On the Use of Unit Root Test to Differentiate Between Deterministic and Stochastic Trend in Time Series Analysis

Authors

  • Maxwell Azubuike Ijomah Dept. of Mathematics/Statistics, University of Port Harcourt, Rivers State
  • Dennis Enegesele Dept. of Mathematics/Statistics, University of Port Harcourt, Rivers State

Keywords:

Unit Root, Deterministic trend, Stochastic trend, non-Stationary, Differencing.

Abstract

Deterministic and Stochastic trends in time series have different memory properties. Series with trend are non stationary and must be transformed to be stabilized. The choice of appropriate de-trending procedure depends on the cause of non-stationarity. Mis-specifying the trend characteristics of the data are consequential and can result in biased test and false predictions. This study used the unit root test (ADF) to distinguish between stochastic and deterministic trend in time series analysis. The Nigeria All Share Index (1985-2013) and Nigeria Spot component price of oil (US Dollar per Barrel) data were considered. The results obtained reveals that the Nigeria All Share Index (1985-2013) has a stochastic trend while that of Nigeria Spot component price of oil (US Dollar per Barrel) between 1983-2013; has deterministic trend. Differencing was used to make the Nigeria All Share index data stationary while de-trending was used to remove the deterministic trend Nigeria Spot component price of oil (US Dollar per Barrel).

References

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Published

2017-01-21

How to Cite

Ijomah, M. A., & Enegesele, D. (2017). On the Use of Unit Root Test to Differentiate Between Deterministic and Stochastic Trend in Time Series Analysis. American Scientific Research Journal for Engineering, Technology, and Sciences, 27(1), 234–246. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/2347

Issue

Vol. 27 No. 1 (2017)

Section

Articles

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