Energy stability and decarbonization in developing countries: Random Forest approach for forecasting of crude oil trade flows and macro indicators

Abstract

The paper observes the dependence of the main macroeconomic indicators in developing countries from the change in world prices for crude oil. We analyzed a system of simultaneous equations, which makes it possible to verify some of these hypotheses, and developed the model to forecast the impact of oil prices on budget revenues. The practical significance of this work lies in the structuring of existing knowledge on the impact of oil crisis. The results of this work can be considered confirmation of the hypothesis of the sensitivity of U.S. macroeconomic indicators to the dynamics of oil prices. Outcomes assume stable growth even in the period of shock prices for oil, which is confirmed by the statistics that were used in the model. Deep decarbonization modeling is a trend in industrial facilities that are used by developing countries. The major challenge is the issue of availability that is applicable to the countries that want to utilize this facility in their communities. Industrial modeling toward decarbonization is now a developing mechanism to curb the growing issue of atmospheric pollution. This paper proves the relevance of promoting deep decarbonization applied by the developing countries.