A talk by Escaping McKinsey Beinhocker Global the Last ... · of GDP. Carbon intensity. of ......
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Escaping the Last Malthusian Trap A talk by Eric Beinhocker McKinsey Global Institute Copyright © 2008 McKinsey & Company, Inc. All rights reserved Complex systems, climate change and economic growth Oxford 27 November 2008
Transcript of A talk by Escaping McKinsey Beinhocker Global the Last ... · of GDP. Carbon intensity. of ......
Escaping the Last Malthusian Trap
A talk byEric BeinhockerMcKinsey Global
Institute
Copyright © 2008McKinsey & Company, Inc.
All rights reserved
Complex systems,
climate change and
economic growth
Oxford27 November 2008
‘The ideas of economists and political philosophers, both when they are right and when they are wrong, are more powerful than is commonly understood. Indeed, the world is ruled by little else.’
JOHN MAYNARD KEYNES
‘We cannot solve problems by using the same kind of thinking
we used when we created them.’ALBERT EINSTEIN
A complexityeconomics view
of growth
Why neo‐classical
economics is the
wrong tool for
climate change
Escaping the
trap: creating
a revolution
in carbon
productivity
The lastMalthusian trap
Today’sdiscussion
A complexityeconomics view
of growth
Why neo‐classical
economics is the
wrong tool for
climate change
Escaping the
trap: creating
a revolution
in carbon
productivity
The lastMalthusian
trap
Some 2.5 million years of economic history (in brief)
Source: US Census Bureau Historical Estimates of
World Population; Kremer (1993)
World populationThousands
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
-2,500,000 -2,000,000 -1,500,000 -1,000,000 -500,000 0 500,000
Year
World GDP per capita1990 international dollars
Source: DeLong
(2005); data 2.5 million to 1 million B.C.
extrapolated
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
-2,500,000 -2,000,000 -1,500,000 -1,000,000 -500,000 0 500,000
Year
The Malthusian trap (circa 1000 BC to 1800 AD)
Rising population
Thousands
Source: US Census Bureau Historical Estimates
of World Population; Kremer (1993)
900
800
600500400300
700
200100
0 500 1000 1500 1800 AD1800 AD
Stagnant incomes
Global income per person (1800 AD = 1)
Source: Clark (2007)
12
10
8
6
4
2
1000 BC 500 BC 0 500 1000 1500
Malthusian trap
0
Population
A
B
CSubsistence
Wages
Malthus in a nutshell
Then a third of the world escaped …
12
10
8
6
4
2
0
1000 BC 500 BC 0 500 1000 1500 2000 AD
Great Divergence
Industrial Revolution
Malthusian trap
Source: Clark (2007)
Global income per person (1800 AD = 1)
Source: IPCC
AR4
WG1
(2007)
… but with an unsustainable growth model …
10,000 5000 0
Time (before 2005)
Changes in
greenhouse
gases from
ice core and
modern data
350
300
250
CO2
(ppm) Radiative
forcing (Wm2)
400
Source: McKinsey Global Institute
Annual household disposable income
Number of households (millions)
… and another third of the world are poised to escape
100‐199
40‐99
25‐39
Less than 25
200 and above
Thousands RMB, real 2000 2005
1.0
8.8
71.4
107.5
1.6
1.2
10.9
91.3
101.1
2.4
2015
3.4
112.6
75.7
74.2
5.7
3.3
55.1
106.0
74.1
5.5
2025
8.2
214.1
54.1
57.8
19.0
9.5
94.9
93.1
49.9
33.1500‐999
200‐499
90‐199
Less than 90
1000 and above
CHINA
INDIA
Thousands RMB, real 2000
Humanity’s next, and perhaps last, Malthusian trap
Projection of surface temperatures
Source: IPCC
AR4
WG1
(2007)
What we need to do, and where economics can help
The world’s to‐do list
Re‐do the Industrial
Revolution, creating a
sustainable economic
system
Transition to a low‐
carbon economy with
minimal impact on
welfare and growth,
especially for the
developing world
Drive the above with
policy –
conduct global
social engineering on
an unprecedented
scale
Questions for economics
How did the first Industrial
Revolution occur? How
might we create a new
one?
