Dynamic connectedness between oil, European gas and EU carbon allowance prices
Year: 2026
Type: article
Abstract: This study examines shock transmission and directional connectedness among crude oil, European natural gas, and EU carbon allowance markets, focusing on structural changes during the 2022 European energy crisis. Using weekly returns on Brent crude oil, Dutch TTF gas futures, and EU Emissions Trading System (EU ETS) primary-auction allowance prices from November 2017 to December 2025, we employ a time-varying parameter vector autoregressive (TVP-VAR) model and generalized forecast-error variance decomposition. The analysis incorporates full-model bootstrap inference, formal structural-break tests, and extensive robustness checks across model specifications, data frequencies, alternative price series, and an electricity-market extension. Results indicate weak overall connectedness, with cross-market spillovers explaining approximately 10% of forecast-error variance and exhibiting cyclical fluctuations without a sustained trend. In the weekly baseline, connectedness declined by approximately 13 percentage points around Russia’s invasion of Ukraine, accompanied by weaker oil–carbon dependence. However, this decline is not supported by full-model bootstrap inference or daily data. Carbon allowances are net receivers of forecast-error variance in the weekly baseline, primarily from oil through a one-week lag, but this finding is sensitive to sampling frequency and sample period, with bootstrap confidence intervals including zero. Crisis-related changes in carbon’s net position are similarly not robust and differ in sign between weekly and daily data. The electricity extension reveals strong gas-to-electricity spillovers but limited net connectedness between electricity and carbon allowances. Overall, the findings provide no robust evidence that EU carbon allowances became a transmission channel for the 2022 gas shock at the weekly frequency.
Source: Discover Environment
Institutions: Institute of Technology and Business, DTI University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,390
OpenAlex ID: W7225802093