Transcript Impacts_L1_v2

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.
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Economics of Climate Change:
Impacts
Economics 331b
Spring 2009
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Market equilibrium
with externality
Price, MC, MPB
of abatement
Marginal cost
Market equilibrium:
Zero carbon reductions
Where MPB = MC
Marginal private benefit
0
Abatement
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Price of carbon emissions
The basic analytical structure
Marginal Damages
Marginal Cost
Pcarbon*
0
Abatement*
Abatement
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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”).
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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, …)
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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
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Market sectors by vulnerability to climate change, US, 2007
Billions of dollars
Gross domestic product
13,808
Major Potential Impact
Farms
Forestry, fishing, and related activities
Nordhaus, based on BEA , industry accounts,
http://www.bea.gov/industry/index.htm#annual
168
1.2
598
4.3
13,041
94.4
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281
159
121
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Small to Negligible Impact
Mining
Construction
Manufacturing
Trade
Retail trade
Transportation and warehousing
Information
Finance, insurance, real estate, etc.
Services and government
100.0
137
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Moderate Potential Impact
Water transportation
Utilities
Real estate
Coastal
Accommodation
Arts, entertainment, and recreation
Outdoor
Percent
of GDP
275
611
1,617
1,698
893
407
586
2,652
4,302
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Example from Sea Level Rise: Model Runs
IPCC, 2001
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Example from Verly on Sea-Level Rise
On Cape Cod
Caroleen Verly, “Sea-Level Rise on Cape Cod: Predicting the Cost of Land and Structure
Losses”, Yale University, 2008
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Land value and altitude
Caroleen Verly, “Sea-Level Rise on Cape Cod: Predicting the Cost of Land and Structure
Losses”, Yale University, 2008
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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
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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.
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Example of impact of weather on yield
Why is this
completely wrong
for understanding
the impact of
climate change on
agriculture?
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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.
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Short-run
v.
long-run productivity
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Estimates of Impacts on Agriculture late in the 21st C
Impacts on net value of agriculture as percent of national or
global income:
Mendelsohn
Cline
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
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First Generation
Estimates of
Aggregate
Monetized Damages
of CO2 Doubling,
U.S., for present
economy
Source: IPCC, Second
Assessment Report
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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
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IPCC Collation of Global Damages, AR Three
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Estimated Damages from Yale Models and IPCC Estimate
11%
Climate damage/global output
10%
RICE-1999
9%
DICE-2007
8%
7%
6%
5%
4%
IPCC estimate
3%
2%
1%
0%
0
1
2
3
4
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Mean temperature increase (oC)
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Summary of Impacts Estimates
Early studies contained a major surprise:
Modest impacts for gradual climate change, market impacts, highincome 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)
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Major problems of impacts analysis
1. Most impacts analyses impose climate changes on current socialeconomic-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.
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