USE OF MACHINE LEARNING METHODS IN FORECASTING INDICATORS OF FISCAL AND MONETARY POLICY COORDINATION FOR THE ECONOMY OF UZBEKISTAN

Abstract

This paper proposes a new type of solution for Uzbekistan economy using several machine learning methods: LASSO, Ridge, Random Forest, Gradient Boosting and Artificial Neural Networks. This paper is one of the first attempts to apply machine learning methods to the macroeconomic forecasting in Uzbekistan. The main result of this paper is the confirmation of the possibility of more accurate forecasting of economic indicators in Uzbekistan using machine learning methods.