Semiparametric estimation and testing of the trend of temperature series

The applicationof 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 o...

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Bibliographic Details
Published in:The econometrics journal 2006-01, Vol.9 (2), p.332-355
Main Authors: Gao, Jiti, Hawthorne, Kim
Format: Article
Language:English
Subjects:
Climate change
Econometrics
Economic models
Economic trends
Estimation
Forecasts
Global climate models
Global warming
International
International environmental cooperation
Kernel estimation
Linear models
Nonparametric kernel
Polynomials
Semiparametric estimation
Series convergence
Significance tests
Specification testing
Studies
Temperature
Time series
Time series models
Trend determination
Trends
Weather forecasting
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Summary:The applicationof 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.
ISSN:1368-4221
1368-423X
DOI:10.1111/j.1368-423X.2006.00188.x