A Multicointegration Model of Global Climate Change
The concept of multicointegration introduced by Granger and Lee (1989) has been little used in economics. This paper demonstrates how it can find a useful application in the econometric analysis of global climate change. Time series models of global climate change tend to estimate a low climate sensitivity (equilibrium effect on global temperature of doubling carbon dioxide concentrations) and a very fast adjustment rate to equilibrium. These results may be biased by omission of a key variable - heat stored in the ocean. A pilot study application illustrates the potential of the multicointegration approach and also demonstrates how partial observations on ocean heat content can be used to constrain the state variable using the Kalman filter. Parameter estimates are much closer to theoretically expected values than those from any existing type of time series model. The estimated climate sensitivity is 4.37K with a 95% confidence interval of 3.6K to 5.1K. However, estimated oceanic heat accumulation appears to correspond to only the heat changes in the upper 300m of the ocean. The pilot model can be elaborated in a number of directions including disaggregating forcings, spatial and vertical resolution, adding a model of the carbon cycle, and testing more complex dynamic specifications.
|Date of creation:||Mar 2004|
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