Impact of Accounting for Financial Market Imperfections on the Predictive Power of the DSGE Model of the Russian Economy

The article examines the question whether financial market imperfections improve the forecasting accuracy of the DSGE model of the Russian economy. To do this, a comparison of the predictive power of several versions of DSGE models evaluated on Russian data is made. The two-sector model of a small open economy is used as a base model. The extended version of the model includes a financial accelerator mechanism and considers two alternative estimates of the model: an estimate using the same data set on which the base model is evaluated, and an estimate using market risk premium data. We conclude that the financial accelerator model, estimated using risk premium data, predicts the key macroeconomic variables output and inflation more accurately. At the same time, the remaining variables that were used to estimate the model parameters give worse predictions. As a result, in practice it is recommended to combine both types of models when analyzing and preparing a forecast.