A dynamic factor model for nowcasting Canadian GDP growth

by Tony Chernis and Rodrigo Sekkel

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.

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Year of publication:	February 2017
Authors:	Chernis, Tony ; Sekkel, Rodrigo
Publisher:	[Ottawa] : Bank of Canada
Subject:	Econometric and statistical methods \| Business fluctuations and cycles \| Konjunktur \| Business cycle \| Kanada \| Canada \| Prognoseverfahren \| Forecasting model \| Wirtschaftsprognose \| Economic forecast \| Faktorenanalyse \| Factor analysis \| Zeitreihenanalyse \| Time series analysis \| Bruttoinlandsprodukt \| Gross domestic product \| Statistische Methode \| Statistical method \| Frühindikator \| Leading indicator \| Wirtschaftswachstum \| Economic growth

Extent:	1 Online-Ressource (circa 29 Seiten) Illustrationen
Series:	Staff working paper / Bank of Canada. - Ottawa : [Verlag nicht ermittelbar], ISSN 1701-9397, ZDB-ID 2278568-1. - Vol. 2017, 2
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Arbeitspapier ; Working Paper ; Graue Literatur ; Non-commercial literature
Language:	English
Notes:	Zusammenfassung in französischer Sprache
Other identifiers:	hdl:10419/171956 [Handle]
Classification:	c38 ; C32 - Time-Series Models ; C53 - Forecasting and Other Model Applications ; E37 - Forecasting and Simulation
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10011592353