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ROCHESTER, NY, 28 June 2023 - Introducing GEO-X: How 10 Big Firms Can Lead Us to End Global Warming - a must-read book for executives who care about global warming. This book proposes an audacious solution to reverse and end global warming - at the least economic cost and by the date of our choosing.
GEO-X examines the political obstacles to ending global warming and concludes that governments will probably never overcome them. The book describes the weaknesses of existing regulatory systems, how they slow emissions but fail to incentivize true net zero operations, much less the enormous carbon removal required to reverse global warming. The book explains the failures of the carbon removal markets, especially the moral hazard so often resulting in fraud.
To solve all of these problems simultaneously, GEO-X proposes a bold three-part solution.
First, a coalition of willing firms could start a Global Emissions and Offset Exchange (GEO-X) to trade emissions permits and carbon removal contracts. Participating firms would end business with non-participating firms. The result would likely be a rush to join through the global supply chain.
Second, the GEO-X institution would strengthen the carbon removal market with contracts backed up by modern data and biological simulation. GEO-X would not pay for reducing emissions, but only for removing carbon from the air.
Third, GEO-X would clear the carbon market with a state-of-art auction mechanism which prices a hard deadline on global warming. This auction mechanism appears to be the most efficient emissions trading system ever designed.
GEO-X would not need government to start, but would benefit from government cooperation. Governments could require businesses within their jurisdiction to participate in GEO-X, accelerating global participation.
GEO-X calls senior business executives to tackle global warming head-on. Where government cannot act, business could succeed - if a few executives take the initiative. Get it now and send it to your boss!
About the author: Dr. Raffensperger has a PhD from the University of Chicago’s Graduate School of Business. With a forty-year career in operations research, he is an expert in market design and supply chain management.
29 minutes, A Faster Path to End Global Warming: A Price on Warming with a Supply Chain Directed Market.
5 minutes, Ending Global Warming Faster and Cheaper.
Abstract: Existing emissions trading system (ETS) designs inhibit emissions but do not constrain warming to any fixed level, preventing certainty of the global path of warming. Instead, they have the indirect objective of reducing emissions. They provide poor future price information. And they have high transaction costs for implementation, requiring treaties and laws. To address these shortcomings, this paper proposes a novel double-sided auction mechanism of emissions permits and sequestration contracts tied to temperature. This mechanism constrains warming for many (e.g., 150) years into the future and every auction would provide price information for this time range. In addition, this paper proposes a set of market rules and a bottom-up implementation path. A coalition of businesses begin implementation with jurisdictions joining as they are ready. The combination of the selected market rules and the proposed implementation path appear to incentivize participation. This design appears to be closer to "first best" with a lower cost of mitigation than any in the literature, while increasing the certainty of avoiding catastrophic warming. This design should also have a faster pathway to implementation. A numerical simulation shows surprising results, e.g., that static prices are wrong, prices should evolve over time in a way that contradicts other recent proposals, and "global warming potential" as used in existing ETSs are generally erroneous.
To get the warming coefficients, I used Hector with the RCP26 scenario. You'll find this as hector_rcp26.ini in the Hector download.
Here is the Python code to get the coefficients: Run_Hector.py.
Python code to run the auction: SMDAMAGE_3.py
Sources of data, corrected forestry.xlsm. The macro is a function for linear interpolation. This data is crude.
Updated 2024 03 28.