Escaping the Last Malthusian Trap: a presentation to IIED by Eric Beinhocker

Escaping the Last

Malthusian Trap

A talk by Eric Beinhocker INET Oxford

Copyright © 2014 Eric Beinhocker

All rights reserved

London 6 February 2014

iied

A complexity economics view

of growth

Why neoclassical economics is the wrong tool for climate change

Escaping the trap: creaAng a revoluAon in carbon

producAvity

The last Malthusian trap

Today’s discussion


of growth

Why neo-‐classical economics is the wrong tool for climate change


producAvity

The last Malthusian

trap

Some 2.5 million years of economic history (in brief)

Source: US Census Bureau Historical EsHmates of World PopulaHon; Kremer (1993)

World populaAon Thousands

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 capita 1990 internaHonal 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 populaAon Thousands

Source: US Census Bureau Historical EsHmates of World PopulaHon; Kremer (1993)

900 800

600 500 400 300

700

200 100

0 500 1000 1500 1800 AD 1800 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

PopulaHon

A

B C

Subsistence

Wages

Malthus in a nutshell

UnHl 1800 Malthus ruled…

12

10

8

6

4

2

0

1000 BC 500 BC 0 500 1000 1500 2000 AD

Malthusian trap

Source: Clark (2007)

Global income per person (indexed 1800 AD = 1)

The Great

Divergence

Industrial RevoluHon

…then a third of the world escaped

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) RadiaHve forcing (Wm2)

400

Source: McKinsey Global InsHtute

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

33.1 500-‐999

200-‐499

90-‐199

Less than 90

1000 and above

CHINA

INDIA

Thousands RMB, real 2000

Expected temperature increase

3.0˚C

2.0˚C

1.8˚C

Probability of temperature increase under 2˚C

15-30%

40-60%

70-85%

Peak at 550 ppm, long-term stabilization 550 ppm Peak at 510 ppm, long-term stabilization 450 ppm Peak at 480 ppm, long-term stabilization 400 ppm

Source: “Taking Stock – Emissions Levels Implied by the Copenhagen Accord,” Project Catalyst, February 2010.

High range of pledges

Low range of pledges

We face our final Malthusian trap Annual emissions implied by Copenhagen Accord pledges (Gt CO2e)

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

What we need to do

The world’s to-‐do list Re-‐do the Industrial RevoluHon, creaHng a sustainable economic system TransiHon 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

Unfortunately tradiAonal economics ill-‐equipped to answer these quesAons

QuesAons for economics How did the first Industrial RevoluHon occur? How might we create a new one? What are the interacHons between welfare, growth and de-‐carbonisaHon? How do we assess the trade-‐offs? What are the leverage points? How do we avoid unintended consequences? Preserve individual freedom?

and quesHons for economics


of growth Escaping the trap: creaAng a revoluAon in carbon

producAvity



Neoclassical economics cannot explain key characterisHcs 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

Source: Bolow (1956), Romer (1996), Nelson (1996), Daly (1999)

Cannot explain the Industrial RevoluHon

No connecHon with the physical world

Y (t) =

Output Capital Knowledge Labour

F (K (t) , A (t) L (t) ) *

Neoclassical failure #2: Human behaviour

Source: Axtel and McRae (2006a), (2006b)

Example Society spends $1 billion today to save 10 lives per year in perpetuity

Social cost of capital equals 5%

ExponenAal 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

ExponenHal discounHng

Hyperbolic discounHng

Neoclassical failure #3: Cost-‐benefit analysis

Source: Stein (2006), Nordhaus (2007), Weitzman (2007), Barker (2008)

• 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’

Prof. William Nordhaus Lord (Nicholas) Stern

“Discount rate!” ‘Discount rate!’

Neoclassical failure #4: Time symmetry

Source: Arrow and Fischer (1974), Frederich, Lowenstein, Donohue (2002), Dietz (2007)

Cost-‐benefit analysis and discounAng assume path independence and Ame symmetry

Samuelson : M R S (τ, τ’) independent of C τ’’

But climate effects are highly path dependent and largely irreversible on human Ame scales

Why neo-‐classical economics is the wrong tool for climate change


producAvity


A complexity economics view of growth

AdapHve

Designs and strategies evolve over Hme

System

Macro parerns emerge from micro behavior

Complex

Many interacHng agents and organizaHons of agents

A different explanaHon – the economy is a ‘complex adapHve system’

A paradigm shis

TRADITIONAL ECONOMICS COMPLEXITY ECONOMICS

Economies are closed, staHc, linear systems in equilibrium

Economies are open, dynamic, non-‐linear systems far from equilibrium

Dynamics

Homogeneous agents •  Only use raHonal deducHon •  Make no mistakes, have no biases •  No need to learn

Heterogeneous agents • Mix deducHve/inducHve decisions • Subject to errors and biases • Learn and adapt over Hme

Agents

Treats micro and macroeconomics as separate disciplines

Macro parerns emerge from micro behaviors and interacHons

Emergence

EvoluHonary process creates novelty and growing order and complexity over Hme

No endogenous mechanism for creaHng novelty or growth in order and complexity

EvoluHon

Explicitly accounts for agent-‐to-‐agent interacHons and relaHonships

Assume agents only interact indirectly through market mechanisms

Networks

Long history of evoluHon in economics (and vice versa)

Problems •  Driven by a biological metaphor for the economy •  Not built on a general computaHonal view of evoluHon

EvoluHon is a search algorithm for ‘fit order’

Create a variety of experiments

VARIATION Select designs that are ‘fit’

SELECTION Amplify fit designs,

de-‐amplify unfit designs

AMPLIFICATION

REPEAT

EvoluHonary search through ‘deducHve-‐Hnkering’

Technologies evolve

Economic evoluAon occurs in three ‘design spaces’

Physical technologies

Social technologies

Business plans

What would economic evoluHon look like?

