nash (1928-),...

4. Simulation (continuous dynamics, multi-agent) Meadows et al, Limits to Growth (1972); Epstein and Axtell, Growing Artifical Societies (1996) (Sugarscape); John Sterman, Business Dynamics (2000); Eric Beinhocker, The Origin of Wealth (2006)....

Historical interjection: Four stages in the development of economic theory (a physicist’s view).

1. Verbalisation (story telling)_ Adam Smith (1723-1790), David Ricardo (1772-1823) Karl Marx (1818-1883), John Maynard Keynes (1883-1946) Joseph Schumpeter (1883-1950), Milton Friedman (1912-2006),...

2. Optimization (marginalization) Leon Walras(1834-1910), Kenneth Arrow (1921- ) , Gerard Debreu (1921-2004), Lionell McKenzie (1919-),...

3. Game theory (interactions between a few players) John von Neumann (1903-1958), John F. Nash (1928-),...

4. Simulation (continuous dynamics, multi-agent) Meadows et al, Limits to Growth (1972); Epstein and Axtell, Growing Artifical Societies (1996) (Sugarscape); John Sterman, Business Dynamics (2000); Eric Beinhocker, The Origin of Wealth (2006)....

quantification

Economic theory is in the process of a radical paradigm shift from

“traditional economics”

based on a combination of verbalized descriptive concepts, economic equilibrium analyses and basic game theoretical elements to

“complexity economics”

based on computer simulations of multi-agent interactions in a dynamically evolving system.

This raises two questions:

1) The emergence problem; How do macro-economic structures emerge from the complex micro-economic interactions of many agents pursuing different goals?

2) The parametrization problem: How can one represent the dynamics of macro-economic systems in terms of the interactions between a small set of aggregated agents?

And in the present context: can one apply such models to assess the impacts of climate policies on the global socio-economic system?


1) The emergence problem; How do macro-economic structures emerge from the complex micro-economic interactions of a multitude of agents pursuing different goals?



Overview







• Conclusions

Herbert Gintis, The dynamics of general equilibrium, The Economics Journal, 117, 1280-1309 (Oct. 2007)(Simulations kindly provided by Steffen Fuerst, PIK)

Question: How does the “invisible hand” of Adam Smith lead to an equilibrium price of goods in which supply and demand are exactly balanced? (The basic credo of economic equilibrium theory)

Embarrassing counter-example, Scarf (1960): three agents offering and demanding three different goods result in a periodic non-equilibrium price attractor.

Gintis’ approach: a large number of producers and consumers interacting individually with each other.

Agent type 1: 140 Firms (on average): - produce 10 different goods, - set (individual) prices, - take up credit (from a “central authority“), - pay taxes, - imitate successful competitors, - can go bankrupt (to be replaced by newcomers)Agent type 2: 5250 workers/consumers/shareholders: - work or become unemployed (receiving wages or unemployment benefits) - consume goods - buy sharesAgent type 3: one “central authority“: - imposes and distributes taxes - creates and lends money/ accepts savings

Results:• Establishment of a statistical equilibrium, with random

fluctuations about the mean state - although all trades were based on local information only: a nice confirmation of the “invisible hand“

• But: Are the actor strategies realistic? No business cycles, recessions, financial instabilities, technological change, structural unemployment, social inequalities,....

• Clearly, we have some way to go to construct reasonably realistic multi-actor economic models!

• Nevertheless: a historical aside on the rate of progress: - Adam Smith: “The Wealth of Nations“: 1776 ; - Herbert Gintis: The Economic Journal, October, 2007


1) The emergence problem; How do macro-economic structures emerge from the complex micro-economic interactions of a multitude of agents pursuing different goals?



Overview







• Conclusions

Example 2: A Multi-Actor Dynamic Integrated Assessment Model (MADIAM)Hoos, G, V. Barth and K. Hasselmann, Ecological Journal , 54, 306-327, 2005Attempt to capture the emergent structures of a macro-economic system in terms of the interactions of a few aggregated actors (firms, households, governments, banks) pursuing different goals – and to apply this to climate policy assessment.

