USING DIGITAL TECHNOLOGIES TO DEVELOP THE GREEN ECONOMY
DOI:
https://doi.org/10.46808/iitp.v3i1.97Kata Kunci:
Digital technologies, green economy, econometric analysis, digital transformation, panel regression, VECM, cointegration, energy efficiency, investment stabilityAbstrak
In this study, the relationship between digital technologies and the green economy is empirically assessed, and their impact on economic development and environmental sustainability is analyzed based on econometric modeling. Within the scope of the research, panel regression and VECM models were applied using the database of Uzbekistan, Kazakhstan, Russia, Belarus, and European Union countries (Germany, Poland, Italy) for the period 2015–2023. The results show that the implementation of digital technologies significantly increases green economy indicators (GEI), with a 1% increase potentially leading to a 0.42-point rise in the green economy index. Long-term analysis revealed the existence of cointegration between digital infrastructure and the green economy, with a 1-point increase in the DTI raising the GEI by 0.61 points. The analysis results were interpreted within the framework of Sustainable Development Theory and the Porter Hypothesis. The research confirmed that digital technologies play an important role in energy efficiency, waste reduction, ecological transformation, and investment stability. In the case of Uzbekistan, between 2019 and 2023, the share of renewable energy increased from 10.5% to 21.8%, and the introduction of digital management systems led to a significant reduction in energy losses. International comparisons showed that CO₂ emissions in the European Union decreased by up to 35–40%, while energy efficiency in Russia and Kazakhstan increased by 12–15% due to digital innovations. The practical significance of the research is that digital technologies act as a strong catalyst in the transition to a green economy. The research results serve as a scientific basis for developing effective solutions based on IoT, artificial intelligence, and big data in the fields of energy, agriculture, and industry. For future research, it is recommended to use advanced econometric approaches such as dynamic panel GMM and Bayesian VAR to study the long-term economic impact of digital transformation in greater depth.