 A now-casting model for Canada: Do U.S. variables matter?Daniela Bragoli and Michele Modugno International Journal of Forecasting, 2017, vol. 33, issue 4, 786-800 Abstract: We propose a dynamic factor model for now-casting the growth rate of the quarterly real Canadian gross domestic product. We select a set of variables that are monitored by market participants, track their release calendar, and use vintages of real-time data to reproduce the information sets that were available at the time when the forecasts would have been made. The accuracy of the forecasts produced by the model is comparable to those of the forecasts made by the market participants and institutional forecasters. We show that including U.S. data in a now-casting model for Canada improves its predictive accuracy dramatically, 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 the state space representation of our model can be modified to link the monthly GDP properly with its quarterly counterpart. Keywords: Now-casting; Updating; Dynamic factor model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:33:y:2017:i:4:p:786-800 DOI: 10.1016/j.ijforecast.2017.03.002 Access Statistics for this article International Journal of Forecasting is currently edited by R. J. Hyndman More articles in International Journal of Forecasting from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.