The Test of Non-Linearity of Unit Root in Crude Oil Prices

Abstract

There is good reason to expect crude oil prices to follow nonlinear models. However, previous research has considered the linear assumption to investigate the existence of a unit root. Unit root linear tests such as ADF, PP, and KPSS are provided for linear models. These tests are not suitable for nonlinear time series. Because the model deviation from the linear state may be considered as a random permanent deviation. The purpose of this article is to test the nonlinear unit root of crude oil prices, specifically Brent and WTI oil in the period 2019-2020 daily. For several decades now, various classes of nonlinear models have been introduced. These models introduce a wider range of dynamics than linear models in time series. A special type of these models that economists pay attention to are TAR models. In these models, as in linear models, valid statistical analysis requires distinguishing between the deterministic trend and the stochastic trend. In this study, the Bayesian unit root test for the general SETAR (1) model has been used with respect to the necessary and sufficient conditions for the maintenance of SETAR processes based on the article by Petrocyl and Wolford (1984). A nonlinear unit root test was performed using Bayesian validity interval. The results show that Brent crude oil prices in both regimes contain a unit root that is consistent with similar findings for the production or consumption of crude oil..

Keywords

• bayesian nonlinear unit root tests
• tar nonlinear time series
• simulation
• brent crude oil
• financial econometrics