Author:
Beenstock M.,Reingewertz Y.,Paldor N.
Abstract
Abstract. We use statistical methods for nonstationary time series to test the anthropogenic interpretation of global warming (AGW), according to which an increase in atmospheric greenhouse gas concentrations raised global temperature in the 20th century. Specifically, the methodology of polynomial cointegration is used to test AGW since during the observation period (1880–2007) global temperature and solar irradiance are stationary in 1st differences, whereas greenhouse gas and aerosol forcings are stationary in 2nd differences. We show that although these anthropogenic forcings share a common stochastic trend, this trend is empirically independent of the stochastic trend in temperature and solar irradiance. Therefore, greenhouse gas forcing, aerosols, solar irradiance and global temperature are not polynomially cointegrated, and the perceived relationship between these variables is a spurious regression phenomenon. On the other hand, we find that greenhouse gas forcings might have had a temporary effect on global temperature.
Subject
General Earth and Planetary Sciences
Reference57 articles.
1. Banerjee, A., Dolado, J. J., Galbraith, J. W., and Hendry, D. F.: Cointegration, Error Correction, and the Econometric Analysis of Non-stationary Data, Oxford University Press, 1993.
2. Choi, I. and Saikkonen, P.: Tests for nonlinear cointegration, Econom. Theory, 26, 682–709, 2010.
3. Crowley, T. J.: Causes of climate change over the past 1000 years, Science, 289, 270–277, 2000.
4. Davidson, R. and MacKinnon, J. G.: Econometric Theory and Methods, Oxford University Press, 2009.
5. Dickey, D. A. and Fuller, W. A.: Likelihood ratio statistics for autoregressive time-series with a unit root, Econometrica, 49, 1057–1072, 1981.
Cited by
29 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献