Agenda

1. Agenda Today: impacts Friday at class time: Gokay will review material. Friday at noon: Questions will be distributed. Monday in class: Exam Wednesday TBA: Gokay will do an introduction of Excel modeling in preparation for your building your little integrated-assessment model. Then spring break.

2. Economics of Climate Change:Impacts Economics 331b Spring 2009

3. Market equilibriumwith externality Price, MC, MPB of abatement Marginal cost Market equilibrium: Zero carbon reductions Where MPB = MC Marginal private benefit 0 Abatement

4. The basic analytical structure Price of carbon emissions Marginal Cost Marginal Damages Pcarbon* 0 Abatement* Abatement

5. What is climate? Consider the complex system as a stochastic process: dx(t)/dt = h[x(t); α, ρ, …] x(t) is temperature, precipitation, ocean currents, etc. α, ρ, etc. are parameters. Weather is the realization of this process. Climate is the statistics of the process (mean, higher moments, extremes). It is usually calculated as moving averages (e.g., 30-year “normals”).

6. Impacts Analysis Central task is to evaluation the impact of climate change on society Two major areas: • market economy (agriculture, manufacturing, housing, …) • non-market sectors • human (health, recreation, …) • non-human (ecosystems, species, fish, trees, …)

7. Basics of Impact Analysis 1. Start with a production function: Q j,t = F(K j,t , L j,t ; T j,t , C j,t) Where Q j,t = output in sector j at time t; K j,t = capital stock and other assets; L j,t = labor and other current; T j,t = weather (realization); C j,t = climate (= statistics of climate) 2. We often have data on the impact of weather changes on Q j,t . But, we need to understand climate impacts: ∂Q j,t /∂ C j,t = ∂F(K j,t , L j,t ; T j,t , C j,t)/∂C j,t 3. Generally, we will have a vector of climatic variables (temperature, precipitation, soil moisture, snow pack, …). We will need to translate global mean temperature change into the relevant climatic variables. This requires calculating ∂C j,t /∂T, which is non-trivial given regional resolution of climate models. 4. Finally, all this gives us the impact relative of global warming: Impact effect =∂Q j,t /∂T = ∂F(K j,t , L j,t ; T j,t , C j,t)/∂ C j,t /∂C j,t /∂T

8. Nordhaus, based on BEA , industry accounts, http://www.bea.gov/industry/index.htm#annual

9. Example from Sea Level Rise: Model Runs IPCC, 2001 10

10. Example from Verly on Sea-Level RiseOn Cape Cod Caroleen Verly, “Sea-Level Rise on Cape Cod: Predicting the Cost of Land and Structure Losses”, Yale University, 2008

11. Land value and altitude Caroleen Verly, “Sea-Level Rise on Cape Cod: Predicting the Cost of Land and Structure Losses”, Yale University, 2008

12. Impact of SLR on Land and Structures Caroleen Verly, “Sea-Level Rise on Cape Cod: Predicting the Cost of Land and Structure Losses”, Yale University, 2008

13. Example from Agriculture Long history of agricultural production functions in which weather is a variable. Remember: Q j,t = F(K j,t , L j,t ; T j,t , C j,t) - This produced first set of estimates of impact of global warming; led to very large estimates of losses.

14. Example of impact of weather on yield Why is this completely wrong for understanding the impact of climate change on agriculture?

15. Example from Agriculture Long history of agricultural production functions in which weather is a variable. - This produced first set of estimates of impact of global warming; led to very large estimates of losses. Problem: The temperature-output relationship does not take into account adaptation of farmers to climate. This is the “dumb farmer” v. “smart farmer” controversy. Ricardian methods are attempt to look at equilibrium effect of climate by looking at cross-sectional impact of climate on farm values (Mendelsohn key figure here) - This produced much smaller estimates because of farmer adaptation.

16. Short-run v. long-run productivity

17. Estimates of Impacts on Agriculture late in the 21st C Impacts on net value of agriculture as percent of national or global income: MendelsohnCline North American + 0.4 % + 0.5 % Africa - 5.0 % - 4.0 % Global average - 0.2 % - 0.1 to -.05% Estimated effect of ag on output is small because (1) agriculture is small, (2) farmers can adapt, (3) CO2 is a fertilizer. Query: Assume this is for 2075. What is effect on growth rate of total GDP of region for 2000-2075? Source: Mendelsohn et al.; Cline

18. First Generation Estimates of AggregateMonetized Damages of CO2 Doubling, U.S., for present economySource: IPCC, Second Assessment Report

19. Economic Impacts of Gradual Climate Change on the U.S. Joel B. Smith, A Synthesis of Potential Climate Change Impacts on the U.S., Prepared for the Pew Center on Global Climate Change, April 2004

20. IPCC Collation of Global Damages, AR Three

21. Estimated Damages from Yale Models and IPCC Estimate

22. Summary of Impacts Estimates Early studies contained a major surprise: Modest impacts for gradual climate change, market impacts, high-income economies, next 50-100 years: - Impact about 0 (+ 2) percent of output. - Further studies confirmed this general result. BUT, outside of this narrow finding, potential for big problems: • many subtle thresholds • abrupt climate change (“inevitable surprises”) • many ecological disruptions (ocean carbonization, species loss, forest wildfires, loss of terrestrial glaciers, snow packs, …) • stress to small, topical, developing countries • gradual coastal inundation of 1 – 10 meters over 1-5 centuries OVERALL: “…global mean losses could be 1-5% Gross Domestic Product (GDP) for 4 ºC of warming.” (IPCC, FAR, April 2007, but no serious original work)

23. Major problems of impacts analysis 1. Most impacts analyses impose climate changes on current social-economic-political structures. - Example: impact of temp/precip/CO2 on structure of Indian economy in 2005 3. However, need to consider what society will look like when climate change occurs. 4. Example of difficulties of looking backward: • 2 ˚C increase in 6-7 decades – that was Nazism, period of Great Depression, Gold Standard, pre-Keynesian macro • 4 ˚C increase in 15 decades –Ming Dynasty, lighting with whale oil, invention of telegraph, no cars, many horses…. 5. Tendency to look for cloud behind every silver lining. 6. In the end, it appears that major impacts are NON-MARKET, VERY DIFFICULT TO VALUE, and VERY CONTENTIOUS.