Increasing variety and complexity

Non-linear wealth creation

Spontaneous self- organization

But we cannot avoid the Second Law of Thermodynamics – economic order does not come for free

Understanding the “mother of all complex systems”

???


of growth




producAvity

Industrial revoluAons are producAvity revoluAons

Physical technologies

Social technologies

Business plans

Rapid evoluAon (e.g. “Cambrian explosion”)

Rapid rise in producAvity

How do we evolve higher ‘carbon producHvity’?

Kaya idenAty

F p g e f = * * *

Anthropogenic (CO2 emissions)

PopulaHon GDP per capita

Energy intensity of GDP

Carbon intensity of energy

Carbon producHvity 1

Non-‐energy emissions and other GHGs

$GDP

CO2e e 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 producHvity must rise 10x to $7,300 per tonne by 2050

Global emissions, tCO2e

Carbon producHvity =

GDP Emissions

World GDP, US$ tn (real 2000)

0

2,000

4,000

6,000

8,000

2000 2010 2020 2030 2040 2050

10x

Carbon producAvity, US$ (real 2000)/tCO2e

7,300

55

20

146

41

+5.6% per year

+3.1% per year

/

-‐2.4% per year

740


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: Global Insight; IPCC; McKinsey analysis

Forecast GDP growth rate 2008-‐2050, percent

Carbon producAvity required to reach 20 Gt CO2e by 2050 US$ (real 2000)/tCO2e

Base case forecast

GDP growth required to hit 20Gt at BAU carbon producHvity growth

If emissions are capped, higher economic growth requires higher carbon producHvity

Annual real growth, %

Carbon producAvity required

-‐2 -‐1 0 1 2 3 4 5

870 1,300 2,000 3,100 4,700 7,000 10,500 15,800

Without carbon producHvity growth need to shrink economy by >-‐2% per annum

If we capped emissions and lived at today’s carbon producHvity, there is not much we could ‘afford’

* Emissions from land use change not included ** Based on 10Gt/year sustainable emissions and future populaHon of 10 billion people Source: McKinsey analysis

0

2

4

6

8

10

0 10 20 30 40 50 60 70 80 90 100 110 120 130Years

Index Year 0 = 1

A carbon producHvity revoluHon is required three Hmes faster than the industrial revoluHon

Carbon producHvity growth required 2008–50

US labor producHvity growth 1830–1955


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 Arabia Australia

Indonesia

Iran

Venezuela Nigeria

Liberia

Turkmenistan

Qatar

G8+5

Norway

France United Kingdom Japan

Italy

Germany Mexico United States

Canada Brazil India

Austria

South Africa Russia

Saint Kirs and Nevis Switzerland MauriHus

China

Sweden

Sri Lanka

Singapore

Turkey Pakistan

Bangladesh

But no-‐one today is close to required carbon producHvity

Carbon producHvity US$ 000 (PPP)/tCO2e

Average carbon producHvity

Source: WRI CAIT; UNFCCC; Global Insight; McKinsey analysis

Carbon producAvity 2007, 177 countries, all GHGs excluding LULUCF

Prosperity GDP per capita US$ 000 (PPP)

Adjusted for purchasing power parity, 2050 target = $13,300 GDP/tonne

Carbon producHvity has increased over Hme, but not nearly quickly enough

* 5-‐year running average. Emissions data includes CO2 from fossil fuels and cement, with projecHons 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

Technology will help – but we need to accelerate innovaHon and buy Hme

Source: Farmer, et. al. (2013)

Some hypotheses for climate policy

•  Climate change is far riskier then convenHonal models lead us to believe –  Fat tails, irreversibility, path dependence, etc.

•  Carbon prices may be necessary but not sufficient –  EffecHveness of price signals in noisy, complex markets –  Industrial revoluHon not triggered by spike in labour

costs alone – broad socioeconomic phenomenon •  Need to broadly change the “fitness funcHon” of the

economy –  RegulaHon, standards (e.g. consumer and worker safety

laws early 20th c.) –  Behaviour, social norms (e.g. slavery, smoking)

•  Policy and poliHcs for homo realitus vs. homo economicus -  The revenge of poliHcal economy and human behaviour

Some hypotheses for climate policy (cont.)

•  Social technology innovaHon just as important as physical technology –  InsHtuHons (e.g. green banks?) –  Laws (e.g. carbon fiduciary responsibility?) –  InformaHon (e.g. climate risk disclosure? GDP measures?)

•  Must accelerate evoluHonary innovaHon process –  VariaHon – dramaHcally increase shots on goal –  SelecHon – bias fitness funcHon toward low carbon –  AmplificaHon – capital and talent flows to low carbon –  CreaHng green innovaHon clusters

•  We need to buy Hme for tech progress -  Role of natural gas as bridge?

•  InternaHonal cooperaHon needs to emerge borom-‐up rather than top-‐down –  EvoluHon of trade regime vs. “Rio Dream” and Copenhagen

Summary

Industrial RevoluHon enabled a third of the populaHon 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 revoluHon on the scale of the Industrial RevoluHon, but at three Hmes the speed Economic revoluHons are profoundly disequilibrium phenomena – not explained well by neoclassical theory A complex systems view helps us understand the evoluHonary processes that drive disconHnuous innovaHon and growth Climate policies should acHvate and leverage economic evoluHonary 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

Escaping the Last Malthusian Trap: a presentation to IIED by Eric Beinhocker

Economy & Finance

Transcript of Escaping the Last Malthusian Trap: a presentation to IIED by Eric Beinhocker