Is Radiative Forcing Cointegrated with Temperature? A Further Examination Using a Structural Time Series Approach

Balcombe, Kelvin and Fraser, Iain and Sharma, Abhijit (2012): Is Radiative Forcing Cointegrated with Temperature? A Further Examination Using a Structural Time Series Approach.

Abstract

This paper re-examines the relationship between radiative forcing and temperatures from a structural time series modelling perspective. The results confirm that cointegration between radiative forcing and temperatures are consis- tent with the data. However, we produce results for which the cointegration between forcing and temperature data finds less support than previously. A Bayesian approach is used to obtain estimates that better represents the uncertainty regarding this relationship. We show that while a cointegrating relationship represents an acceptable characterisation of the relationship between these variables, another equally acceptable model exists in which there is no cointegration, and the relationship between forcing and temperature is insignificant.

• Item Type: MPRA Paper
• English Title: This paper re-examines the relationship between radiative forcing and temperatures from a structural time series modelling perspective. The results confirm that cointegration between radiative forcing and temperatures are consis- tent with the data. However, we produce results for which the cointegration between forcing and temperature data finds less support than previously. A Bayesian approach is used to obtain estimates that better represents the uncertainty regarding this relationship. We show that while a cointegrating relationship represents an acceptable characterisation of the relationship between these variables, another equally acceptable model exists in which there is no cointegration, and the relationship between forcing and temperature is insignificant.
• Language: English
• Keywords: Radiative forcing; cointegration; structural time series
• Subjects: Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q53 - Air Pollution ; Water Pollution ; Noise ; Hazardous Waste ; Solid Waste ; Recycling; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q5 - Environmental Economics > Q54 - Climate ; Natural Disasters and Their Management ; Global Warming

References

Gerlagh R. and Zwaan B. Van Der. 2006. Options and Instruments for a Deep Cut in CO2 emissions: Carbon dioxide capture or renewables, taxes or subsidies?. The Energy Journal 27(3): 2548.

Harvey A.C. (1989). Forecasting Structural Time Series Models and the Kalman Filter. Cambridge University Press.

Van Heerden J., Gerlagh R., Blignaut, J., Horridge M., Hess S., Mabugu R. and Mabugu M. 2006. Searching for triple dividends in South Africa: Fighting CO2 pollution and poverty while promoting growth. The Energy Journal 27(2): 113142.

Johansen S. (1995). Likelihood-Based Infernce in Cointegrated Vector Auto- Regressive Models, Advanced Tests in Econometrics. Oxford University Press. Oxford.

Kaufmann R.K., Kauppi, H. and Stock, J.H. (2006). The Relationship Be- tween Radiative Forcing and Temperature: What do Statistical Analyses of the Instrumental Temperature Record Measure? Climatic Change. 77: 279-289.

Kaufmann R.K. and Stern D.I. (2002). Cointegration Analysis of Hemi- spheric Temperature Relations. Journal of Geophysical Research, 107 (D2), article No. 4012.