Public Investments and Forecasting in Renewable Energy Technologies: A Comparative Analysis Using ARIMA and GARCH Models

This paper analyzes public investments in relation to the promotion of renewable energy technologies (RET) within the solar, wind and hydropower, bioenergy industries. Based on historical information, the ARIMA (Auto Regressive Integrated Moving Average) model is used to predict future investment trends, and GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model analyzes the volatility of these investments. Both the models utilized univariate time series data to observe the temporal trends behavior purely based on past investment values without any external variables. Furthermore, a correlation matrix is prepared to determine the degree of interaction between investments in different RETs. The result indicates that public investment is important in supporting RET markets and thus promoting a more sustainable energy transition. Thus, the results of the study presented in the paper are quite encouraging and valuable in terms of policy perspective and future investments in the field of renewable energy generation.