Determining Climate Sensitivity Using the Quasi-cointegrated VAR

Seminar abstract

Climate sensitivity is temperature deviation from its long-run mean in response to a doubling of carbon dioxide stocks. To find confidence intervals for the climate sensitivity parameter, we write the popular Hasselmann (1976) model as a quasi-cointegrated vector autoregression. The authoritative study of Sherwood et al. (2020) finds this interval to be [2.6, 4.1]. Using quasi-cointegration methods, the maximum likelihood interval is [1.37, 2.17]. The class of model we consider places the global climate on a persistent process that becomes a random walk in the limit with implied equilibria around those disturbances. Necessarily, we obtain a nuisance parameter that regulates persistence. We use the method of Elliott, Mueller, Watson (2015) to eliminate the nuisance parameter and find a confidence interval based on a most powerful test.

How to attend this seminar

This seminar will take place online on Wednesday 15 March at 2pm. 

This seminar is free to attend. Please contact Professor Robert Taylor for the details on how to join.

Speaker bio

Dr Jerome Simons

Jerome obtained his first degrees in Mathematics and Physics at Johns Hopkins University, Baltimore, USA. He then worked as a staff physicist and expert witness in environmental law for an NGO in Washington, D.C. Afterwards, he moved to the United Nations to work as a researcher on climate change-proof infrastructure interventions. Before pursuing his MPhil and DPhil degrees in Economics at Oxford, Jerome was a financial software developer for the World Bank. He is now a Postdoctoral Researcher at the University of Cambridge.