Crude oil price point forecasts of the Norwegian GDP growth rate
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Crude oil price point forecasts of the Norwegian GDP growth rate Nima Nonejad1 Received: 27 January 2020 / Accepted: 16 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Given the important role of the petroleum industry in the Norwegian economy, one would assume that changes in the price of crude oil would help greatly improve the accuracy of the Norwegian real gross domestic product growth rate point (density) forecasts out-of-sample. Surprisingly, evidence of one-quarter-ahead out-of-sample point (density) forecast accuracy gain relative to the benchmark model is very weak, at best close to 3%. Furthermore, results from the unconditional equal predictive ability test suggested in Diebold and Mariano (J Bus Econ Stat 13:253–263, 1995) document that these modest gains are not statistically significant. However, the null hypothesis of equal conditional predictive ability as specified in Giacomini and White (Econometrica 74:1545–1578, 2006) is rejected for a number of models. Moreover, by relying on the information provided by the conditioning variables used in the Giacomini and White (2006) test and devising a forecast selection strategy following Granziera and Sekhposyan (Int J Forecast 35:1636–1657, 2019), we succeed at obtaining point forecast accuracy gains as high as 12% relative to the benchmark one-quarter ahead. Keywords Conditional predictability · Crude oil price · Forecast accuracy · Norway · Real GDP growth rate JEL Classification C22 · C53 · E32
1 Introduction The aim of this study is to contribute to the growing number of studies that evaluate the ability of the price of crude oil to forecast the Norwegian real gross domestic product
The views expressed in this paper are our own and do not in any way reflect those of Danske Bank .
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Nima Nonejad [email protected] Danske Bank and CREATES, Laksegade 8, 1063 Copenhagen, Denmark
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N. Nonejad
(GDP) growth rate out-of-sample. Our point of departure is studies, such as Bjørnland et al. (2008), Gerdrup et al. (2009), Aastveit et al. (2011), Bjørnland et al. (2011), Aastveit and Trovik (2012), Bjørnland et al. (2012), Luciani and Ricci (2014) and Akram and Mumtaz (2019). For instance, Bjørnland et al. (2008), Gerdrup et al. (2009), Bjørnland et al. (2011), Aastveit et al. (2011) and Bjørnland et al. (2012) explore the degree to which combining forecasts produced under different univariate and multivariate models further improve forecasts of key Norwegian macroeconomic variables, such as inflation and the real GDP growth rate. Aastveit and Trovik (2012) and Luciani and Ricci (2014) focus on nowcasting the Norwegian real GDP growth rate using factor models. In these studies, the price of crude oil is often employed as a predictor together with other macroeconomic variables. Recently, using a time-varying parameters vector autoregressive (VAR) model with stochastic volatility effects, Akram and Mumtaz (2019) examine the dynamic properties of key Norwegian macroeconomic variables, namely the real GDP gap, CPI infla
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