The U.S. Federal Reserve responded to the great recession by implementing quantitative easing, or large‐scale asset purchases, when its conventional policy rate reached the zero lower bound. We assess the international spillover effects of this quantitative easing program on the Canadian economy in a factor‐augmented vector autoregression (FAVAR) framework, by considering a counterfactual scenario in which the Federal Reserve's long‐term asset holdings do not rise in response to the recession. We find that U.S. quantitative easing boosted Canadian output, mainly through the financial channel.

No abstract

Summary This paper studies the effects of a conventional monetary policy shock in the USA during times of high financial stress. The analysis is carried out by introducing a smooth transition factor model where the transition between states (‘normal’ and high financial stress) depends on a financial conditions index. Employing a quarterly dataset over the period 1970:Q1 to 2008:Q4 containing 108 US macroeconomic and financial time series, I find that a monetary policy shock during periods of high financial stress has stronger and more persistent effects on macroeconomic variables such as output, consumption and investment than it has during ‘normal’ times. Differences in effects among the regimes seem to originate from nonlinearities in both components of the credit channel, i.e. the balance sheet channel and the bank‐lending channel. Copyright © 2016 John Wiley & Sons, Ltd.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AcknowledgementsWe thank Marta Banbura for sharing her Matlab codes and Domenico Giannone for his insightful comments. We would also like to thank seminar participants at the Bank of Canada for helpful comments and suggestions. Bryce Shelton provided excellent research assistance.iii AbstractEmerging-market economies have become increasingly important in driving global GDP growth over the past 10 to 15 years. This has made timely and accurate assessment of current and future economic activity in emerging markets important for policy-makers not only in these countries but also in advanced economies. This paper uses state-of-theart dynamic factor models (DFMs) to nowcast real GDP growth in five major emerging markets-Brazil, Russia, India, China and Mexico ("BRIC+M"). The DFM framework allows us to efficiently handle data series characterized by different publication lags, frequencies and sample lengths. This framework is particularly suitable for emerging markets for which many indicators are subject to significant publication lags and/or have been compiled only recently. The methodology also allows us to extract model-based "news" from a data release and assess the impact of this news on nowcast revisions. Results show that the DFMs generally outperform simple univariate benchmark models for the BRIC+M. Overall, our results suggest that the DFM framework provides reliable nowcasts for GDP growth for the emerging markets under consideration. JEL classification: C33, C53, E37 Bank classification: Econometric and statistical methods; International topics RésuméAu cours des dix à quinze dernières années, les économies de marché émergentes ont pris une place grandissante dans la croissance du PIB mondial. C'est pourquoi il est important que les responsables des politiques publiques de ces pays, mais également ceux des économies avancées, disposent de prévisions rapides et exactes de l'activité économique actuelle et future dans les marchés émergents. Dans la présente étude, les auteurs ont recours à des modèles à facteurs dynamiques avancés pour prévoir, pour un horizon allant du passé récent au futur proche, le taux de croissance du PIB réel de cinq grands marchés émergents, soit le Brésil, la Russie, l'Inde, la Chine et le Mexique (pays du BRIC+M). Ces modèles permettent de traiter efficacement des séries de données dont les délais et la fréquence de parution ainsi que la longueur de la période d'observation sont diff...

No abstract