«The choice of discounting rate in decision making regarding climate change»

Transcription

1 «The choice of discounting rate in decision making regarding climate change» Presentation at the final conference Economics of Prevention Measures Addressing Coastal Hazards EcosHaz Ευτύχιος Σαρτζετάκης 02/12/2016

2 Ι. Introduction: Climate change CO 2 Concentration 05/2016: 405ppm Facts: - Over the last 2 centuries average temperature on earth has increased more than can be explained by the natural climate cycles. - There is an agreement that the causes of climate change are anthropogenic. - Climate change coincides with industrial revolution and is evolving at an accelerating rate over the last 50 years. - The use of fossil fuels as the main energy source that fueled industrial revolution is the main source of the problem, since GHGs (mainly CO 2 ) enhance the greenhouse effect. 2 / 26

3 Ι. Introduction: Climate change CO 2 concentration 2016: 405ppm 280 Δ= Using ice-core drilling in Antarctica (a process that started in the 1970s) we get data for CO 2 and CH 4 concentrations for a period of 800,000 years. During this period up to industrial revolution, CO 2 concentration remained within the ppm range, while CH 4 concentration never exceeded 750 ppb. The last 150 years CO 2 concentration has increased dramatically and has already exceeded the critical value of 400 ppm (404,86ppm τέλη Μαρτίου 2016) while CH 4 concentration is above ppb. In carbon equivalent (CO 2 e), greenhouse gases concentration already exceed 450 ppm. 3 / 26

4 Ι. Introduction: Climate change Δ=85,15 404,83 319,68 συγκεντρώσεις CO Data accessed at NOAA ESRL DATA: ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt Given the difficulty to grasp changes over such long period, allow me to make the argument a bit more personal in an attempt to improve understanding. Since I have already witnessed an increase of 85,15ppm, it s very likely that during my lifetime I will have contributed to an increase in CO 2 concentration by 100ppm, an amount greater than the max variance during the last years, while the mean change/1.000y (for the y) never exceeded 25ppm!!!!!!!!!!!!!!!!!!!!! 4 / 26

5 Ι. Introduction: Climate change All forecasts converge on the prediction that CO 2 concentration will soon exceed the double of the historical average (more than 450ppm). The impacts of this dramatic increase in greenhouse gases concentrations cannot be estimated with certainty. The best scientific forecasts available are those of the Intergovernmental Panel on Climate Change (IPCC) and they estimate that doubling GHGs concentration will result in an increase of average temperature on earth s surface which «it is likely to be in the range o C with a best estimate of 3 o C, and is very unlikely to be less than 1.5 o C. Values substantially higher than 4.5 o C cannot be excluded, but agreement of models with observations is not as good for those values.» Intergovernmental Panel on Climate Change (IPCC-AR4 2007) 5 / 26

6 Ι. Introduction: Climate change Key observed and projected climate change and impacts for the main regions 2016 EEA Report on Climate change, impacts and vulnerability in Europe Climate-related extreme events accounted for almost 400 billion Euro of economic losses in the EEA member countries over the period This is 82% of the total reported losses due to extreme events over this period, whereby geophysical extreme events such as earthquakes and volcano eruptions are responsible for the remaining 18%. The economic losses appear to have increased in recent decades, but this increase is due primarily to better reporting and to socio-economic trends, such as changes in population, human activities and infrastructure in hazard prone areas. Future climate change will affect the frequency and intensity of climate related extremes and associated losses differently across Europe, but most climate related hazards are projected to increase across Europe. 6 / 26

7 Ι. Introduction: Climate change Changes in the average maximum temperature during the summer between the periods (α) and και (β) and (Climate Change Impacts Study Committee, BofG, Chapter 1) 7 / 26

8 ΙΙ. Mitigation and Adaptation Realizing the importance of the problem, there are two types of actions that should Adaptation: be undertaken: design of actions, (1) but Mitigation also actions targeting the long-term behavioral changes, for ameliorating climate reduction of greenhouse gas emissions (GHG)and (2) Adaptation actions targeting at change impacts ameliorating the non-reversible impacts of climate change in the short and medium run. those bearing Mitigation the costs may not Adaptation be the same. Renewable energy sources Energy conservation New improved building codes Efficiency improvements in the use of fuels CCS Improving resilience of infrastructure Water management Health programs (cooling centers, smog alerts, diseases, etc) Support of vulnerable groups Developing adaptation strategies specific to business sectors In November 2011, Canada announced a $148.8 million investment over five years ( ) for the continued support of federal adaptation programs. Both adaptation and mitigation cost money, but on different timescales and Much of the warming, once realized, is irreversible for centuries. Today s emissions will be a legacy for many centuries. «White paper - Adapting to climate change: towards a European framework for action.» Commission of the European Communities COM(2009) 147. Education - awareness: It is extremely important that people understand the problem so that they change behavior Mitigation is a collective goal and can only be achieved through some type of an international environmental agreement among all countries, such as the one signed (but not yet ratified) at Paris. Unilateral action, by one or a small number of countries will only have a small effect. Adaptation, to the unavoidable affects of climate change, depends on local effects and should be undertaken by governments, which should develop Adaptation Strategies at the national and local levels. 8 / 26

