This paper proposes a novel unobserved component model with a COVID-19 structural break in the trend growth rate to model output gaps. Using historical real GDP data for the Euro Area between 1995Q1 and 2022Q1, we test our framework against a battery of competing models, including a standard unobserved components model, a correlated model with a second-order Markov process, a Hodrick–Prescott filter and an augmented version of it. To examine the impact on the fitting performance, we test the inclusion and exclusion of pandemic quarters and we also extend the estimation to a country-level detail. We find that: (i) our suggested model outperforms the competing ones; (ii) when excluding pandemic quarters, the standard unobserved component model outperforms their counterparts; (iii) our model yields the best fitting performance for most of the Euro Area countries and (iv) the Hodrick–Prescott filter model has the poorest fitting performance.

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Euro Area,COVID-19,HP filter,Output gaps,Trend-cycle decomposition,Unobserved component models

• Economia e Gestão - Ciências Sociais