Download Escaping the Last Malthusian Trap

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Escaping the Last Malthusian Trap
A talk by
Eric Beinhocker
McKinsey Global
Institute
The Hague 26 May 2011
Copyright © 2011
McKinsey & Company, Inc. All rights reserved
The last
Malthusian trap
Today’s
discussion
Why neoclassical economics is the wrong tool for climate change
A complexity
economics view
of growth
Escaping the trap: creating a revolution in carbon productivity
The last
Malthusian
trap
Why neo‐classical economics is the wrong tool for climate change
A complexity
economics view
of growth
Escaping the trap: creating a revolution in carbon productivity
Some 2.5 million years of economic history (in brief)
World GDP per capita
1990 international dollars
World population
Thousands
7,000
7,000,000
6,000
6,000,000
5,000,000
5,000
4,000,000
4,000
3,000,000
3,000
2,000,000
2,000
1,000,000
1,000
0
-2,500,000 -2,000,000 -1,500,000 -1,000,000 -500,000
0
0
500,000
Year
Source: US Census Bureau Historical Estimates of World Population; Kremer (1993)
-2,500,000 -2,000,000 -1,500,000 -1,000,000 -500,000
0
500,000
Year
Source: DeLong (2005); data 2.5 million to 1 million B.C. extrapolated
The Malthusian trap (circa 1000 BC to 1800 AD)
Malthus in a nutshell
A
Wages
Subsistence
C
B
Population
Stagnant incomes
Global income per person (1800 AD = 1)
Rising population
Thousands
12
900
10
800
700
600
500
400
300
200
100
8
6
4
Malthusian trap
2
0
1000 BC 500 BC
0
500
1000
1500 1800 AD
0
Source: Clark (2007)
500
1000
1500
1800 AD
Source: US Census Bureau Historical Estimates of World Population; Kremer (1993)
…then a third of the world escaped
Until 1800 Malthus ruled…
Global income per person (indexed 1800 AD = 1)
12
10
8
The
Great
Divergence
6
4
Industrial Revolution
2
Malthusian trap
0
1000 BC
Source: Clark (2007)
500 BC
0
500
1000
1500
2000 AD
… but with an unsustainable growth model …
Changes in greenhouse gases from ice core and modern data
400
350
Radiative forcing (Wm2)
CO2 (ppm)
300
250
10,000
5000
Time (before 2005)
Source: IPCC AR4 WG1 (2007)
0
… and another third of the world are poised to escape
Annual household disposable income Thousands RMB, real 2000
Number of households (millions)
2005
2015
2025
CHINA
200 and above
1.0
3.4
8.2
100‐199
1.6 5.7 19.0 40‐99
112.6
8.8
71.4
25‐39
Less than 25
107.5
214.1
75.7
54.1
74.2
57.8
Thousands RMB, real 2000
INDIA
1000 and above
1.2
500‐999
2.4 200‐499
10.9
90‐199
Less than 90
Source: McKinsey Global Institute
3.3
9.5
5.5
33.1
55.1
91.3
101.1
94.9
106.0
74.1
93.1
49.9
We face our final Malthusian trap
Peak at 550 ppm, long-term
stabilization 550 ppm
Annual emissions implied by Copenhagen Accord pledges (Gt CO2e)
Peak at 510 ppm, long-term
stabilization 450 ppm
70
Peak at 480 ppm, long-term
stabilization 400 ppm
65
Low range of pledges
60
55
50
45
40
35
30
Probability of
temperature
increase
under 2˚C
Expected
temperature
increase
15-30%
3.0˚C
40-60%
2.0˚C
70-85%
1.8˚C
25
20
15
10
5
0
2005
High range of pledges
2010
2015
2020
2025
2030
2035
2040
2045
2050
Source: “Taking Stock – Emissions Levels Implied by the Copenhagen Accord,” Project Catalyst, February 2010.
What we need to do and questions for economics
The world’s to‐do list
Questions for economics
Re‐do the Industrial Revolution, creating a sustainable economic system
How did the first Industrial Revolution occur? How might we create a new one?
Transition to a low‐
carbon economy with minimal impact on welfare and growth, especially for the developing world
What are the interactions between welfare, growth and de‐carbonisation? How do we assess the trade‐
offs?
Drive the above with policy – conduct global social engineering on an unprecedented scale
What are the leverage points? How do we avoid unintended consequences? Preserve individual freedom?
