Medium Term Balance-econometric Model of Russian Economy

This study consider medium-term changes in the Russian economy in the case of changes in a certain set of exogenous factors. The aim of the work is to develop a model that defines the relationships between the main variables in the Russian economy, and then forecast them. In accordance with the goal, the following tasks were set: • Consideration of the main tools and approaches to modeling the country's economy; • Making a list of main endogenous and exogenous variables; • Collecting the necessary statistics, as well as pre-processing time series for later use; • Model development – evaluating equations, checking the quality of the model and its predictive properties, and calculating the remaining variables using balance identities; • Scenario forecasting with accordance of the resulting model. The concept of the model is that a set of exogenous and/or previously calculated endogenous variables is used to develop each subsequent variable. This approach avoids simultaneous modeling of the entire economy and simplifies the selection of significant variables. The extended autoregressive integrated moving average model (ARIMAX) was used for econometric estimation of endogenous variables. For each equation, the forecast quality was evaluated for 15 subsequent periods. Then the variables were calculated using the balance ratio. 24 econometric equations and 13 balance identities were obtained. After the final development of the model, scenario forecasting was performed. The result of this study is a model that allows instantly calculate the main indicators of the country's economy based on user-entered exogenous parameters. Thus, the developed model study the behavior of the economy in response to various external shocks and the consequences of using tools to smooth the volatility of economic indicators. However, this model is not universal; it is clearly specified only for the Russian economy. The value of this work is two facts: the use of variables for modeling growth rates, which allows you to most accurately predict the percentage change in variables; and also, this work, one of the few, includes an out-of-sample verification of the quality of forecasting. The research can be continued in the context of a deeper study of all exogenous variables for forecasting of the Russian economy, as well as expanding the list of endogenous variables.