The Economics of Climate Change

The basic mechanism

In the long run perspective

Do not mix up with Ozone layers Both are environmental problems Both are related to the atmosphere But they different issues – The atomosphere is so complex that more than one process may go on there The ozone layer stop ultra-violet rays – With a thin ozone layer, skin cancer more likely – But note: This is an example demonstrating that international agreement can be successful! Global warming is an other problem

International agreement The problems of reaching an agreement on CO 2 is eminent. In addition to the incentives discussed, we have distributional issues. – The cost likely to be born by developing countries – These countries have not caused the problems. – Equal emission cut in % will harm the poor – Equal emissions per capita will gain China and India hugely.

The Kyoto protocol Agreement from December 1997 Annex I: Countries listed to take cut in emission – Countries with emissions above 2 tC/cap 1990 Reductions relative to 1990-level. – Not by populations or GDP – Avoid strategic emissions Annex I countries may induce reduction in Non-Annex I countries through Clean Development mechanisms (CDM)

Emissions 2000 relative to target

Emission trading in Kyoto Was controversial in negotiations – Concern about market power from large sellers (Russia) and buyers (US) – Resistance to emission trading in general. Two main mechanism – Clean Development Mechanism (CDM) Countries with comittments can pay for development projects in countries without committment provided these would not be undertaken otherwise. – Joint implementation: Two or more countries with committment can jointly implement their committment (Trade quotas; EU has redistributed their quota and established a market)

Returning to optimal policy Recall from last week Nordhaus find an optimal carbon price of 27$/tC Stern find an optimal carbon price at 250$/tC The main different is the discount rate – The Stern review implicitly uses 1.4% – Nordhaus uses 4% discount rate, but a 6% return on capital.

Return to investments If we invest 1 million $ today, what will it be worth 100 years from now: – In Treasury Bills: at most 2,7 million $ (1%) – In stocks: 2,2 billion $ (historical return, 8%) Why this huge difference? – Uncertainty explains some of the difference – But not all of it – Returns to stock may be lower if we estimate it today.

A Crash-course in Finance; CAPM An investor is better of owning 50% of two firms than 100% of one. – If one firm get bankrupt he is still not broke. The best hedged portfolio owns a share of all stocks. (The market portfolio) Now consider selling 1000 $ of the portfolio and buy stock A: Will the portfolio be more or less risky? – Depends on the correlation with the market portfolio.

Example: To assets Both A and B pays 1 million Kroner with probability 0.1%, otherwise nothing? – Are they equally risky? Depends on how they correlate with your wealth: – A pay 1 million if your house burns. – B pay 1 million if the stock market is excep. good. A makes you wealth less uncertain, B makes it more uncertain.

The Capital Asset Pricing Model (CAPM)

Does climate abatement add to future uncertainty? Nordhaus: D’(A) is positively correlated with future GDP. – There is more at stake when future GDP is high – Implies a discount rate above the Treasury bill (1%) Howarth estimate the CAPM model and finds a discount rate much closer to 1% than to 8%.

Temperature change and consumption

Subjective probabilities and tails Difficult to estimate probabilities – Not like a dice we can roll hundreds of times and observe frequencies The rare events that we almost never observe, may be the most important.

The equity premium puzzle If stock pay 7% more than bonds, why don’t we put all our wealth into bonds? – Risk aversion must be implausibly high to explain it – The returns to stock may be overestimated? – Some other theories, resolution of uncertainty, behavioral economics, etc. The implication for climate discounting not well studied.

The tick tail (Weitzman) Consider the St. Petersburg paradox – Flip a coin until tail in n’th flip – Payment 2 to the n’th, 2,4,8,16,32… – Expected value If we run simulation, we will most likely not observe n above 30 – Estimated value will be rather small With observation we will miss the tail – And hence miss the real expected value In climate chance the extreme event are important, events we do not observe and no model simulates

Assessing the tail of climate change (Weitzman) There are hundreds of simulation of temperature change provided we stabilize at 560 ppm (2x 280 ppm, the pre- industrial level) 1% of these give temperature change > 10 degree – The premise ignores feedback, methane will be released from the tundra, likely temperature increase is up to 20 degrees; the difference between summer and winter in Oslo. – No guarantee that mankind will survive – D’(A) and GDP negatively correlated – Weitzman conclude that the optimal carbon price is almost infinite. Note: It is highly unlikely that the world will be able to stabilize CO 2 at a level as low as 560 ppm