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Theoretical foundations of time series analysis in green economy

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  • Muradov Rustamjon Sobitkhonovich

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.

Suggested Citation

  • Muradov Rustamjon Sobitkhonovich, 2025. "Theoretical foundations of time series analysis in green economy," GREEN ECONOMY AND DEVELOPMENT, "Ma'rifat-Print-Media" LLC, Tashkent State University of Economics, vol. 3(4), April.
    • Handle: RePEc:teu:ged000:v:3:y:2025:i:4:id:5167
    DOI: 10.5281/zenodo.15351926
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