Discussion Paper

No. 2011-17 | June 14, 2011
A Shapley Value Approach to Pricing Climate Risks
(Published in Special Issue The Social Cost of Carbon)

Abstract

This paper prices the risk of climate change by calculating a lower bound for the price of a virtual insurance policy against climate risks associated with the business as usual (BAU) emissions path. In analogy with ordinary insurance pricing, this price depends on the current risk to which society is exposed on the BAU emissions path and on a second emissions path reflecting risks that society is willing to take. The difference in expected damages on these two paths is the price which a risk neutral insurer would charge for the risk swap excluding transaction costs and profits, and it is also a lower bound on society’s willingness to pay for this swap. The price is computed by (1) identifying a probabilistic risk constraint that society accepts, (2) computing an optimal emissions path satisfying that constraint using an abatement cost function, (3) computing the extra expected damages from the business as usual path, above those of the risk constrained path, and (4) apportioning those excess damages over the emissions per ton in the various time periods. The calculations follow the 2010 US government social cost of carbon analysis, and are done with DICE2009.

Paper submitted to the special issue
The Social Cost of Carbon  

JEL Classification

C71 Q54

Cite As

Roger M. Cooke (2011). A Shapley Value Approach to Pricing Climate Risks. Economics Discussion Papers, No 2011-17, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2011-17

Assessment



Comments and Questions


James K. Hammitt - Referee Report 1
October 20, 2011 - 12:01

See attached file


Anonymous - Referee Report 2
October 31, 2011 - 12:00

see attached file


Roger Cooke - Reply to Referee Reports
November 08, 2011 - 10:44

see attached file


Alexander Golub - Remark on the essence of the paper
November 10, 2011 - 15:14

In my view the essence of the paper – to show different approach, e.g. risk constrained optimization. And I think you did that well. If somebody doesn’t like 2C target or 0.19 probability, can repeat experiment with different parameters…

Crystal Ball is a powerful instrument and good platform for ...[more]

... constrain stochastic optimization. Alternative would be matlab. GAMS would not be my choice. I have some experience running Monte-Carlo in R and GAMS it is time consuming. After all there in no significant benefits to choose GAMS over CB/optquest since DICE is a very simple model.
Possible extensions and next steps:
It will be nice to continue experiment and reconcile dynamic stochastic optimization, optimization with real option value, risk constrain optimization. Then we can see how shadow price of risk constrain related to risk adjusts SCC etc . What should be value of on optimal carbon tax, emission pathway etc.


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