Nowcasting Russian GDP in a mixed-frequency DSGE model with a panel of non-modelled variables

Alexander Eliseev ()
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Alexander Eliseev: Bank of Russia, Russian Federation

No wps145, Bank of Russia Working Paper Series from Bank of Russia

Abstract: This study focuses on improving the accuracy of nowcasting in DSGE models. We extend one of the general equilibrium models of the Russian economy by incorporating mixed-frequency data. Specifically, we introduce an equation that links a panel of non-modelled high-frequency indicators to observable variables, whose dynamics are determined directly by the model. The out-of-sample pseudo-real-time forecasting procedure demonstrates that incorporating these additional variables enhances the accuracy of Russian GDP nowcasting using the DSGE model. This improvement makes the model’s forecasts comparable in accuracy to state-of-the-art econometric models and superior to univariate models. We also investigate the extent to which fluctuations in high-frequency indicators are associated with macroeconomic factors, as well as the economic shocks driving the explained portion of these fluctuations. While the structural interpretation of non-modelled variables is a potential strength of the model, caution is warranted due to the econometric methodology employed.

Keywords: nowcasting; GDP; DSGE model; mixed frequency data; pseudo real-time forecasting (search for similar items in EconPapers)
JEL-codes: C53 C82 E32 E37 (search for similar items in EconPapers)
Pages: 73 pages
Date: 2025-02
New Economics Papers: this item is included in nep-dge
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