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

2. 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: creaAng a revoluAon in carbon producAvity

3. The last Malthusian trap Why neo-‐classical economics is the wrong tool for climate change A complexity economics view of growth Escaping the trap: creaAng a revoluAon in carbon producAvity

4. Some 2.5 million years of economic history (in brief) World GDP per capita 1990 internaHonal dollars World populaAon 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 EsHmates of World PopulaHon; 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

5. The Malthusian trap (circa 1000 BC to 1800 AD) Malthus in a nutshell A Wages Subsistence C B PopulaHon 12 Stagnant incomes Global income per person (1800 AD = 1) 10 8 6 4 Malthusian trap 2 0 1000 BC 500 BC 0 500 1000 1500 1800 AD 900 Rising populaAon Thousands 800 700 600 500 400 300 200 100 0 Source: Clark (2007) 500 1000 1500 1800 AD Source: US Census Bureau Historical EsHmates of World PopulaHon; Kremer (1993)

6. UnHl 1800 Malthus …then a third of the world escaped ruled… Global income per person (indexed 1800 AD = 1) 12 10 8 The Great Divergence 6 4 Industrial RevoluHon 2 Malthusian trap 0 1000 BC Source: Clark (2007) 500 BC 0 500 1000 1500 2000 AD

7. … but with an unsustainable growth model … Changes in greenhouse gases from ice core and modern data 400 350 RadiaHve forcing (Wm2) CO2 (ppm) 300 250 10,000 5000 Time (before 2005) Source: IPCC AR4 WG1 (2007) 0

8. … 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 25 214.1 75.7 74.2 107.5 54.1 57.8 Thousands RMB, real 2000 INDIA 1000 and above 1.2 500-‐999 10.9 90-‐199 Less than 90 Source: McKinsey Global InsHtute 9.5 5.5 2.4 200-‐499 3.3 33.1 55.1 91.3 101.1 106.0 74.1 94.9 93.1 49.9

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 Probability of temperature increase under 2˚C 30 2.0˚C 70-85% 35 3.0˚C 40-60% 40 Expected temperature increase 15-30% 45 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.

10. What we need to do and quesHons for economics 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 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? Unfortunately tradiAonal economics ill-‐equipped to answer these quesAons

11. The last Malthusian trap 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

12. Neoclassical economics cannot explain key characterisHcs of the economy

13. The economy is viewed as an equilibrium system

14. The economy is viewed as an equilibrium system but such a system cannot grow explosively, create novelty, nor spontaneously self-‐organize

15. And such a system cannot just ‘crash’ – as ours has

16. The accidental history of equilibrium in economics

17. Neoclassical failure #1: Theory of growth Y (t) = Output Cannot explain the Industrial RevoluHon F (K (t) , A (t) * L (t) ) Capital Knowledge Labour No connecHon with the physical world Source: Bolow (1956), Romer (1996), Nelson (1996), Daly (1999)

18. Neoclassical failure #2: Human behaviour Theory doesn’t match real world behaviour ExponenHal discounHng Hyperbolic discounHng 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 Source: Axtel and McRae (2006a), (2006b) Hyperbolic answer Cost = $1 million to $4 million per life saved

19. Neoclassical failure #3: Cost-‐beneﬁt analysis “Discount ate!’ ‘Discount rrate!” 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)

20. Neoclassical failure #4: Time symmetry 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 Source: Arrow and Fischer (1974), Frederich, Lowenstein, Donohue (2002), Dietz (2007)

21. The last Malthusian trap A complexity economics view of growth Why neo-‐classical economics is the wrong tool for climate change Escaping the trap: creaAng a revoluAon in carbon producAvity

22. A diﬀerent explanaHon – the economy is a ‘complex adapHve system’ Complex AdapHve System Many interacHng agents and organizaHons of agents Designs and strategies evolve over Hme Macro parerns emerge from micro behavior

