<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article characterizes a dynamic crude oil trade network of Eastern Europe and Eurasia using the network connectedness measure of Diebold and Yilmaz (2014, 2015) and asymmetric reaction of crude oil bilateral trade flow in response to the positive and negative changes of its key determinants using the nonlinear panel ARDL model. Results indicate the existence of large and time-varying spillovers with a considerable explanatory power among the crude oil trade flow volatility of Iran, Russia, US and Saudi Arabia in Eastern Europe and Eurasia crude oil trade network. The findings also show that crude oil trade flow of Eastern Europe and Eurasia experiences net volatility transmission to Iran, Russia and US respectively, whereas it is a net volatility receiver from Saudi Arabia. Also based on gravity models, the analysis confirms the existence of impact, reaction and adjustment asymmetry through different magnitude among network participants.</p></abstract>

This article characterizes a dynamic crude oil trade network of Eastern Europe and Eurasia using the network connectedness measure of Diebold and Yilmaz (2014, 2015) and asymmetric reaction of crude oil bilateral trade flow in response to the positive and negative changes of its key determinants using the nonlinear panel ARDL model. Results indicate the existence of large and time-varying spillovers with a considerable explanatory power among the crude oil trade flow volatility of Iran, Russia, US and Saudi Arabia in Eastern Europe and Eurasia crude oil trade network. The findings also show that crude oil trade flow of Eastern Europe and Eurasia experiences net volatility transmission to Iran, Russia and US respectively, whereas it is a net volatility receiver from Saudi Arabia. Also based on gravity models, the analysis confirms the existence of impact, reaction and adjustment asymmetry through different magnitude among network participants.

A Dynamic Network Comparison Analysis of Crude Oil Trade: Evidence from Eastern Europe and Eurasia

Zagreb International Review of Economics and Business

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

This article characterizes a dynamic crude oil trade network of Eastern Europe and Eurasia using the network connectedness measure of Diebold and Yilmaz (2014,...

A Dynamic Network Comparison Analysis of Crude Oil Trade: Evidence from Eastern Europe and Eurasia

Online veröffentlicht: 08. Juni 2020

Seitenbereich: 95 - 119

DOI: https://doi.org/10.2478/zireb-2020-0007

Schlüsselwörter
Crude Oil Trade, Dynamic Network Connectedness Measure, Gravity Model, Nonlinear Panel ARDL Model

© 2020 Masoud Shirazi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

A Dynamic Network Comparison Analysis of Crude Oil Trade: Evidence from Eastern Europe and Eurasia

Online veröffentlicht: 08. Juni 2020

Seitenbereich: 95 - 119

DOI: https://doi.org/10.2478/zireb-2020-0007

SchlüsselwörterCrude Oil Trade, Dynamic Network Connectedness Measure, Gravity Model, Nonlinear Panel ARDL Model

© 2020 Masoud Shirazi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
Crude Oil Trade, Dynamic Network Connectedness Measure, Gravity Model, Nonlinear Panel ARDL Model