Imperfect measurement of uncertainty (deeper uncertainty) in climate sensitivity is introduced in a two-sectoral integrated assessment model (IAM) with endogenous growth, based on an extension of DICE. The household expresses ambiguity aversion and can use robust control via a 'shadow ambiguity premium' on social carbon cost to identify robust climate policy feedback rules that work well over a range such as the IPCC climate sensitivity range (IPCC, 2007a). Ambiguity aversion, in combination with linear damage, increases carbon cost in a similar way as a low pure rate of time preference. However, ambiguity aversion in combination with non-linear damage would also make policy more responsive to changes in climate data observations. Perfect ambiguity aversion results in an infinite expected shadow carbon cost and a zero carbon consumption path. Dynamic programming identifies an analytically tractable solution to the IAM.
Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment
Working Paper by Magnus Hennlock — May 4, 2009Download
Press Release — Nov 12, 2019
New Episode of Resources Radio: “Carbon Pricing Proposals in Today's Congress, with Marc Hafstead”
Marc Hafstead offers insight on the numerous carbon pricing proposals that have been introduced in the US Congress.
Carbon Pricing Proposals in Today's Congress, with Marc Hafstead
In a special crossover episode with CSIS' Energy 360° podcast, Marc Hafstead analyzes the recent cluster of carbon pricing proposals that have been introduced in the US Congress.
Testimony and Public Comments — Oct 30, 2019
Hearing on Building a 100 Percent Clean Economy: Solutions for the Power Sector
Written Testimony Prepared for the Energy Subcommittee of the US House Committee on Energy and Commerce