A dynamic factor model for nowcasting Canadian GDP growth - Tony Chernis; Rodrigo Sekkel (Bank of Canada, 2017)
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: C38; C32; C53; E37; 330; Econometric and statistical methods; Business fluctuations and cycles