Dynamic Modeling of Energy Data: World Crude Oil and Coal Prices 2017-2023 (A State-Space Model Analysis of Multivariate Time Series) - Russel, Edwin; Wamiliana; Usman, Mustofa; Elfaki, Faiz AM; Adnan, Arisman; Lindrianasari (Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya, 2025)
The analysis of global crude oil and coal prices has attracted considerable research interest, as these prices significantly affect both society and industry, making the topic highly relevant for governments and policy makers. This study examines the correlation between global coal and crude oil prices from 2017 to 2023. It analyzes the behavior of these price series using a unit root test and develops an optimal model for conducting a Granger-causality analysis. To forecast crude oil and coal prices for the next 30 periods, a state-space modeling approach is applied. The unit root test results reveal that these prices are non-stationary, suggesting that any shocks to prices will have persistent effects. The best-fitting model for the association between coal and crude oil prices is a vector autoregressive model of order two (VAR(2)). The Granger-causality results reveal that current crude oil prices are influenced by both their own past values and previous coal prices, and vice versa. Forecasts using the state-space model suggest a modest upward trend for crude oil prices over the next 30 periods, while coal prices are projected to rise more strongly.