Polynomial cointegration tests of anthropogenic impact on global warming

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 gases 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. This implies that recent global warming is not statistically significantly related to anthropogenic forcing. On the other hand, we find that greenhouse gas forcing might have had a temporary effect on global temperature

Statistically derived contributions of diverse human influences to twentieth-century temperature changes

“…These results would erroneously lead to the argument that these series are at least integrated of order one. Applying the ADF test to the first-differenced synthetic series to test for a possible integration of order two, the results are very similar to those described in some cointegration-based attribution studies 5,51 : temperatures are found to be integrated of order one while radiative forcing series are integrated of order two. These results are spurious and, as shown in the literature, they may lead to contrasting cointegration results and inferences depending on the order of integration selected.…”

“…A recent publication based on polynomial cointegration 51 has proposed that both solar irradiance and global temperature series are integrated of order one, while greenhouse gases and aerosols forcing are integrated of order two. These authors find that, although greenhouse gases and aerosols forcing cointegrate to an integration order of one, the stochastic trend in temperatures and in the aggregated anthropogenic forcing are independent, precluding the existence of a long-term relationship between them.…”

Comment on "Polynomial cointegration tests of anthropogenic impact on global warming" by Beenstock et al. (2012) – some hazards in econometric modelling of climate change

“…In their empirical statistical study of temperature and radiative forcing of greenhouse gases, Beenstock et al (2012) present statistical tests that purport to show that these variables have different integrability properties, and hence cannot be related unless they polynomially cointegrate. Beenstock et al (2012) then show that their constructed measure of anthropogenic forcing, an "anthropogenic anomaly", does not cointegrate with observed temperature, presenting this as evidence against anthropogenic global warming.…”

“…We outline six important hazards that can be encountered in econometric modelling of time-series data, and apply that analysis to demonstrate errors in the empirical modelling of climate data in Beenstock et al (2012). We show that the claim made in Beenstock et al (2012) as to the different degrees of integrability of CO 2 and temperature is incorrect. In particular, the level of integration is not constant and not intrinsic to the process.…”

“…In particular, the level of integration is not constant and not intrinsic to the process. Further, we illustrate that the measure of anthropogenic forcing in Beenstock et al (2012), a constructed "anthropogenic anomaly", is not appropriate regardless of the time-series properties of the data. …”