The current green agenda, the climate change, and sustainability frameworks are closely linked to the successful transition to renewable energy. The study purpose is to estimate the influence of economic and environmental drivers of renewable energy promotion in the EU-27, using the 2013–2021 data for member states. Breusch and Pagan Lagrangian multiplier test and Hausman specification test were performed to determine the proper model specification. Using random-effects GLS regression for selected data, the study found that the rise in the magnitude of the Land-Ocean Temperature Index by one unit contributes to an increase in renewable energy sources by 10-16 percentage points. The rise in natural gas prices in the EU by USD 10 per MMBtu is associated with an average growth of renewable energy sources by 2.1-2.6 percentage points and three percentage points for growth in renewable electricity. An increase in GDP per capita of USD 1,000 led to an average increase in renewable electricity by 0.2 percentage points. An increase in CO2 per capita by one ton is associated with an average decrease in renewable electricity by 0.85 percentage points. This study proves that the critical point of GDP per capita within the “economic growth/renewable energy” nexus when economic stimulus starts to decline was estimated at USD 121,227-148,623. Thus, for countries that have reached the break-even point in GDP per capita, the incentives for introducing renewable energy sources are reduced when the effect of wealth prevails over the impact of environmental awareness and responsibility.

The paper aims to develop and adapt an econometric model for assessing and forecasting the impact of household energy efficiency and renewable energy deployment on reducing energy poverty in Ukraine. Due to the lack of updated statistical data after 2022 caused by the war, the adapted model was tested using pre-war data from the State Statistics Service of Ukraine and the World Bank for 2002-2021. As access to some prewar datasets was also restricted for security reasons in Ukraine, proxy indicators were applied, allowing adaptation to limited information conditions. The modeling results showed that a 1,000 USD increase in GDP per capita reduces the share of the population living below the national poverty line and, accordingly, the energy-poor population, by 3%. Conversely, a 1% increase in gross capital formation raises the energy poverty level by 0.5%, indicating no direct impact of investment in physical capital, including expenses on energy-efficiency measures, on household welfare. Household expenditures on utilities and the share of renewable energy in total energy consumption were found to be statistically insignificant. The study confirms that household income remains the dominant determinant of energy poverty, while improvements in energy efficiency and renewable energy development play supportive but not yet decisive roles. These findings highlight the need to integrate social and energy policies to raise household incomes, improve access to renewable technologies, and promote energy efficiency measures. The developed model offers a tool for enhancing state policies to alleviate energy poverty under wartime constraints and in post-war recovery.