Theoretical foundations of time series analysis in green economy

Muradov Rustamjon Sobitkhonovich

GREEN ECONOMY AND DEVELOPMENT, 2025, vol. 3, issue 4

Abstract: The rapid global shift towards environmentally sustainable development necessitates advanced analyticalmethods to monitor and predict environmental and economic indicators. This paper presents a comprehensive theoreticaland empirical analysis of time series methodologies applied to the green economy. It focuses on renewable energyproduction, 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 trendsand forecast future dynamics. The results confirm that policy-driven strategies have contributed to a consistent risein renewable energy generation and green investment while effectively reducing CO₂ emissions. The ARIMA-basedforecasts offer robust short- and medium-term insights to support informed decision-making in environmental and energypolicy. The findings underscore the importance of statistical forecasting in promoting long-term sustainability and offer aconceptual basis for future research integrating econometric and computational approaches.

Keywords: Time series analysis; green economy; ARIMA model; renewable energy; CO₂ emissions; green investment; environmental modeling; sustainable development (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:teu:ged000:v:3:y:2025:i:4:id:5167

DOI: 10.5281/zenodo.15351926

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