The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey
Matteo Mogliani (),
Olivier Darné and
Economic Modelling, 2017, vol. 64, issue C, 26-39
This paper introduces a new nowcasting model of the French quarterly real GDP growth rate (MIBA), developed at the Banque de France and based on monthly business surveys. The model is designed to target initial announcements of GDP in a mixed-frequency framework. The selected equations for each forecast horizon are consistent with the time frame of real-time nowcasting exercises: the first one includes mainly information on the expected evolution of economic activity, while the second and third equations rely more on information on observed business outcomes. The predictive accuracy of the model increases over the forecast horizon, consistent with the gradual increase in available information. Furthermore, the model outperforms a wide set of alternatives, such as its previous version and MIDAS regressions, although not a specification including also hard data. Further research should evaluate the performance of the MIBA model with respect to promising alternative approaches for nowcasting GDP (e.g. mixed-frequency factor models with targeted predictors), and consider forecast combinations and density forecasts.
Keywords: Nowcasting GDP; Mixed-frequency data; Model selection; Real-time data (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 E37 (search for similar items in EconPapers)
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Working Paper: New estimate of the MIBA forecasting model. Modeling first-release GDP using the Banque de France's Monthly Business Survey and the “blocking” approach (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:64:y:2017:i:c:p:26-39
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