April 2016

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

Daniela Bragoli and Michele Modugno

Abstract:

We propose a dynamic factor model for nowcasting the growth rate of quarterly real 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.

Accessible materials (.zip)

Keywords: Dynamic Factor Model, Nowcasting, Updating

DOI: http://dx.doi.org/10.17016/FEDS.2016.036

PDF: Full Paper

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Last Update: June 19, 2020