What are the interactions
between welfare, growth
and de‐carbonisation? How
do we assess the trade‐
offs?
What are the leverage
points? How do we avoid
unintended consequences?
A complexityeconomics view
of growth
Escaping the
trap: creating
a revolution
in carbon
productivity
The lastMalthusian trap
Whyneo‐classical
economics is the wrong tool for climate
change
Neoclassical economics cannot explain key characteristics of the economy
The economy is viewed as an equilibrium system
The economy is viewed as an equilibrium systembut such a system cannot grow explosively, create
novelty, nor spontaneously self‐organize
The accidental history of equilibrium in economics
Neoclassical failure #1: Theory of growth
Source: Bolow
(1956), Romer
(1996), Nelson (1996), Daly (1999)
Cannot explain the Industrial Revolution No connection with the physical world
Y (t)
=
Output Capital Knowledge Labour
F (K (t)
, A (t)
L (t)
)*
Neoclassical failure #2: Cost‐benefit analysis
Source: Stein (2006), Nordhaus
(2007), Weitzman (2007), Barker (2008)
Weitzman’s ‘Dismal Theorem’:
For any given n
and k, lim
E [M/λ] = + ∞
λ→∞
Uncertainty about climate has fat tails with power law scaling
Cost benefit analysis doesn’t work
Would pay a lot to avoid catastrophe
Prof. William Nordhaus Lord (Nicholas) Stern
“Discount rate!”‘Discount rate!’
Neoclassical failure #3: Human behaviour
Source: Axtell and McRae (2006a), (2006b)
Example
Society spends $1 billion today to save 10 lives per year in perpetuity
Social cost of capital equals 5%
Exponential answer
Cost = $4.76 million
per life saved
Hyperbolic answer
Cost = $1 million to $4 million
per life saved
Theory doesn’t match real world behaviour
Exponential discounting
Hyperbolicdiscounting
Neoclassical failure #4: Time symmetry
Source: Arrow and Fischer (1974), Frederich, Lowenstein, Donohue (2002), Dietz (2007)
Cost‐benefit analysis and discounting assume path independence and time symmetry
Samuelson :
M R S (τ, τ’) independent of C τ’’
But climate effects are highly path dependent and largely irreversible on human time scales
Why neo‐classical
economics is the
wrong tool for
climate change
Escaping the
trap: creating
a revolution
in carbon
productivity
The lastMalthusian trap
A complexity economics
view ofgrowth
Adaptive
Designs and strategies
evolve over time
System
Macro patterns emerge
from micro behavior
Complex
Many interacting agents and
organizations of agents
A different explanation – the economy is a ‘complex adaptive system’
Traditional economics versus complexity economics
A paradigm shift
TRADITIONAL ECONOMICS COMPLEXITY ECONOMICS
Economies are closed, static, linear
systems in equilibrium
Economies are open, dynamic,
non‐linear systems far from equilibrium
Dynamics
Homogeneous agents•
Only use rational deduction•
Make no mistakes, have no biases•
No need to learn
Heterogeneous agents•
Mix deductive/inductive decisions•
Subject to errors and biases•
Learn and adapt over time
Agents
Treats micro and macroeconomics as
separate disciplines
Macro patterns emerge from micro
behaviors and interactions
Emergence
Evolutionary process creates
novelty and growing order and
complexity over time
No endogenous mechanism for
creating novelty or growth in order
and complexity
Evolution
Explicitly accounts for agent‐to‐agent
interactions and relationships
Assume agents only interact indirectly
through market mechanisms
Networks
Source: Beinhocker (2006)
“Economic activity is fundamentally an order creating process” (Georgescu-Roegen)
Complex economic systems use energy to decrease local entropy, create ‘fit order’
Energy inputs
CaloriesFossil
fuels
Ordered outputs:Goods and services(entropy locally decreased)
Disordered outputs:Waste products, heat, gases
(entropy universally increased)
Agents interacting
Evolution is a search algorithm for ‘fit order’
Create a variety of experiments
VARIATION
Select designs that are ‘fit’
SELECTIONAmplify fit designs,
de‐amplify unfit designs
AMPLIFICATION
REPEAT
Long history of evolution in economics (and vice versa)
Problems• Driven by a biological metaphor for the economy • Not built on a general computational view of evolution
A general computational model of evolution
Design space Schema
1
0
1
1
0
0
1
0
0
0
Source: E.g. Holland (1975), Mitchell (1996), etc.
