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A Dynamic Factor Model for Nowcasting Canadian GDP Growth

Tony Chernis and Rodrigo Sekkel

Staff Working Papers from Bank of Canada

Abstract: This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data. The model is then used to generate nowcasts, predictions of the recent past and current state of the economy. In a pseudo real-time setting, we show that the DFM outperforms univariate benchmarks as well as other commonly used nowcasting models, such as mixed-data sampling (MIDAS) and bridge regressions.

Keywords: Business fluctuations and cycles; Econometric and statistical methods (search for similar items in EconPapers)
JEL-codes: C32 C38 C53 E37 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2017
New Economics Papers: this item is included in nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:bca:bocawp:17-2

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