9 ΙΙ. Mitigation and Adaptation Mitigation Economic Development Adaptation Mitigation and adaptation strategies should be designed in a way that promotes development (not only economic growth) creating opportunities and benefits for all society members, especially the most vulnerable groups. Economic development should be designed in order to cater the needs of mitigation and adaptation to climate change. As any such big change it creates risks but offers opportunities as well. With respect to mitigation, there are some, but not enough, steps taken towards the transition to a low carbon economy. Most of these actions are at the local or regional level. With respect to adaptation, there are many investments in flood risk reduction, agriculture, tourism and other sectors. These investments could create economic opportunities the benefits of which should be spread to the society through proper design. 9 / 26

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11 ΙΙ. Mitigation and Adaptation Geoengineering Resources 2020 with Thomas C. Schelling 2005 Nobel Laureate in Economic Sciences Distinguished University Professor, University of Maryland "Geoengineering: Time for Some Gentle Experimentation" Thursday, December 13, with-thomas-c-schelling.aspx 11 / 26

12 ΙΙΙ. Climate change Economics Despite the efforts to design mitigation and adaptation strategies in a way to promote economic development, it is certain that the necessary investments will require large amount of resources which will be taken away from the production of consumption goods and services in the short to medium term. The main concern of climate change economics is the estimation of the optimal degree in the reduction of consumption in order to mitigate climate change. SCC Economists agree that the full social cost of a ton of carbon exceeds its private cost (as determined by the market). The problem is the magnitude of the additional cost, which should be added to its market value through proper policies, in order to correct the market failure. This additional cost is termed social cost of carbon (SCC). There are important developments in the quest of determining the SCC. A variety of extremely complex models has been developed, attempting to integrate climate and economic parameters and using the most advanced methods and tools available in all scientific areas. 12 / 26

13 ΙΙΙ. Climate change Economics The Figure shows the effect of the increase in average temperature on global GDP in 2100 (ratio of global damages to global GDP) based on the main three models: DICE, FUND and PAGE. Elizabeth Kopits (2014) «The Social Cost of Carbon in Federal Rulemaking», National Center for Environmental Economics, U.S. EPA (U.S. Government Interagency Working Group on SCC) The Stern Report urges the global community to undertake immediate action. The Report estimates that damages will be between 5 and 10% (and the most recent amendments up to 15%) while the cost of the necessary mitigation actions will be between 0,3 and 0,7% (Sterner and Persson) of global GDP. 13 / 26

14 ΙΙΙ. Climate change Economics 14 / 26 Percentage change of Greek GDP as a result of climate change, by economic sector. Most damages are expected in the agricultural and tourism sectors, while substantial damages are expected in the coastal areas and in water supply (Climate Change Impacts Study Committee, BofG, Chapter 2)

15 ΙV. CC models: Basic structure SCC Effect of GHG emissions on the concentration of GHG in the atmosphere Effect of the increase in GHG concentration on the average temperature (and on other key effects of climate change, sea level rise, etc.) Effect of the increase in average temperature on different indicators of social welfare (such as production by sector and per capita consumption) Climate models Economic models Integrated assessment models (IAMs) 15 / 26

16 ΙV. CC models: Basic structure Future CO 2 e emissions BAU (GDP growth and CO 2 e/$gdp) Climate models Future CO 2 e concentration (due to old, current and future levels of GHG emission) Climate sensitivity (changes in average temperature, rainfalls, hurrican es, sea level rise etc, due to the increase in CO 2 e concentration) 6 Economic effects (constructing the social welfare function and choosing the discount rate) 5 Cost estimates of emission reduction (necessary technological changes) 4 Damage estimation (economic, social, political and health damages due to the increase in average temperature, given adaptation) Economic models Integrated assessment models (IAMs) 16 / 26