Schema reader‐builder
1011001000
Environment
A computational model of economic evolution
Plan
A
Plan BPlan
C
Plan D Plan
E
Design space Schema reader‐builderSchema
Source: Beinhocker (2006)
Economic evolution occurs in three ‘design spaces’
Physical
technologies
Social
technologies
Business
plans
Source: Beinhocker (2006)
Evolutionary search through ‘deductive‐tinkering’
Source: Beinhocker (2006)
Technologies evolve
Business plans are a form of ‘design’
too
StrategyHigh‐end microprocessorsIntegrated chip setsChips/components
Social technologiesInnovation processesDirect salesCompetitive culture
Physical technologiesSemiconductor designTestingFabrication
StrategyLarge selection book superstoreSuburban malls, urban centresEnjoyable browsing experience
Social technologiesOrganized by brand/geographyValuesLogistic systems
Physical technologiesStore designComputersWarehousing
Source: Beinhocker (2006)
Business A
Business B
Business C
Business D
Markets
Option A
Option B
Option C
Option D
Organizations
Business plan evolution works on three levels
Option A
Option B
Option C
Option D
Individuals ???
???
???
Source: Beinhocker (2006)
What would economic evolution look like?
Increasing variety and complexity
Non-linear wealthcreation
Spontaneous self-organization
Source: Beinhocker (2006)
But we cannot avoid the Second Law of Thermodynamics – order does not come for free
A complexityeconomics view
of growth
Why neo‐classical
economics is the
wrong tool for
climate change
The lastMalthusian trap
Escaping the trap: creating
a revolutionin carbon
productivity
Solow wasn’t wrong – just incomplete
Y (t)
=
Output Capital Knowledge Labour
F (K (t)
, A (t)
L (t)
)*
Physical
technologies
Social
technologies
Business
plans
Solow wasn’t wrong – just incomplete
Physical
technologies
Social
technologies
Business
plans
Y (t)
=
Output Capital Knowledge Labour
F (K (t)
, A (t)
L (t)
, A (t)
R (t)
)*
Physical
technologies
Social
technologies
Business
plans
*
Knowledge Resources
How do we evolve ‘carbon productivity’?