Unfortunately
traditional
economics
ill‐equipped
to answer
these questions
The last
Malthusian trap
A complexity
economics view
of growth
Why
neoclassical economics is the wrong tool for climate change
Escaping the trap: creating a revolution in carbon productivity
Neoclassical economics cannot explain key characteristics of the economy
The economy is viewed as an equilibrium system
The economy is viewed as an equilibrium system
but such a system cannot grow explosively, create novelty, nor spontaneously self‐organize And such a system cannot just ‘crash’ – as ours has
The accidental history of equilibrium in economics
Neoclassical failure #1: Theory of growth
Y (t)
=
Output
F (K (t) , A (t)
Capital
Cannot explain the Industrial Revolution
Source: Bolow (1956), Romer (1996), Nelson (1996), Daly (1999)
*
Knowledge
L (t) )
Labour
No connection with the physical world
Neoclassical failure #2: Human behaviour
Theory doesn’t match real world behaviour
Exponential discounting
Hyperbolic
discounting
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
Source: Axtel and McRae (2006a), (2006b)
Hyperbolic answer
Cost = $1 million to $4 million
per life saved
Neoclassical failure #3: Cost‐benefit analysis
“Discount rate!”
‘Discount rate!’
Prof. William Nordhaus
Lord (Nicholas) Stern
• Climate uncertainty has fat tails with power law scaling
• Cost‐benefit analysis typically assumes away the tails
• Would pay a lot to avoid catastrophe, e.g. Weitzman’s ‘Dismal Theorem’
Source: Stein (2006), Nordhaus (2007), Weitzman (2007), Barker (2008)
Neoclassical failure #4: Time symmetry
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
Source: Arrow and Fischer (1974), Frederich, Lowenstein, Donohue (2002), Dietz (2007)
The last
Malthusian trap
A complexity economics
view of
growth
Why neo‐classical economics is the wrong tool for climate change
Escaping the trap: creating a revolution in carbon productivity
A different explanation – the economy is a ‘complex adaptive system’
Complex
Adaptive
System
Many interacting agents and organizations of agents
Designs and strategies evolve over time
Macro patterns emerge from micro behavior
A paradigm shift
TRADITIONAL ECONOMICS
COMPLEXITY ECONOMICS
Dynamics
Economies are closed, static, linear systems in equilibrium
Economies are open, dynamic, non‐linear systems far from equilibrium
Agents
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
Networks
Assume agents only interact indirectly through market mechanisms
Explicitly accounts for agent‐to‐agent interactions and relationships
Emergence
Treats micro and macroeconomics as separate disciplines
Macro patterns emerge from micro behaviors and interactions
Evolution
No endogenous mechanism for creating novelty or growth in order and complexity
Evolutionary process creates novelty and growing order and complexity over time
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
Evolution is a search algorithm for ‘fit order’
VARIATION
SELECTION
AMPLIFICATION
Create a variety of experiments
Select designs that are ‘fit’
Amplify fit designs, de‐amplify unfit designs
REPEAT
Evolutionary search through ‘deductive‐tinkering’
Technologies evolve
Economic evolution occurs in three ‘design spaces’
Physical technologies
Business plans
Social technologies
Business plan evolution works on three levels
Business A
Business B ???
Markets
Business C
Business D ???
Option A
Organizations
Option B
Option C
Option D
Option A
Individuals
Option B ???
Option C
Option D
What would economic evolution look like?
Non-linear wealth
creation
Increasing variety and
complexity
Spontaneous selforganization
But we cannot avoid the Second Law of Thermodynamics – economic order does not come for free
The last
Malthusian trap
A complexity
economics view
of growth
Escaping the trap: creating a revolution
in carbon productivity
Why neoclassical economics is the wrong tool for climate change
Industrial revolutions are productivity revolutions
Physical technologies
Business plans
Social technologies
Rapid evolution (e.g. “Cambrian explosion”)
Rapid rise in productivity
How do we evolve higher ‘carbon productivity’?
