Some properties of time series data and their use in econometric model specification

Abstract

The impact of geopolitical risk on energy markets has drawn attention to the need for better statistical modeling, especially of the crude oil markets and the shipping industry. In this work, the West Texas Intermediate crude oil price and the Baltic Dry Index behavior under the assumption of geopolitical risks are examined by using monthly data from January 1985 until May 2021. Using fractional integration methods, the results indicate that geopolitical risk and the Baltic Dry Index series will return to their original trends in the event of an exogenous shock, in contrast to the West Texas Intermediate behavior. These results are supported by analyzing the long-term relationship of the time series using the Fractional Cointegration Vector AutoRegressive approach. Finally, we use Bai and Perron (2003) and wavelet transform approaches to detect breaks in the prices paid for the maritime transport and for the crude oil prices caused by geopolitical risks.