Prediction of economic dynamics using complex-valued auto-regression with a time component (CTAR)

Abstract

Purpose: the article, prepared according to the results of the RFBR grant No. 19-010-00610\19 «Theory, Methods, and Techniques of Forecasting Economic Development by Autoregressive Models of Complex Variables,» is devoted to the problems of modeling and forecasting economic dynamics using methods of complex-valued economics. Discussion: in modern economic forecasting, autoregressive models are actively used. Since quite often we are talking about predicting a system of indicators, vector autoregression is used. An intermediate position between simple autoregression and vector autoregression is integrated autoregression. The properties of complex autoregression, in which one of the components is an indicator of time, are discussed in this article. Results: the author has proposed a new model for short and medium-term forecasting, which has new properties that distinguish it from other autoregressive models. It can be included in the arsenal of tools of modern economic forecasting.