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The Synergistic Role of Circular Economy, Energy Transition, Digitalization, and Emissions Trading Systems in Achieving Carbon Reduction in EU Countries
The transition to carbon reduction (CR) is among the key global challenges, at the core of international agreements like the Paris Agreement and the United Nations SDGs. Global net-zero carbon emissions by 2050, with European Union targets set for 2030,… Leggi tutto demand such strategies as the practice of Circular Economy (CE), Energy Transition (ET), Emissions Trading Systems (ETS), and Digitalization (DI). While all these factors are individually impactful, their combined potential, interdependencies, and dynamic interactions remain extensively unexplored. This project will try to find answers to five key questions: (1) evaluate the individual contribution of CE, ET, ETS, and DI towards CR; (2) study the effect of their combination on CR; (3) analyze the causality directions among CE, ET, ETS, DI, and CR; (4) measure the degree and evolution of their connectedness over time; and (5) identify the main driver behind CR and predict CO₂ emissions future trend considering different scenarios. This project proposes a new methodological framework, which combines Directed Acyclic Graph Theory (DAG) to unveil the causal structure, time-varying copula-based dynamic connectedness analysis for measuring evolution of interdependencies, and Support Vector Regression (SVR) for scenario-based forecasting of CO₂ emissions. This study uses annual frequency data, such as total CO₂ emissions, annual percent changes in emissions, recycling rates, renewable energy share, fossil fuel dependency, material footprint, resource productivity, carbon credit prices, traded allowances, internet penetration rates, and UN E-Government Development Index, for the period 2000-2023. Data will be obtained from various open access databases, including European Environment Agency, Eurostat, and World Bank for all the EU member states. This project contributes the CR research domain by addressing several research gaps, by examining interdependencies among CE, ET, ETS, and DI, advancing methodological tools that integrate DAG, time-varying copula, SVR, and exploring how these interdependencies jointly impact CR. Scenario-based forecasting further enhances the practical relevance of the study, with pathways for future CO₂ emissions. Expected results will emphasize the role of CE, ET, ETS, and DI in the optimization of CR strategies, show synergies among them, and also develop actionable, country-specific policy recommendations.