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Dynamic GMM Estimation With Structural Breaks. An Application to Global Warming and its Causes

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  • Travaglini, Guido

In this paper I propose a nonstandard t-test statistic for detecting level and trend breaks of I(0) series. Theoretical and limit-distribution critical values obtained from Montecarlo experimentation are supplied. The null hypothesis of anthropogenic versus natural causes of global warming is then tested for the period 1850-2006 by means of a dynamic GMM model which incorporates the null of breaks of anthropogenic origin. World average temperatures are found to be tapering off since a few decades by now, and to exhibit no significant breaks attributable to human activities. While these play a minor causative role in climate changes, most natural forcings and in particular solar sunspots are major warmers. Finally, in contrast to widely held opinions, greenhouse gases are in general temperature dimmers.

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File URL: https://mpra.ub.uni-muenchen.de/7108/1/MPRA_paper_7108.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 7108.

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Date of creation: 11 Feb 2008
Handle: RePEc:pra:mprapa:7108
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  16. repec:cup:etheor:v:13:y:1997:i:6:p:818-49 is not listed on IDEAS
  17. Antonio E. Noriega & Daniel Ventosa-Santaularia, 2005. "Spurious regression under broken trend stationarity," Department of Economics and Finance Working Papers EM200501, Universidad de Guanajuato, Department of Economics and Finance.
  18. Vogelsang, Timothy J., 1997. "Wald-Type Tests for Detecting Breaks in the Trend Function of a Dynamic Time Series," Econometric Theory, Cambridge University Press, vol. 13(06), pages 818-848, December.
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