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Modelling the asymmetric relationship between energy and CO2 emissions in the Visegrad group: empirical evidence from a panel NARDL approach

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Suproń B.

Statistics in Transition new series

2025

vol. 26

issue 3

155-180

The study aims to understand the impact of renewable energy consumption, non-renewable energy consumption, and economic growth on carbon dioxide (CO2) emissions per capita (measured in metric tonnes) in the Visegrad countries between 1991 and 2021. Using a Nonlinear Autoregressive Distributed Lag (NARDL) model for panel data, the research captures both long-term dependencies and short-term dynamics. The results show that a reduction in CO2 emissions yielded by a significant long-term decrease in non-renewable energy consumption is proportionally larger than the increase in the emissions caused by the growth in the consumption of such energy. What is more, GDP growth in the V4 countries increases CO2 emissions, but GDP decline contributes significantly more to the reduction in emissions. In contrast, renewable energy consumption consistently reduces CO2 emissions over the long term, with no significant asymmetry detected. In the short term, both economic growth and non-renewable energy consumption increase CO2 emissions. The error correction factor suggests a rapid adjustment of CO2 emissions towards a longterm equilibrium, with a decreasing trend over time. These results have some policy implications, i.e. they suggest that for the V4 countries, increasing investment in technologies and solutions that improve energy efficiency will be crucial for reducing nonrenewable energy consumption and, consequently, CO2 emissions, without negatively impacting economic growth. Additionally, stable and long-term promotion of renewable energy should be a policy priority in order to effectively contribute to emission reductions.

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1 Statistics in Transition new series

1 Suproń B.

1 2025

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Modelling the asymmetric relationship between energy and CO2 emissions in the Visegrad group: empirical evidence from a panel NARDL approach