MADIAM: Multi-Actor Dynamic Integrated Assessment Model

NICCS: Non-linear Impulse response coupled Carbon cycle-Climate System

MADEM: Multi-Actor Dynamic Economic Model

CO2 emissions

Climate change : space-time fields of temperature, precipitation, cloud cover, sea level, etc

ClimatePolicy + Economics

MADEM (Multi-Actor Dynamic Economic Model) Actors Goals Firms Maximize profits Workers Maximize wages Governments Maximize GDP Banks Stabilize money supplyAll actors strive to achieve individual goals while jointly committed to avoiding dangerous climate change (classical “tragedy of the commons” conflict)

MADEM mathematical structure:state variables x = (xi)control variables z = (zi) = Ci(x)

dxi/dt = Fi (x,z) = Gi (x)

10 state variables xi : physical capital, productivity, employed workers, wages, household and firm savings, government budget deficit, energy intensity, carbon intensity, fossil resources

( Ci(x) define the actors’ control strategies)

Prognostic equations:

Control parameters:Firms:

Investments in physical capital Investments in productivity

Investments in emissions reduction Credit uptake/Savings

Consumers/Wage earners: Wage negotiations Credit uptake/Savings

Consumer preferences (climate friendly or climate adverse goods)

Governments: Emissions tax Recycled taxes (in consumption or subsidies in renewables)

Principal driver of economic growth: Investments in technological change

Firms strive to escape the erosion of profits through the pressures of competition (increasing wage levels, diffusion of technological advantages) by continually investing in technology and know how (human capital).Structural unemployment arises when it is more profitable for firms to invest in productivity (technology - with associated reduction in employment) than in physical capital (Basic idea expressed by classical economists of all persuasions - Adam Smith, Karl Marx, Joseph Schumpeter, ... – but ignored in traditional economic equlibrium models)

BAU / MM (Moderate Mitigation)

ITC (Induced Technological Change)

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

wms

(a) (b)

mitigation measures: w: weak, m: moderate, s: strong

Estimates of the costs of climate change mitigation: 1 % of GDP

Consistent with: IPCC 4th Assessment Report; macro-economic model intercomparison, The Energy Journal, Special Issue, 2006; the Stern Review, 2006).Range of other estimates: -1 % to + 4% of GDP

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!

2 -

1 -

3 -

4 -

BSP (log Skala)

Is climate change mitigation affordable?

1% BAU growth

Overview







• Conclusions

Third example: A multi-actor model of the evolution and implementation of climate policy Scenarios from 1970 (first serious warnings of climate

change) to 2100 (end of IPCC scenarios)Simplified MADIAM, extended to include • interaction of scientific knowledge, interest

groups, media, etc in climate policy development and implementation

• identification of critical policy parameters (e.g. whip and carrot policies)

IPCC

NGOs

media

extreme events vested interests

public

scientificknowledgeresearch

Climate polic iespolicy

conceptspolicy information

subsidies carrot

carbon price whiplow fruits

technology

solar technology

low fruitsinvestments

solar investments

emissionsGDP

carbonintensity

policy implementation

globalwarmingwarming rate

T1 T2

glatt 1

A Vensim model of the climate-policy obstacle course: from scientific knowledge (1) to reduced global warming (8)

(1)

(2) (3)

(4)(5)

(7)

(6)

(8)

IPCC

NGOs

media


public




subsidies carrot


technology

solar technology


solar investments

emissionsGDP

carbonintensity



T1 T2

glatt 1

A Vensim model of the climate-policy obstacle course: from scientific knowledge (1) to reduced global warming (8)

(1)

(2) (3)(4)

(5)(7)

(6)

(8)

Three stages: 1: scientific knowledge (1 ) to policy information (2) 2: Information (2) to mitigation technology (5) 3: mitigation technology (5) to global warming (8)

IPCC

NGOs

media


public




Stage 1: From scientific knowledge (1) (IPCC) to policy information (2) via the media, vested interests, extreme events, etc.

