Exhibit A – the Social Cost of Carbon

I recently discovered a cool set of tools from MIT’s Simile project. My favorites are Timeline and Exhibit, which provide a fairly easy way to create web sites where visitors can interact with data. As a test, I built an Exhibit containing Richard Tol’s survey of assessments of the social cost of carbon (SCC):

Social Cost of Carbon Exhibit

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More Oil Price Forecasts

The history of long term energy forecasting is a rather mixed bag. Supply and demand forecasts have generally been half decent, in terms of percent error, but that’s primarily because GDP growth is steady, energy intensity is price-inelastic, and there’s a lot of momentum in energy consuming and producing capital. Energy price forecasts, on the other hand, have generally been terrible. Consider the Delphi panel forecasts conducted by the CEC:

California Energy Commission Delphi Forecasts

In 1988, John Sterman showed that energy forecasts, even those using sophisticated models, were well represented by a simple adaptive rule: Continue reading “More Oil Price Forecasts”

SRES – We've got a bigger problem now

Recently Pielke, Wigley and Green discussed the implications of autonomous energy efficiency improvements (AEEI) in IPCC scenarios, provoking many replies. Some found the hubbub around the issue surprising, because the assumptions concerned were well known, at least to modelers. I was among the surprised, but sometimes the obvious needs to be restated loud and clear. I believe that there are several bigger elephants in the room that deserve such treatment. AEEI is important, as are other hotly debated SRES choices like PPP vs. MEX, but at the end of the day, these are just parameter choices. In complex systems parameter uncertainty generally plays second fiddle to structural uncertainty. Integrated assessment models (IAMs) as a group frequently employ similar methods, e.g., dynamic general equilibrium, and leave crucial structural assumptions untested. I find it strange that the hottest debates surround biogeophysical models, which are actually much better grounded in physical principles, when socio-economic modeling is so uncertain.

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