17 V. Prediction & uncertainty Nordhaus 2008 estimate: SCC=$20/ton 2011 estimate: SCC=$12/ton Stern 2007 estimate: SCC=$200/ton Great uncertainty temperature = f(co 2 concentration) Effect of GHG emissions on the concen-tration of GHG in the atmosphere Effect of the increase in GHG concentration on the average temperature (and on other key effects of climate change, sea level rise, etc.) Great uncertainty Economic impact = g(temperature) Effect of the increase in average temperature on different indicators of social welfare (such as production by sector and per capita consumption)) U.S. Government Interagency Working Group on Social Cost of Carbon: 2010 estimate: SCC=$21/ton, 2013 estimate: SCC=$33/ton Climate models Economic models Integrated assessment models (IAMs) PAGE (Policy Analysis of the Greenhouse Effect) DICE (Dynamic Integrated Climate and Economy) FUND (Climate Framework for Uncertainty, Distribution, and Negotiation) 17 / 26

18 VI. Uncertainty (climate model) Climate sensitivity is defined as the temperature increase that will result in equilibrium (a period around 50 years) after doubling CO 2 concentration in the atmosphere due to anthropogenic actions. The main problem in estimating climate sensitivity is the existence of feedback loops that we do not know their intensity (and in some cases not even their sign). IPCC has summarized the results of 22 published papers and estimated the climate sensitivity between ο C taking into account probability distribution. From the summary of distributions results that there exists 5% probability that CS is >6.5 ο C. Assume λ 0 is the climate sensitivity without feedback loops (ΔT 0 =λ 0ο C). However, the initial change ΔT 0 will result in changes that further change ΔΤ. According to Roe and Baker (2007) the final CS is: where f (0 f 1) is the total feedback. Unfortunately we don t know the value of f and therefore we need to consider probabilities once more. The uncertainty over f adds to the uncertainty over λ (if f has a value close to unity, λ will be extremely large). Therefore there are a lot of questions regarding the determination of λ. 18 / 26

19 VI. Uncertainty (economic model) With regards to the estimation of damages, we do not have any data and thus we resort to hypothetical functions (the estimation of climate sensitivity despite uncertainties is based on data). We assume that without climate change, consumption (or GDP) grows with a rate equal to g and in period t is GDP t. Climate change results in damages which are estimated using the loss function L(ΔT), with L(0) = 1 and L'(ΔT) < 0, and therefore with climate change we have GDP t cc = L(ΔT t )GDP t. Different reports use a variety of functional forms. Nordhaus (2008) using the DICE model: L = 1/[1 + π 1 ΔΤ + π 2 (ΔT ) 2 ]. Weitzman (2009): L(ΔT ) = exp[ β(δt) 2 ] (allowing for greater damages for higher ΔΤ) Some other studies use more complicated functional forms which are applied to global, regional and even economic sector s level. All of them though are hypothetical. How do the values of β and π are chosen? Most studies choose the parameters so as L(1) is close to 1 (mo damages), L(2) is close to.99 or.98, and L(3) and L(4) is close to.97 και.96 respectively. This is done so that they remain close to the IPCC damage estimates of 1-5% damages for an increase of 4 0 C. But the IPCC estimates are the result of the studies summary: Cycle. 19 / 26

20 VI. Uncertainty (economic model) Defining the social welfare function (for estimating the effects of the expected reduction in consumption over time). C t : consumption at period t η: index of relative risk aversion (IRRA) δ: rate of time preference time-additive, constant relative risk aversion (CRRA) utility What is the «true» value of η ; Index η expresses peoples attitude when exposed to uncertainty. In general, higher values of η imply lower values of SCC. In macroeconomics and finance literature values between 1.5 and 4 are considered reasonable. Since though η reflects aversion towards intergenerational inequalities, its value should be considerably lower varying between 1 and 3. In both cases the range of values is quite wide. What is the «true» value of δ; The choice of the value of δ is crucial since the time frame of the problem at hand is large (50 to 200 years) and thus, values above 2 would hardly justify any action. The range in financial markets is between 2 to 5%, which though cannot be used for large periods of time. Some economists (Stern and Heal) suggest δ=0 using ethical arguments (it is unethical to discount the welfare of future generations relative to the current). The debate over the choice of η and δ values relates to the choice of the discount rate of future costs and benefits. This discount rate according to Ramsey is: R = δ + ηg, where g (1.5-2%) is the growth rate. (Stern: δ=0, η =1 R small, Nordhaus: : δ =1.5%, η =2 R=5.5%, IWG: R=3%) 20 / 26

21 VI. Uncertainty (economic model) 120 time 5% 1,50% , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , % 3% 1,5% 1% 100 euros discounted at 5% are worth in 100 years less than a euro. However, when discounted at 1,5%, although they are loosing considerable value they are still worth a substantial amount. The larger the period the more important is the value of the discount rate. 21 / 26

