A Nowcasting Model for Canada: Do U.S. Variables Matter?

Daniela Bragoli and Michele Modugno

No 2016-036, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We propose a dynamic factor model for nowcasting the growth rate of quarterly real{{p}}Canadian gross domestic product. We show that the proposed model produces more accurate nowcasts than those produced by institutional forecasters, like the Bank of Canada, the The Organisation for Economic Co-operation and Development (OECD), and the survey collected by Bloomberg, which reflects the median forecast of market participants. We show that including U.S. data in a nowcasting model for Canada dramatically improves its predictive accuracy, mainly because of the absence of timely production data for Canada. Moreover, Statistics Canada produces a monthly real GDP measure along with the quarterly one, and we show how to modify the state space representation of our model to properly link the monthly GDP with its quarterly counterpart.

Keywords: Nowcasting; Updating; Dynamic Factor Model (search for similar items in EconPapers)
JEL-codes: C33 C53 E37 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2016-04
New Economics Papers: this item is included in nep-for and nep-mac
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Citations: View citations in EconPapers (3)

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http://www.federalreserve.gov/econresdata/feds/2016/files/2016036pap.pdf (application/pdf)

Related works:
Journal Article: A now-casting model for Canada: Do U.S. variables matter? (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2016-36

DOI: 10.17016/FEDS.2016.036

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