Forecastability and Statistical Characteristics of Aggregate Oil and Gas Investments on the Norwegian Continental Shelf

29 Pages Posted: 10 Nov 2016

See all articles by Sindre Lorentzen

Sindre Lorentzen

University of Stavanger

Petter Osmundsen

University of Stavanger; CESifo (Center for Economic Studies and Ifo Institute)

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Date Written: October 11, 2016

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.

Keywords: Investment, Oil and Gas Sector, Norwegian Continental Shelf, Pseudo Out-Of-Sample Forecasting

JEL Classification: C310, C520, D220, D920, E170, E220, E270, G310

Suggested Citation

Lorentzen, Sindre and Osmundsen, Petter, Forecastability and Statistical Characteristics of Aggregate Oil and Gas Investments on the Norwegian Continental Shelf (October 11, 2016). CESifo Working Paper Series No. 6113, Available at SSRN: https://ssrn.com/abstract=2867310 or http://dx.doi.org/10.2139/ssrn.2867310

Sindre Lorentzen

University of Stavanger ( email )

PB 8002
Stavanger, 4036
Norway

Petter Osmundsen (Contact Author)

University of Stavanger ( email )

4036 Stavanger
Norway

CESifo (Center for Economic Studies and Ifo Institute) ( email )

Poschinger Str. 5
Munich, DE-81679
Germany

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