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Costing the Earth: Uncertainty and Climate Policy Nafees Meah Head of Science May 2010 Climate Change As ‘Hard’ Problem In Public Policy As a public policy issue, climate change is a classic example of a ‘wicked’ problem Notwithstanding the compelling scientific evidence, it is still contested It is the case that there is and will always be irreducible scientific uncertainty – we cannot do a controlled experiment on the planet Even if there is consensus on the science, that does not tell us what we ought to do: what are the trade-offs that the decision-makers need to consider? Outline Summary of the science of climate change The 2 degree target – AVOID Programme Key questions in the economics of climate change Economic modelling and cost-benefit analysis Stern Review and its critics Bottom up technical/economic models The task facing the decision maker Carbon Dioxide Concentrations In The Atmosphere Since The Beginning Of The Industrial Revolution MacKay (2009) Evidence that CO2 is Man Made Last decade has been the warmest since records began Observed Global Temperature Changes Not Explained by Natural Factors Alone Year to year range of modelled global temperatures Excluding human influence Climate models show the observed warming is only explained by including human effects through GHG emissions By 2100 Global Temperature is likely to be1.8 to 4oC Above 1990 Level The scale of warming depends on emissions: Low scenario 1.1 – 2.9oC Best estimate 1.8 – 4.0oC High scenario 2.4 – 6.4oC IPCC (2007) Projected temperatures – land and polar regions warm more than oceans IPCC (2007) IPCC Fourth Assessment Report 2007 “Warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice and rising global average sea level” – p2, IPCC Synthesis Report Temperature, Sea Level and Snow Cover • The Earth’s surface has warmed by 0.75C since 1900 • Sea levels have risen by 20cm since 1900 • Now: glaciers, snow cover and sea ice are all declining • Now: more heatwaves, droughts, extreme rain events and more intense cyclones IPCC (2007) Arctic Ocean September Ice Extent Impacts of climate change 0°C Food Water Global temperature change (relative to pre-industrial) 1°C 2°C 3°C 4°C 5°C Falling crop yields in many areas, particularly developing regions Falling yields in many Possible rising yields in developed regions some high latitude regions Small mountain glaciers disappear – water supplies threatened in several areas Significant decreases in water availability in many areas, including Mediterranean and Southern Africa Sea level rise threatens major cities Ecosystems Extensive Damage to Coral Reefs Rising number of species face extinction Extreme Rising intensity of storms, forest fires, droughts, flooding and heat waves Weather Events Risk of Abrupt and Increasing risk of dangerous feedbacks and Major Irreversible abrupt, large-scale shifts in the climate system Changes Cascade of uncertainty Emission scenario Atmospheric concentrations Climate sensitivity Climate change Range of Impacts Impacts may not increase linearly with warming Lenton (2007) Climate Sensitivity: Temperature Response of doubling [CO2] Q = F-λ∆T Where Q = energy balance, F = forcing and λ = feedback parameter At eqm Q=0 F = λ∆T For the special case of doubling CO2 F’ = λS Where S = Climate sensitivity AR4 concluded that best estimate of climate sensitivity was 30C with range of 2-4.50C (ca. 2SD) IPCC (2007) Climate feedbacks include Feedback Water vapour This is the most important. Water vapour is a powerful greenhouse gas. Cloud radiation Complex impact. Several processes involved. Sensitive to structure of clouds Ocean-circulation Plays large part in determining earth’s climate. Large heat capacity and moves heat around. Ice-albedo Ice and snow are a powerful reflector of solar radiation Climate feedbacks affect the sensitivity of the climate. Why a ‘fat’ tail? AVOID Programme and the 2 degree target 2 degree target agreed at Copenhagen Accord balances risks against technical and social feasibility in an informal way AVOID examined variations in: 1. The year of peak emissions (2014 to 2030) 2. The emission rates leading up to the peak (BAU) 3. The emissions reduction rate following peak emissions (1 to 5% per year) 4. The net long-term level of emissions (zero to high levels) Business as usual Policy scenario AVOID Programme: 2 degree trajectories AVOID uses a ‘tuned’ climate model (MAGICC) Global average temperature determined by cumulative emissions of GHGs (2.63TtCO2e 2000-2500) Approximates to the area under the curve Take home message is that to stabilise temperature at 2 degrees is going to be a huge challenge - we need to peak soon and STRONG decline thereafter GHG emission trajectories consistent with 2˚C increase in global average temperature at 2100 at a 50% probability level Action on Climate Change Key questions 1. How much will it cost to ‘stabilise’ the climate and avoid dangerous climate change? 