Kaya identity
F
=
Anthropogenic
(CO2 emissions)
p
*
GDP per
capita
Population
1
Carbon productivity ~=
Source: Beinhocker, et. al. (2008)
+
e * f
g
*
e
*
Energy
intensity of GDP
Non‐energy emissions and other GHGs
f
Carbon intensity
of energy
≈
$GDP
CO2e
To grow the economy and reduce emissions, carbon productivity must rise 10x to $7,300 per tonne by 2050
World GDP, US$ tn (real 2000)
150
125
100
75
50
25
0
146
+3.1% per year
41
2000 2010 2020 2030 2040 2050
Global emissions, tCO2e
60
55
‐2.4% 50
per year
40
30
20
10
0
2,000
7,300
10x
740
0
2000 2010 2020 2030 2040 2050
20
2000 2010 2020 2030 2040 2050
Source: Beinhocker, et. al. (2008)
Carbon productivity, US$ (real 2000)/tCO2e
Carbon productivity = 8,000
GDP
6,000
Emissions
+5.6% /
4,000
per year
If emissions are capped, higher economic growth requires higher carbon productivity
Carbon productivity required to reach 20 Gt CO2e by 2050
US$ (real 2000)/tCO2e
16,000
Annual real growth, %
14,000
Carbon
productivity
required
‐2
870
‐1
1,300
0
2,000
1
3,100
6,000
2
4,700
4,000
3
7,000
4
10,500
5
15,800
12,000
10,000
Base case forecast
8,000
2,000
0
‐2
‐1
0
1
2
GDP growth required to hit 20Gt at BAU carbon productivity growth
Source: Global Insight; IPCC; McKinsey analysis
3
4
5
Forecast GDP growth rate 2008‐2050, percent
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 people
Source: McKinsey analysis
A carbon productivity revolution is required three times faster than the industrial revolution
Index Year 0 = 1
10
Carbon productivity growth required
2008–50
8
US labor productivity growth 1830–1955
6
4
2
0
0
10
20
30
40
50
60
70
80
90
100
110
120
130
Years
Source: Beinhocker, et. al. (2008)
But no‐one today is close to required carbon productivity
Carbon productivity 2007, 177 countries, all GHGs excluding LULUCF
Adjusted for purchasing power parity, 2050 target = $13,300 GDP/tonne
Carbon productivity
US$ 000 (PPP)/tCO2e
5.5
Saint Kitts and Nevis
5.0
Switzerland
Mauritius
4.5
Bangladesh
4.0
Sweden
Sri Lanka
Norway
Average carbon productivity
3.5
France
3.0
United Kingdom
Japan Austria
2.5
Singapore
Italy
Pakistan
Turkey
2.0
Indonesia
Germany
Mexico
1.5
India
Brazil
South Korea
Iran
Canada
United States
Australia
Venezuela Saudi Arabia
1.0
Nigeria
0.5
Liberia
G8+5
Qatar
South Africa
Russia
0
0
5
Turkmenistan
China
10
15
20
25
30
35
Prosperity
GDP per capita US$ 000 (PPP)
Source: WRI CAIT; UNFCCC; Global Insight; McKinsey analysis
40
45
50
Carbon productivity has increased over time, but not nearly quickly enough
* 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: IEA, CDIAC, OECD, EPA, CEC, World Bank, US Bureau of Economic Analysis, McKinsey analysis
Some hypotheses for climate policy
• Climate change is far riskier then conventional models lead us to believe
– Fat tails, irreversibility, path dependence, etc.
• Carbon prices may be necessary but not sufficient
– Effectiveness of price signals in noisy, complex markets
– Industrial revolution not triggered by spike in labour costs – broad socioeconomic phenomenon
• Need to broadly change the “fitness function” of the economy
– Regulation, standards (e.g. consumer and worker safety laws early 20th c.)
– Behavior, social norms (e.g. slavery, smoking)
• Policy and politics for homo realitius vs. homo economicus
Some hypotheses for climate policy (cont.)
• Social technology innovation just as important as physical technology
– Institutions (e.g. green banks?)
– Laws (e.g. carbon fiduciary responsibility?)
– Information (e.g. climate risk disclosure? GDP measures?)
• Must accelerate evolutionary innovation process
–
–
–
–
Variation – dramatically increase shots on goal
Selection – bias fitness function toward low carbon
Amplification – capital and talent flows to low carbon
Creating green innovation clusters
• International cooperation needs to emerge bottom‐
up rather than top‐down
– Evolution of trade regime vs. “Rio Dream” and Copenhagen
Summary
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!
‘We cannot solve problems by using the same kind of thinking
we used when we created them.’
ALBERT EINSTEIN
Unless we truly understand the system we are dealing with we will fail
We cannot afford to fail
But if we can more deeply understand that system, we just might succeed