| Title |
Risk network of global energy markets / |
| Authors |
Uddin, Gazi Salah ; Luo, Tianqi ; Yahya, Muhammad ; Jayasekera, Lokuralahamilage I R ; Rahman, Md Lutfur ; Okhrin, Yarema |
| DOI |
10.1016/j.eneco.2023.106882 |
| Full Text |
|
| Is Part of |
Energy economics.. Amsterdam : Elsevier. 2023, vol. 125, art. no. 106882, p. [1-24].. ISSN 0140-9883. eISSN 1873-6181 |
| Keywords [eng] |
Energy companies ; Systemic risk ; Risk spillover ; High-dimensional network |
| Abstract [eng] |
This study evaluates extreme uncertainty connectedness among top global energy firms. The sample comprises of 68 firms from four energy-related subsectors (oil & gas, oil & gas related equipment and services, multiline utilities, and renewable energy). To provide an overview of tail connectedness, we construct a high-dimensional network between firms by utilizing a generalized error decomposition and a sparse vector autoregression framework with a latent common factor. Our empirical results indicate that between the four subsectors, the renewable energy subsector exhibits the highest uncertainty transmission to other underlying subsectors, primarily credited to an increased within-subsector idiosyncratic uncertainty before the COVID-19 crisis. After the burst of the COVID-19 pandemic, due to the higher connectedness, the role of the renewable energy companies in the spillover network is further intensified. The uncertainty connectedness demonstrates a time-varying trait. While the oil and gas subsector exhibits greater long-term linkages with the oil and gas related equipment and services subsector, the long-run dynamics exhibit a lower interconnectedness as compared to the short-run. Finally, there is an increased connectedness among companies operating in the same subsector with similar size, attributing to similarity and competition. |
| Published |
Amsterdam : Elsevier |
| Type |
Journal article |
| Language |
English |
| Publication date |
2023 |
| CC license |
|