2. Will the cost of avoiding dangerous climate change compete with other priorities such as development? What action do we take in the light of the scientific evidence for climate change? So if we applied the appropriate discount rate , then we might say that action would be justified on cost-benefit grounds if: NPV = Present Value (benefits) – Present Value (costs) > 0 Or for a range of alternative policy actions, choose the one with highest NPV Uncertainties in economic modelling of climate change This is a formidable challenge because: We do not and cannot know the precise benefits of policy action given the underlying uncertainty in the science We do not and cannot know what the future cost of the policy will be given the long time horizons Costs and benefits functions are likely to be highly non-linear - and we don’t know what they are If standard economic models are based on marginal changes, how do we account for irreversibilities? Given the very long time horizons, what is the appropriate discount rate to use? Economic models for climate policy Number of different kinds of economic models Much of the debate is about Integrated Assessment Models (IAMS) which seek to integrate science and the economic theory to optimise climate policy These are utility maximising models which seek to maximize, W, the social welfare, where W = ∫ exp(-ρt)U[c(t)]dt Where ρ is the rate of pure time preference, c(t) is the consumption at time t, and U is the utility function specifying how much utility is derived from a particular level of consumption Outputs from Integrated Assessment Models Reference case without impacts Global economic activity Reference case with impacts Benefits of policy Cost of policy Time Stern Review Uses PAGE 2002 Integrated Assessment Model Takes account of risk and uncertainty through Monte Carlo simulations on the climate sensitivity parameter, assumptions on risk aversion and equity Key finding Cost of trajectory consistent with 550ppm CO2e stabilisation averages 1% of global GDP per year (range -1% to 3.5%) Avoided damages would be 11% of GDP (range 2-27%) for Baseline climate and 14% (range 3-32%) for High climate This contrasts with other IAMs which suggest a higher level of cost and lower level of damage – DICE, MERGE, FUND Other models propose ‘policy ramp’ and modest rates of GHG reduction The critics Main criticism in the literature has been over the choice discount rate used by the Stern Review – should instead have used a market rate (i.e. 3 – 7%) In the Ramsay formula, the social discount rate is given by: Social discount rate = + ( x consumption/cap growth rate) Reflects pure rate of time preference (which Stern suggest should be 0) and risk of human extinction (which Stern select as 0.1). Elasticity of marginal utility of consumption (Stern suggest this is 1, which assumes society is moderately adverse to income inequality). Growth in per capita consumption varies over time and according to extent of climate change damages. For baseline climate scenario with market impacts only, the 5-95% range of timeaveraged growth is 1.08% - 1.14%. Therefore in Stern, discount rate = 0.1 + (1*(1.08 to 1.14%)) = 1.18 to 1.24% Discount rate have an important effect on the present value of climate change impacts Value of £100 over time using different discount rates £ 90.479 60.577 0.1% 0.5% 1.0% 5.0% 2.0% 10.0% 81.865 36.603 36.696 13.262 13.533 1.759 0.0000001 0.004 0.623 0.003 0 10 20 30 40 50 60 70 80 90 10 0 11 0 12 0 13 0 14 0 15 0 16 0 17 0 18 0 19 0 20 0 100 90 80 70 60 50 40 30 20 10 0 Years On Extreme Uncertainty of Extreme Climate Change – Martin Weitzman Implication of the fat tail of climate sensitivity Translating the pdf of climate sensitivity into confidence levels for temperature change as a function of GHG concentrations gives: So at 550 ppm there is a 10% of T >4.8 ˚C. This is disturbing and can’t be ignored in formal economic modelling. Damage function Thought experiment on the damage function, which often takes the quadratic form in IAMs of: C*(T) = 1/ 1+aT2 Where C*(T) is defined as the ‘welfare equivalent’ consumption as a fraction of what the consumption would be at T=0, and a=0.003 However, it is impossible to know a priori what the functional form should be for high temperatures What if we used quartic or exponential form then the estimated damages would be very different For a quartic exponential function, C*(T) = exp(-bT4), then at 10˚C C*(T) is 0.08% i.e. a catastrophic loss of ‘welfare equivalent’ consumption Technical feasibility models McKinsey Marginal Abatement Cost Curve – Bottom up estimates Generally optimistic – it can be done and at comparatively small cost! Choices facing the decision makers Is formalised cost-benefit analysis appropriate for climate change policy? If the answer is ‘no’ what other approach should we adopt? Given that a 2 ˚C has been adopted, should economic analysis focus on seeking the cost effective pathway Is a risk based approach formalising the ‘precautionary principle’ the appropriate way forward? Do we need more scientific knowledge on threshold temperatures for major discontinuities or catastrophe’s? What else is there any other approach that we should consider? Thank you for your attention Finally....