Stochastic Simulation of the FR-BDF Model and an Assessment of Uncertainty around Conditional Forecasts

Harry Turunen, Anastasia Zhutova and Matthieu Lemoine

Working papers from Banque de France

Abstract: This paper presents a framework to introduce uncertainty into the FR-BDF model, used for macroeconomic projections and policy analysis at the Banque de France. Belonging to the semi-structural class of large-scale macroeconomic models, it is only fair to assume that FR-BDF may suffer from various types of misspecification. We do not seek to correct the latter, but instead we study its systematic nature using unobserved component models for the residuals of FR-BDF. Stochastic simulations based on random draws of innovations of these models allow us to work with applications that describe probabilities of events and risk in general. Applying this framework to the December 2022 forecast exercise of Banque de France, based on the available information at that time, the highest probability of observing a technical recession occurs in 2023Q2 and reaches 42%.

Keywords: Semi-Structural Modelling; Stochastic Simulation; Unobserved Component Model (search for similar items in EconPapers)
JEL-codes: C54 E37 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2023
New Economics Papers: this item is included in nep-cmp
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Persistent link: https://EconPapers.repec.org/RePEc:bfr:banfra:920

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