Theoretical foundations of time series analysis in green economy
DOI:
https://doi.org/10.5281/zenodo.15351926Keywords:
Time series analysis, green economy, ARIMA model, renewable energy, CO₂ emissions, green investment, environmental modeling, sustainable developmentAbstract
The rapid global shift towards environmentally sustainable development necessitates advanced analytical
methods to monitor and predict environmental and economic indicators. This paper presents a comprehensive theoretical
and empirical analysis of time series methodologies applied to the green economy. It focuses on renewable energy
production, green investment flows, and carbon dioxide (CO₂) emissions. Utilizing real-world data from 2010 to 2023,
the study employs classical time series techniques, stationarity diagnostics, and ARIMA modeling to uncover trends
and forecast future dynamics. The results confirm that policy-driven strategies have contributed to a consistent rise
in renewable energy generation and green investment while effectively reducing CO₂ emissions. The ARIMA-based
forecasts offer robust short- and medium-term insights to support informed decision-making in environmental and energy
policy. The findings underscore the importance of statistical forecasting in promoting long-term sustainability and offer a
conceptual basis for future research integrating econometric and computational approaches.
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