(1)

(2)

Policy information4

2

01970 1990 2010 2030 2050 2070 2090

Time

policy information : reference 2 SK

IPCC4

2

01970 1990 2010 2030 2050 2070 2090

Time (Year)

IPCC : reference 2 SK

Media4

01970 2000 2030 2060 2090

Time (Year)

media : reference 2 SK

Vested interests0

-41970 2000 2030 2060 2090

Time (Year)

vested interests : reference 2 SK

extreme events10

01970 2000 2030 2060 2090

Time (Year)

extreme events : reference 2 SK

(1) (2)

Step 1: From scientific knowledge (1) (IPCC) to policy information (2) via the media, vested interests, extreme events, etc.

policyconcepts

policy information

subsidies carrot


technology

solar technology


solar investments


Stage 2: The delay cascade: Information (2) to mitigation technology (5)

(2)(3)

(4)

(5)

Step 2: The delay cascade: Information (2) to mitigation technology (5)

(2) (3)

(4)(5) Policy implementation0.4

0.2

01970 2000 2030 2060 2090

Time (Year)

policy implementation : Test 23 Mar WGDP

Low fruits/solar technology20 Year*WGDP20 Year*WGDP

0 Year*WGDP0 Year*WGDP

1970 2010 2050 2090Time (Year)

low fruits technology : Test 23 Mar Year*WGDPsolar technology : Test 23 Mar Year*WGDP

Policy information4

2

01970 1990 2010 2030 2050 2070 2090

Time

policy information : Test 23 Mar SK

Policy concepts0.4

0.2

01970 2000 2030 2060 2090

Time (Year)

policy concepts : Test 23 Mar WGDP

low fruitstechnology

solar technology


solar investments

emissionsGDP

carbonintensity


Stage 3: From mitigation technology (5) to global warming (8)

(5) (6)

(7)

(8)

Low fruits/solar technology20 Year*WGDP20 Year*WGDP

0 Year*WGDP0 Year*WGDP

1970 2000 2030 2060 2090Time (Year)

low fruits technology : run Alcala Year*WGDPsolar technology : run Alcala Year*WGDP

Emissions40 GTC/Year40 GTC/Year

20 GTC/Year20 GTC/Year

0 GTC/Year0 GTC/Year

1970 1990 2010 2030 2050 2070 2090Time

BAU emissions : run Alcala GTC/Yearemissions : run Alcala GTC/Year

global warming4 degC4 degC

0 degC0 degC

1970 1990 2010 2030 2050 2070 2090Time (Year)

BAU global warming : run Alcala degCglobal warming : run Alcala degC

GDP8 WGDP8 WGDP

0 WGDP0 WGDP

1970 1990 2010 2030 2050 2070 2090Time (Year)

BAU GDP : run Alcala WGDPGDP : run Alcala WGDP

------2 degree limit --------------------------------

BAU

BAUBAUpolicy

policy

policy

solar

low fruits

Step 3: From mitigation technology (5) to global warming (8)

(7)

(5)

(8)

What are the critical parameters that govern the effectiveness of climate policy?• the whip factor: the emissions cap in a cap and trade system• the carrot factor: the subsidies level, in

particular for solar energy• the delay factor: time delay between policy concepts and implementationSee Vensim sensitivity simulation….

Overview







• Conclusions

Consider again the two basic questions raised by the paradigm shift from traditional economic equilibrium theory to “complexity economics”:

1) The emergence problem; How do macro-economic structures emerge from the complex micro-economic interactions of many agents pursuing different goals?


Proponents of the paradigm shift have focused on the first problem:

the emergence problem:

e.g. Eric Beinhocker, 2006:

“The ultimate accomplishment of Complexity Economics [is to take us] from theories of agents, networks and evolution all the way up to the macro-economic patterns we see in real-world economies. Such a comprehensive theory does not yet exist, but we can begin to see glimmers of hope….”

However, if we wish to close the present gap between useful scientific advice and climate policy, we need also to urgently address the second problem:

the parametrization problem

However, if we wish to close the present gap between useful scientific advice and climate policy, we need also to urgently address the second problem:

the parametrization problem

I hope I have provided you also with a “glimmer of hope”

Thank you for listening

What to Do? Does Science have a Role? Klaus Hasselmann Max-Planck-Institut for Meteorology, Hamburg,...

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