23. A paradigm shis TRADITIONAL ECONOMICS COMPLEXITY ECONOMICS Dynamics Economies are closed, staHc, linear systems in equilibrium Economies are open, dynamic, non-‐linear systems far from equilibrium Agents 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 Networks Assume agents only interact indirectly through market mechanisms Explicitly accounts for agent-‐to-‐agent interacHons and relaHonships Emergence Treats micro and macroeconomics as separate disciplines Macro parerns emerge from micro behaviors and interacHons EvoluHon No endogenous mechanism for creaHng novelty or growth in order and complexity EvoluHonary process creates novelty and growing order and complexity over Hme

24. 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

25. EvoluHon 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

26. EvoluHonary search through ‘deducHve-‐Hnkering’

27. Technologies evolve

28. Economic evoluAon occurs in three ‘design spaces’ Physical technologies Business plans Social technologies

29. What would economic evoluHon look like? Non-linear wealth creation Increasing variety and complexity Spontaneous selforganization

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

31. Understanding the “mother of all complex systems” ???

32. The last Malthusian trap A complexity economics view of growth Escaping the trap: creaAng a revoluAon in carbon producAvity Why neoclassical economics is the wrong tool for climate change

33. Industrial revoluAons are producAvity revoluAons Physical technologies Business plans Social technologies Rapid evoluAon (e.g. “Cambrian explosion”) Rapid rise in producAvity

34. How do we evolve higher ‘carbon producHvity’? Kaya idenAty F = Anthropogenic (CO2 emissions) Carbon producHvity ~ = Source: Beinhocker, et. al. (2008) p * GDP per capita PopulaHon 1 e * f g + * e * Energy intensity of GDP Non-‐energy emissions and other GHGs f Carbon intensity of energy ≈ $GDP CO2e

35. To grow the economy and reduce emissions, carbon producHvity 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 producAvity, US$ (real 2000)/tCO2e Carbon producHvity = 8,000 GDP 6,000 Emissions +5.6% 4,000 / per year

36. If emissions are capped, higher economic growth requires higher carbon producHvity Carbon producAvity required to reach 20 Gt CO2e by 2050 US$ (real 2000)/tCO2e 16,000 Annual real growth, % 14,000 -‐2 -‐1 0 1 2 3 4 5 12,000 10,000 Base case forecast 8,000 6,000 4,000 2,000 Carbon producAvity required 870 1,300 2,000 3,100 4,700 7,000 10,500 15,800 0 -‐2 -‐1 0 1 2 GDP growth required to hit 20Gt at BAU carbon producHvity growth Source: Global Insight; IPCC; McKinsey analysis 3 4 5 Forecast GDP growth rate 2008-‐2050, percent Without carbon producHvity growth need to shrink economy by >-‐2% per annum

37. 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

38. A carbon producHvity revoluHon is required three Hmes faster than the industrial revoluHon Index Year 0 = 1 10 Carbon producHvity growth required 2008–50 8 US labor producHvity 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)

39. But no-‐one today is close to required carbon producHvity Carbon producAvity 2007, 177 countries, all GHGs excluding LULUCF Adjusted for purchasing power parity, 2050 target = $13,300 GDP/tonne Carbon producHvity US$ 000 (PPP)/ tCO2e 5.5 5.0 Saint Kirs and Nevis Switzerland MauriHus 4.5 Bangladesh 4.0 Sweden Sri Lanka Norway Average carbon producHvity 3.5 France 3.0 2.5 Japan Austria 2.0 Indonesia Turkey Germany Mexico Brazil South Korea Iran Australia Venezuela Saudi Arabia 1.0 Nigeria 0.5 Liberia 0 Canada United States Qatar South Africa Russia 0 5 Turkmenistan China 10 15 G8+5 Singapore Italy Pakistan 1.5 India United Kingdom 20 25 30 35 Prosperity GDP per capita US$ 000 (PPP) Source: WRI CAIT; UNFCCC; Global Insight; McKinsey analysis 40 45 50

40. 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

41. Technology will help – but we need to accelerate innovaHon and buy Hme Source: Farmer, et. al. (2013)

42. 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

43. 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

44. 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!

45. ‘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

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

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