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Semiparametric estimation and testing of the trend of temperature series
Article first published online: 30 JUN 2006
DOI: 10.1111/j.1368-423X.2006.00188.x
Additional Information
How to Cite
Gao, J. and Hawthorne, K. (2006), Semiparametric estimation and testing of the trend of temperature series. The Econometrics Journal, 9: 332–355. doi: 10.1111/j.1368-423X.2006.00188.x
Publication History
- Issue published online: 30 JUN 2006
- Article first published online: 30 JUN 2006
- Received: March 2005
- Abstract
- Article
- References
- Cited By
Keywords:
- Nonparametric kernel;
- Semiparametric estimation;
- Specification testing;
- Trend determination
Summary The application of a partially linear model to global and hemispheric temperature series is proposed. Partially linear modelling allows the trend to take a very general form rather than imposing the restriction of linearity seen in existing studies. The removal of the linearity restriction is based on the fact that it is well accepted that a significant trend is present in global temperature series. The model will allow for the data to ‘speak for themselves’ with regard to the form of the trend. The results initially reveal that a linear trend does not approximate well the behaviour of global or hemispheric temperature series. This is further confirmed through a formal testing procedure.
The results suggest that little faith should be instilled in long-term forecasts of temperatures in which the trend of global and hemispheric series is assumed to be linear. All the current evidence suggest that temperatures will continue to rise in an unknown and probably nonlinear fashion.