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A Multicointegration Model of Global Climate Change

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  • David I. Stern

    ()
    (Department of Economics, Rensselaer Polytechnic Institute, Troy NY 12180-3590, USA)

Abstract

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.

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Paper provided by Rensselaer Polytechnic Institute, Department of Economics in its series Rensselaer Working Papers in Economics with number 0406.

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Date of creation: Mar 2004
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Handle: RePEc:rpi:rpiwpe:0406

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  1. Johansen, Søren, 1995. "A Stastistical Analysis of Cointegration for I(2) Variables," Econometric Theory, Cambridge University Press, vol. 11(01), pages 25-59, February.
  2. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages S145-59, Supplemen.
  3. Stern, David I., 1993. "Energy and economic growth in the USA : A multivariate approach," Energy Economics, Elsevier, vol. 15(2), pages 137-150, April.
  4. Engsted, Tom & Haldrup, Niels, 1999. " Multicointegration in Stock-Flow Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(2), pages 237-54, May.
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  1. Atmospheric CO2 Concentrations During Ancient Greenhouse Climates were Similar to those Predicted for A.D. 2100
    by David Stern in Stochastic Trend on 2011-02-12 08:09:00
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Cited by:
  1. Travaglini, Guido, 2010. "Dynamic Econometric Testing of Climate Change and of its Causes," MPRA Paper 23600, University Library of Munich, Germany.
  2. Robert K. Kaufmann & David I. Stern, 2004. "A Statistical Evaluation of Atmosphere-Ocean General Circulation Models: Complexity vs. Simplicity," Rensselaer Working Papers in Economics 0411, Rensselaer Polytechnic Institute, Department of Economics.
  3. David I. Stern, 2005. "A Three-Layer Atmosphere-Ocean Time Series Model of Global Climate Change," Rensselaer Working Papers in Economics 0510, Rensselaer Polytechnic Institute, Department of Economics.

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