Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/147367
Authors: 
Lorentzen, Sindre
Osmundsen, Petter
Year of Publication: 
2016
Series/Report no.: 
CESifo Working Paper 6113
Abstract: 
We investigate the potential for statistical forecasting of aggregate oil and gas investment on the Norwegian Continental Shelf (NCS). A unique and detailed dataset containing data from 109 different fields on the NCS between 1970 and 2015 was employed. A set of 1080 autoregressive distributed lag models are evaluated pseudo out-of-sample and tested for data mining by utilizing a Diebold-Mariano hypothesis test and the model confidence set procedure by Hansen and Lunde (2011). The main results are as follows. First, we find that it is indeed possible but challenging to outperform the parsimonious random walk benchmark in an out-of-sample environment. Second, lags of investment growth, crude oil price growth and realized volatility is found to be adequate predictors for the investment growth. Finally, there is a clear benefit from re-estimating the models coefficient at every step.
Subjects: 
investment
oil and gas sector
Norwegian Continental Shelf
pseudo out-of-sample forecasting
JEL: 
C31
C52
D22
D92
E17
E22
E27
G31
Document Type: 
Working Paper

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