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Short term forecasts of economic activity: are fortnightly factors useful?

Libero Monteforte () and Valentina Raponi ()
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Libero Monteforte: Bank of Italy
Valentina Raponi: Imperial College London and Sapienza University of Rome

No 1177, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: A short term mixed-frequency model is proposed to estimate and forecast the Italian economic activity fortnightly. Building on Frale et al. (2011), we introduce a dynamic factor model with three frequencies (quarterly, monthly and fortnightly), by selecting indicators that show significant coincident and leading properties and are representative of both demand and supply. We find that high-frequency indicators improve the real time forecasts of Italian GDP. Moreover, the model provides a new fortnightly indicator of GDP, consistent with the official quarterly series. Our results emphasize the potential benefit of the high frequency series, providing forecasting gains beyond those based on monthly variables alone.

Keywords: factor models; Kalman filter; temporal disaggregation; mixed frequency data; forecasting (search for similar items in EconPapers)
JEL-codes: C53 E17 E32 E37 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-eec, nep-for and nep-mac
Date: 2018-06
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Persistent link: https://EconPapers.repec.org/RePEc:bdi:wptemi:td_1177_18

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