Climate Change, Socioeconomic Vulnerability and Climate-Related Economic Losses in the European Union: Evidence from Fixed-Effects Panel Models (2015–2023)
Juan Antonio Torrents Arevalo, Rosella de NiscoClimate change represents one of the most significant sustainability challenges facing contemporary societies, generating substantial environmental, economic, and social impacts across multiple spatial scales (This study examines the associations between climate-related economic losses, measured as the logarithm of climate-related losses relative to GDP (Log Loss Ratio), and climatic, environmental, and socioeconomic factors across the 27 European Union Member States over the period 2015–2023. The explanatory variables include annual average temperature, greenhouse-gas emissions, renewable-energy deployment, unemployment, and the At-risk-of-Poverty Rate. A panel-based empirical framework was applied, combining multiple linear regression and mixed-effects models with a country and year fixed-effects specification as the principal robustness check. The baseline and mixed-effects models indicate statistically significant positive associations between the Log Loss Ratio and temperature, greenhouse-gas emissions, renewable-energy deployment, and the At-risk-of-Poverty Rate, while unemployment is not statistically significant. However, the fixed-effects specification provides a more stringent assessment by controlling for time-invariant country-specific characteristics and common year effects. Under this specification, temperature, greenhouse-gas emissions, renewable-energy deployment, and unemployment are no longer statistically significant, whereas the At-risk-of-Poverty Rate remains statistically significant (p = 0.049). These findings indicate that some associations identified in the baseline models may partly reflect persistent differences between countries, while socioeconomic vulnerability retains explanatory relevance when country-specific and temporal effects are controlled for. The results should therefore be interpreted as conditional statistical associations rather than causal effects and highlight the importance of integrating socioeconomic vulnerability into climate adaptation and resilience policies.