Jeffrey K. O’Hara Emissions Scenarios ESP – Climate Change Forum May 12, 2006.

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Presentation transcript:

Jeffrey K. O’Hara Emissions Scenarios ESP – Climate Change Forum May 12, 2006

Importance of Forecasting Emissions Emissions forecasts are important because climate change mitigation is a “global public good” A public good is defined as a good that is both non-rival and non-excludable –Example: national defense The benefits of associated carbon reductions are enjoyed by everyone, so any future agreement must anticipate what the future level or carbon emissions will be so that they understand what the benefits will be from mitigation

Public Goods and Free Ridership Public goods (in contrast to private goods) can lead to market failures due to the free rider effect Because the benefits of reductions can be enjoyed by everyone, this gives incentives to others to avoid paying for the good Providing a public good generates an externality: someone is getting benefits from your consumption they did not pay for Externalities can be good or bad

Cost-Benefit Analysis Emissions forecasts are used for cost-benefit analysis CBA is often used by government economists to weigh the economic costs and benefits of a particular policy when evaluating Costs and benefits that occur in the future are discounted – thus, benefits that occur in 100 years will count little in a “present discounted value” of a particular policy Formal work includes the role that uncertainty plays

Cost Benefit Analysis with Climate Change Some sectors (agriculture and forestry in US, Canada, and Russia) could gain from increased temperatures Some climate change impacts are now guaranteed and cannot be avoided at this point Costs of abatement are very large From CBA perspective, global stabilization would lead to $3 trillion cost to the US A modest tax ($9/ton C) was found in one study to be optimal approach – 5% abatement in short run (relative to business as usual) and 11% in long run

CBA Summary CFC abatement –Costs very small due to close substitute –Benefits extremely high even in medium term (skin cancer deaths) GHG abatement –Costs extremely high up front –Benefits occur in future – lower than CFC abatement since not fatal

Game Theory Notion of strategic interplay between 2 or more parties Definition of “best response function” = what is the best that I can do given the strategy choice that others are making? Definition of “Nash Equilibrium” = where best response functions intersect

Prisoners Dilemma Climate change has similar features to a prisoner’s dilemma Literature in economics on necessary conditions an agreement will need to have to support abatement (Pollute, Pollute) is Nash equilibrium (Country A payoff, Country B payoff) Country B AbatePollute Country A Abate(1,1)(-1,2) Pollute(2,-1)(0,0)(0,0)

How Are Emissions Forecasted? Emissions are forecast in a variety of ways Am going to approach on work by Auffhammer, Carson, and Garin-Munoz to contrast the different approaches that have been taken with emissions in China China is interesting to examine because it is currently the #2 emitter and is expected to be the #1 emitter by 2020

Approach #1 Use annually observed aggregate emissions data Predictors are population, income, some measure of technology Ones with economic focus incorporate fuel switching, induced technological change, and emissions trading This approach is commonly used by scientists and used in IPCC report

Approach #2 & 3 Limitations to approach #1 obvious Approach #2 disaggregates emissions by industry sector Can either be done with aggregate sectoral data by firms or by using random samples of firms stratified by sector Approach #3 explores case studies by looking at factors that influence performance of specific plants

Approach #4 Explore emissions scenarios spatially at the provincial level Chinese provinces differ greatly in land area with heterogeneity over population, income, and technological change Pollution regulated varies at the provincial and city level

Environmental Kuznets Curve Empirical question as to whether emissions follows “Kuznets curve hypothesis” Country’s pollution is a quadratic function of income (rises, then falls) Assumes abatement is a luxury good – poor people cannot afford it, but richer people can Hypothesis is controversial (implication being that rising income will lead to abatement) and may hold for some pollutants and not others

Summary to this Point Prisoners dilemma nature of game implies benefits won’t be realized w/out developing country participation The notion of meeting a target coupled with a timetable was fundamental to the Kyoto process (technology standards largely ignored) Problem: EKC implies this approach will impose much larger costs on developing countries than developed countries Kyoto has other obvious flaws (namely the lack of enforcement) –Does not deter non-participation and does not deter non-compliance

General Model The dependent variable is per capita carbon emissions for a particular province in a particular year Independent variables: –Province fixed effect –Year fixed effect –Current GDP at province –Lagged GDP at province –Current population density at province –Lagged per capita carbon emissions at all provinces –Other controls: industry composition, coastal provinces, etc.

Findings Province specific per capita emissions likely to follow very different income/pollutant trajectories Small number of provinces that are very large coal producers driving results Uncertainty in population changes likely to dominate uncertainty over per capita GDP – in other words, population policies should also be considered in addition to technology policies

References Auffhammer, M., R. Carson, T. Garin-Munoz, Forecasting China’s Provincial Emissions: A Provincial Approach, unpublished. Barrett, Scott, Environment & Statecraft: The Strategy of Environmental Treaty-Making, Oxford University Press, 2003 Dutta, Prajit K. and Roy Radner, “Self-Enforcing Climate Change Treaties”, PNAS, April 6, 2004 Goulder, Lawrence H. and William A. Pizer, “The Economics of Climate Change”, NBER Working Paper, January 2006.