TY  - UNPD
A1  - Meyer-Gohde, Alexander
A1  - Shabalina, Ekaterina
T1  - Estimation and forecasting using mixed-frequency DSGE models
T2  - Working paper series / Institute for Monetary and Financial Stability ; 175
N2  - The authors propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting. The second method transforms a quarterly state space into a monthly frequency. Their algorithm combines the advantages of these two existing approaches.They compare the new method with the existing methods using simulated data and real-world data. With simulated data, the new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in their method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
T3  - Working paper series / Institute for Monetary and Financial Stability - 175 
KW  - Mixed-frequency data
KW  - DSGE models
KW  - Forecasting
KW  - Estimation
KW  - Temporal aggregation
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/65695
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-656952
UR  - https://www.imfs-frankfurt.de/de/forschung/imfs-working-papers/details/mm_publication/detail/publication/estimation-and-forecasting-using-mixed-frequency-dsge-models.html
N1  - This research was supported by the DFG through grant nr. 465469938 'Numerical diagnostics and improvements for the solution of linear dynamic macroeconomic models'.
PB  - Johann Wolfgang Goethe-Univ., Inst. for Monetary and Financial Stability
CY  - Frankfurt am Main
ER  -