Nowcasting Italian GDP growth: a Factor MIDAS approach

Donato Ceci (), Orest Prifti and Andrea Silvestrini
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Donato Ceci: Bank of Italy
Orest Prifti: Università degli Studi di Roma-Tor Vergata

No 1446, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: This paper examines the role of weekly financial data in nowcasting the quarterly growth rate of Italian real GDP, with a specific focus on the impact of the COVID-19 pandemic. It combines factor models and MIxed DAta Sampling (MIDAS) regression models to set up Factor MIDAS specifications, which leverage a large set of higher-frequency financial variables to exploit the information flow within the quarter. The analysis is performed using a comprehensive dataset that includes monthly macroeconomic data and weekly financial data. The predictive accuracy is assessed by conducting a pseudo out-of-sample nowcast exercise and evaluating the performance of the models with and without the inclusion of factors derived from financial indicators. Financial variables improve the nowcast of real GDP growth in Italy, particularly in the first month of the quarter, when few macroeconomic data are available. The models incorporating financial variables consistently exhibit high nowcasting accuracy throughout the quarter.

Keywords: nowcasting; mixed frequency; factor models; variable selection; financial markets; factor MIDAS (search for similar items in EconPapers)
JEL-codes: C22 C43 C53 C55 E32 E37 (search for similar items in EconPapers)
Date: 2024-03
New Economics Papers: this item is included in nep-ban, nep-eec and nep-fdg
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