Economics 331

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Economics 331. 1. Finale on climate change policy. Today: Endgame Alternative perspectives Environmentalist perspective Conservative perspective Reprise on learning Tipping points and policy. Endgame for course. 1. Final exam (absence by Dean’s excuse only) - PowerPoint PPT Presentation

Transcript of Economics 331

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Economics 331

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Finale on climate change policy

Today:EndgameAlternative perspectives

• Environmentalist perspective• Conservative perspective• Reprise on learning• Tipping points and policy

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Endgame for course1. Final exam (absence by Dean’s excuse only)

ECON 331. Assigned to exam group 33Friday, May 6, 2011. 9:00 am – 11:00 am

2. Structure: probably three parts: will probably have choice.40 minutes for “prepared questions” (to be posted); 40 minutes

problems; 40 minutes more problems 3. I will post last year’s exams (but no answers)4. Review sessions: WN 1 next week; WN 1 week after; office

hours by Lint 5. Grades will be approximately based 20 percent on the

problems, 30 percent on the paper, 20 percent on the midterm, and 30 percent on the final, all with adjustments.

6. Paper due noon April 27 (hard copy outside my office; electronic copies to WN and LB)

7. Hard deadlines for seniors. No postponements for last-minute procrastinations.

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Strong --------- Stern ------------------A----B----C----------DICE------D-----------Lomberg--- Weak

policies $100 /tCO2 $10 - $20/tCO2 $1/tCO2 policies

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The spectrum of economic views on climate change

Stern: Stern Review, also summarized in his Ely lecture, American Economic Review.

Lomberg has organized the Copenhagen consensus of (largely) conservative thinkers to rank major issues.

A, B, C, D are other models

The Copenhagen Consensus: Priorities for Action

Economics 487b, Spring 20075

“In ordering the proposals, the panel was guided predominantly by consideration of economiccosts and benefits.” http://www.copenhagenconsensus.com

Environmentalist critiqueStern/Krugman critique* of the DICE model

approach:

1. Uses too high a discount rate2. Ignores the uncertainty and the “fat tail” of low-

probability catastrophic outcomes3. Uses a temperature sensitivity coefficient of 3 °C

per CO2 doubling instead of more realistic 6 °C Next slide shows the sensitivity of the emissions

control rate if we introduce these sequentially. Which are most important?

*Stern Review : http://webarchive.nationalarchives.gov.uk/+/http://www.hm-treasury.gov.uk/sternreview_index.htm

Krugman, “Building a Green Economy,” NYT Magazine, 2010, http://www.nytimes.com/2010/04/11/magazine/11Economy-t.html 6

Emissions Controls for Environmentalist Assumptions

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0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

2005 2025 2045 2065 2085 2105

Emis

sion

s co

ntro

l rat

e

Optimal: base assumptions

6 deg C

6 deg C and double damages

Base and low discounting

6 °C and low discounting

6 deg C, double damages, and low discounting

Reprise on learning

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Original example

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The state of the environmental world

Good outcome (low damage, many green technologies)

Poor outcome (catastrophic damage, no green technologies)

Climate

Strong policies (high carbon tax, cooperation, R&D) -1% -1%

policyWeak policies (no carbon tax, strife, corruption) 0% -50%

Probability 90% 10%

Learn then act:

E(U) = 0.9 x 0% + 0.1 x -1% = -0.1% Expectation of strong = 0.1

Act then learn:

Strong: E(U) = 0.9 x -1% + 0.1 x -1% = -1% Best policy: Expectation of strong = 1

Weak: E(U) = 0.9 x 0% + 0.1 x -50% = -5%

Therefore, learning leads to weaker policies. Precautionary motive holds.

Revised example with lower damage in bad state.

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The state of the environmental world

Good outcome (low damage, many green technologies)

Poor outcome (catastrophic damage, no green technologies)

Climate

Strong policies (high carbon tax, cooperation, R&D) -1% -1%

policyWeak policies (no carbon tax, strife, corruption) 0% -5%Probability 90% 10%

Learn then act:

E(U) = 0.9 x 0% + 0.1 x -1% = -0.1% Expectation of strong = 0.1

Act then learn:Strong: E(U) = 0.9 x -1% + 0.1 x -1% = -1.0%

Weak: E(U) = 0.9 x 0% + 0.1 x -5% = -0.5% Best policy: Expectation of strong = 0

Therefore, learning leads to stronger policies. Precautionary motive DOES NOT hold.

ConclusionExample shows how expected strength of policy can

either go up or down with learning.No general theorem about whether learning

increases or decreases your abatement (or investments more generally)

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How can we treat tipping points and threshold effects?

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kk***k**k* 13

OOPS!!!!!!!

kk***k**k* 14

Note: Have new and different locally stable equilibrium

Non-linearities in the climate systemMost of the impacts literature examines gradual

climate change, with roughly linear systems and impacts.

Scientists have been particularly concerned about discontinuities, abrupt climate change, tipping points, catastrophic impacts.

How can we deal with thresholds in our economic analysis? A very tough problem on the frontier.

Examples from climate system

Source: Lenton et al., “Tipping Elements,” PNAS, Feb 2008, 1786. 16

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TotalAbatement Cost

Temperature

Total Damage

0Temperature*

Optimum Without Thresholds

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TotalAbatement Cost

Temperature

Total Damage

0Temperature*

Optimum With Thresholds

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Marginal Abatement Cost

Temperature

Marginal Damage

0Temperature*

Optimum Without Thresholds

2020

Marginal Abatement Cost

Temperature

Marginal Damage

0Temperature*

Optimum With Thresholds ???!!!???

2121Temperature

Net income

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Which is the real maximum?

Have multiple equilibrium for system and policy

• DICE type model.• Catastrophic damage at 3 °C = 50 % of output• Have abatement choice about whether to pass

the threshold as function of costs and benefits.• Abatement cost varies from 1% to 100% of

output.• Next slide shows whether optimally pass the

threshold as function of abatement cost.• Note that SOLVER can’t reliably get the right

answer near the cross-over because it is local optimizer!

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Solutions for temperature

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0

2

4

6

8

10

12

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0 0.2 0.4 0.6 0.8 1 1.2

Max

imum

tem

pera

ture

(deg

C)

Mitigation cost intercept

Max T from upper end

Max T from lower end Cross catastrophic threshold

Avoid catastrophic threshold

Note: 1. Have algorithm problems because multiple local maxima. 2. Sharp discontinuity in solution around threshold.

Solutions for PV net income

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0

2000

4000

6000

8000

10000

12000

0 0.2 0.4 0.6 0.8 1 1.2

Pres

ent v

alue

net

out

put

Mitigation cost intercept

PV from upper end

PV from lower end

Cross catastrophic threshold

Avoid catastrophic threshold

Note: Solution is continuous for PV income (although bad)

Solutions for first-period control rate

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Note: Paradox that control rate goes UP around switch point. Why? First you speed up, then when you know you are going to miss your plane, slow down.

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0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

0 0.2 0.4 0.6 0.8 1 1.2

Emiss

ions

cont

rol r

ate

first

per

iod

Mitigation cost intercept

Cross catastrophic threshold

Avoid catastrophic threshold

Note: had slightly wrong graph in class.

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Where do we go from here?

It is in YOUR hands…

Where do we go from here?

It is in YOUR hands…

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