22 VI. Uncertainty (economic model) Estimates of SCC mean values for the period , for three levels of discount: 2,5, 3 και 5% (mean distributions of the three models using five socioeconomic scenarios for each model). Estimates of the SCC distribution for 2020 for three discount rates: 2,5, 3 και 5% (average distributions of the 3 models running 5 socioeconomic scenarios each). 22 / 26 Elizabeth Kopits (2014) «The Social Cost of Carbon in Federal Rulemaking», National Center for Environmental Economics, U.S. EPA (U.S. Government Interagency Working Group on SCC)

23 VII. Catastrophic events The IAM models do not take into account the possibility of catastrophic events due to climate change. The damage functions are structured so as to yield impacts in the range of 1-5% of global GDP for ΔΤ<4-4.5 o C. These functional forms cannot say anything for ΔT>5 o C. Despite the fact that the probability of increases in average temperature greater than 7 to 8 o C is small, the fact that the impacts are enormous, would substantially increase the value of SCC. Ignoring this, small, probability yields misleading results. Unfortunately we cannot use the IAM models to get results in this case. The best way remaining is to follow a much simpler approach and use more crude, subjective estimates of the probability of very high increases in average temperature and then to assume a distribution of the magnitude of the impacts (in terms of lost GDP or productive capital). This problem is similar to the estimation of the catastrophic dangers of a nuclear war during the cold war era. In that case as well, the probabilities were unknown and so were the impacts. However, the estimates of the extreme damages were very important in leading to the elimination of the probability through the arms control agreements. 23 / 26

24 VII. Catastrophic events The distributions of the 18 studies that IPCC summarized (2 4.5 o C, with best estimate 3 o C, very unlikely that it will be smaller than 1.5 o C and without being able to exclude increases higher than 4.5 o C) are presented in part (α) of the Figure and it is evident that their right tails are long and fat (long and fat tailed pdfs) and cut above 10 ο C. The upper 5% confidence interval (mean value of the 18 studies) is 6.2 ο C, which can be considered that implies P[ΔΤ>6.2 ο C]>5%. Weitzman (2007) (α) (β) we consider as tail of the distribution values above 4.5 C, since these values are above the limit of IPCC s range Calel, Stainforth and Dietz (2014) «Tall tales and Fat tails: The science and economics of extreme warming» The black curve (in both (α) & (β)) shows the IPCC s estimate (mode: 3 C, density: 0.67 for changes between C) in log-normal pdf, the blue curve in (β) is the Roe and Baker (2007) and the in-between is the loglogistic pdf of Stainforth et al. (2005). 24 / 26

25 VII. Catastrophic events All models surveyed above (despite their obvious problems) predict very large economic impacts of climate change, especially if we consider extreme catastrophic events which results mainly from non well defined «bad feedback components of the carbon cycle» Even if someone is not convinced that climate change will result in catastrophes, no one can preclude the possibility that such events could happen. Therefore, some mitigation and adaptation action should be undertaken, even as an insurance against the possibility that such large damages could occur. Action? Yes No Does the problem exists? Probability Ναι 10%? High cost Avoid large damages Small cost Large damages No Large cost Small damages Small cost Small damages The basic issue here is that spending money to slow global warming should perhaps not be conceptualized primarily as being about consumption smoothing as much as being about how much insurance to buy to offset the small change of a ruinous catastrophe that is difficult to compensate by ordinary savings. Weitzman, Journal of Economic Literature / 26

26 VIIΙ. Literature Heal, Geoffrey Climate Economics: A Meta-Review and Some Suggestions. Review of Environmental Economics and Policy, 3: Interagency Working Group on Social Cost of Carbon Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis. U.S. Government. Intergovernmental Panel on Climate Change Climate Change Cambridge University Press. Nordhaus, William D A Review of the Stern Review on the Economics of Climate Change. Journal of Economic Literature, Pindyck, Robert S. 2011a. Fat Tails, Thin Tails, and Climate Change Policy. Review of Environmental Economics and Policy, 5(2): Pindyck, Robert S. 2013b. Pricing Carbon When We Don t Know the Right Price. Regulation, 36(2): Stern, Nicholas The Structure of Economic Modeling of the Potential Impacts of Climate Change Has Grafted Gross Underestimation onto Already Narrow Science Models. Journal of Economic Literature, 51 Weitzman, Martin L OnModeling and Interpreting the Economics of Catastrophic Climate Change. Review of Economics and Statistics, 91: Weitzman, Martin L Tail-Hedge Discounting and the Social Cost of Carbon. Journal of Economic Literature, / 26