Kaya
identity
F p g e f= * * *
Anthropogenic(CO2
emissions)Population GDP
percapita
Energyintensity of GDP
Carbon intensityof energy
Carbon productivity1
Non‐energy emissions
and emissions from
other GHGs
$GDP
CO2
ee f*+ ≈=~
Source: Beinhocker, et. al. (2008)
0255075
100125150
2000 2010 2020 2030 2040 2050
0102030405060
2000 2010 2020 2030 2040 2050
To grow the economy and
reduce emissions, carbon productivity must rise 10x to $7,300 per tonne by 2050
Global emissions, tCO2
e
Carbon productivity =
GDPEmissions
World GDP, US$ tn
(real 2000)
0
2,000
4,000
6,000
8,000
2000 2010 2020 2030 2040 2050
10x
Carbon productivity, US$ (real 2000)/tCO2
e7,300
55
20
146
41
+5.6%
per year
+3.1%
per year
/
‐2.4%
per year
740
Source: Beinhocker, et. al. (2008)
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
0 5 10 15 20 25 30 35 40 45 50
South Korea
Saudi ArabiaAustralia
Indonesia
Iran
VenezuelaNigeria
Liberia
Turkmenistan
Qatar
G8+5
Norway
France United Kingdom
Japan
Italy
GermanyMexicoUnited States
CanadaBrazilIndia
Austria
South AfricaRussia
Saint Kitts and NevisSwitzerlandMauritius
China
Sweden
Sri Lanka
Singapore
TurkeyPakistan
Bangladesh
Varied relationship between carbon productivity and prosperity; no‐one is close to target carbon productivity
Carbon
productivity000 US$(PPP)/tCO2e
Average carbon
productivity
Source: McKinsey Global Institute
Carbon productivity 2007, 177 countries, all GHGs excluding LULUCF
ProsperityGDP per capita000 US$(PPP)
Adjusted for purchasing
power parity, 2050 target = $13,300
GDP/tonne
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
‐2 ‐1 0 1 2 3 4 5
Source: McKinsey Global Institute
Forecast GDP growth rate
2008‐2050, percent
Carbon productivity required to reach 20 Gt
CO2
e by 2050
US$ (real 2000)/tCO2
e
Base case forecast
GDP growth required to hit 20Gt
at
BAU
carbon productivity growth
If emissions are capped, higher economic growth requires higher carbon productivity
Annual real growth, %
Carbonproductivityrequired
‐2
‐1
0
1
2
3
4
5
870
1,300
2,000
3,100
4,700
7,000
10,500
15,800
If we capped emissions and lived at today’s carbon productivity, there is not much we could ‘afford’
* Emissions from land use change not included** Based on 10Gt/year sustainable emissions and future population of 10 billion peopleSource: McKinsey Climate Change Special Initiative
Carbon productivity has gradually increased over time
* 5‐year running average. Emissions data includes CO2
from fossil fuels and cement, with projections
for CO2
from land use changes and five non‐CO2
gases (CH4, N2O, HFCs, PFCs, and SF6) Source: McKinsey Global Institute
0
2
4
6
8
10
0 10 20 30 40 50 60 70 80 90 100 110 120 130Years
Index Year 0 = 1
But a carbon productivity revolution is required three times faster than the industrial revolution
Carbon productivity growth required2008–50
US labor productivity
growth 1830–1955
Source: Beinhocker, et. al. (2008)
How do we create a carbon productivity revolution on par with Industrial
Revolution – at three times the speed?
How do we activate the evolutionary processes of the economy to do so?
‐
Physical technologies?
‐
Social technologies?
‐
Business plans?
Can we use policy to change the evolutionary fitness function of
the
economy to include carbon?
Some questions and some hypotheses
A carbon price is necessary but far from sufficient‐
Industrial revolution did not happen because labour was expensive‐
Need mutual reinforcement between price signals and other selection
pressures (e.g., policy, social norms, competition)
Innovation in social technologies will be critical‐
New regulatory frameworks‐
New market structures‐
New business forms‐
New international institutions
We need to think more broadly than current policy debates, e.g.
‐
Female education in developing countries
‐
Green technology innovation clusters
‐
Catalysing infrastructure investments‐
Changing cultural norms
Some questions
Summary: Escaping the Last Malthusian Trap
Industrial Revolution enabled a third of the population to escape the
Malthusian trap of poverty, hardship and disease
But it created our next, and possibly last, Malthusian trap –
climate
change
Escaping that trap will require a low‐carbon revolution on the scale of
the Industrial Revolution, but at three times the speed
Economic revolutions are profoundly disequilibrium phenomena
– not explained well by neoclassical theory
A complex systems view helps us understand the evolutionary
processes that drive discontinuous innovation and growth
Climate policies should activate and leverage economic evolutionary
processes –
policymakers need new ideas, there is much work to do!
