Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment

Knightian uncertainty in climate sensitivity is analyzed in a two sectoral integrated assessment model (IAM), based on an extension of DICE. A representative household that expresses ambiguity aversion uses robust control to identify robust climate policy feedback rules that work well over IPCC climate-sensitivity uncertainty range [1]. Ambiguity aversion, together with linear damage, increases carbon cost in a similar way as a low pure rate of time preference. Secondly, in combination with non-linear damage it makes policy responsive to changes in climate data observations as it makes the household concerned about misreading sudden increases in carbon concentration rate and temperature as sources to global warming. Perfect ambiguity aversion results in an infinite expected shadow carbon cost and a zero carbon-intensive consumption path. Dynamic programming identifies an analytically tractable solution to the model.<p>