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Climate change presents a substantial impediment for the global community and prompts policymakers worldwide to prioritize environmental goals when defining national development strategies. Prioritizing these goals is particularly challenging for governments of developing economies still relying on fossil fuels, foreign capital, and industry contribution to GDP. This study examines the relationships between carbon dioxide emissions, industry value added, financial development, and electricity generation in 15 Central and Eastern European countries from 1995 to 2021. To achieve this objective, we examined stationarity and cointegration and employed a vector error correction model to investigate causalities between the variables, along with a variance decomposition analysis. Our findings suggest that the short-run unidirectional causalities exist from industry value-added to carbon dioxide emissions and from carbon dioxide emissions to financial development and electricity generation. Long-term causality exists between carbon dioxide emissions and industry value added. The findings shed light on the challenges and opportunities these countries face in transitioning to climate neutrality and meeting the decarbonization targets. Within this context, the findings underscore the significance of crafting customized strategies for these economies to navigate the complex landscape of climate change while promoting sustainable industrial, electricity and financial sector development. [ABSTRACT FROM AUTHOR]

Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO2 emissions, economic growth, electricity consumption, and trade openness in Serbia. Initially, an Autoregressive Distributed Lag (ARDL) model is used to characterize the Environmental Kuznets Curve (EKC) using data from the period from 1995 to 2019, followed by the construction of a bootstrap logistic regression model to predict environmental quality in Serbia. Long-term estimates of the model confirm an inverted U-shaped relationship, where all three variables exert a statistically significant influence on CO2 emissions. In the short run, however, a causal relationship is only observed between electricity consumption and CO2 emissions. The logistic regression results show that all three factors significantly influence environmental quality. The study proposes policy recommendations for Serbia, such as promoting sustainable economic growth, implementing long-term programs to reduce CO2 emissions, reviewing trade policies to prioritize sustainable practices, and investing in renewable energy sources to reduce emissions. [ABSTRACT FROM AUTHOR]