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The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies.

The prices of commodities produced in Canada have important implications for the performance of the Canadian economy and the conduct of monetary policy. The authors explain an important change to the methodology used to construct the Bank of Canada commodity price index (BCPI).

I investigate how monetary policy transmits to mortgage rates via the mortgage market concentration channel for both traditional and shadow banks in the United States from 2009 to 2019. On average, shadow and traditional banks exhibit only a slight disparity in transmitting monetary shocks to mortgage rates.

Conventional models imply that central banks aiming to raise inflation should lower nominal rates and thus stimulate aggregate demand. However, several economists have recently challenged this conventional wisdom in favour of an alternative “neo-Fisherian’’ view under which higher nominal rates might in fact lead to higher inflation.

In this article the author examines the effects that major changes in energy prices in recent years have had on inflation and on the pace of economic expansion. These are then compared with the effects of the oil-price shocks that occurred in the 1970s and early 1980s. Changes in the intensity of energy use are examined, as well as developments in Canada's merchandise trade surplus in energy commodities and products. The author also considers the effects that a monetary policy anchored to low and stable inflation could have on price-setting behaviour and thus on the pass-through of higher energy costs to core inflation in Canada and in other industrial countries.

The Canadian dollar has declined against the US dollar since October 2024, mostly due to rising uncertainty around trade policies. A widening differential in policy interest rates between the two countries has also played a modest role.

There is ample evidence that information and communication technologies (ICT) contributed significantly to the surge in output and labour-productivity growth in the United States in the late 1990s.

This article examines the efforts of the major advanced countries to strengthen the international financial system in order to avoid financial crises such as those that occurred in emerging-market economies in the 1990s. These efforts have focused on crisis prevention and crisis management. The prevention of such crises has necessitated the formation of new international groups that include emerging markets in their membership. Measures have also been taken to reduce the vulnerability of countries to such crises. These measures have centered on the need for appropriate macroeconomic policies, including the need for sustainable exchange rate regimes, sound domestic financial systems, and prudent risk management. In the area of crisis management, the International Monetary Fund (IMF) has been given access to additional resources for lending to countries that experience financial crises. The IMF has also established new lending facilities for use in such circumstances. It has also been agreed that the private sector will need to play a greater role in the management of such crises in the future.

The financial crisis of 2007–09 has highlighted the importance of developments in financial conditions for real economic activity. The authors estimate the effect of current and past shocks to financial variables on U.S. GDP growth by constructing two growthbased financial conditions indexes (FCIs) that measure the contribution to quarterly (annualized) GDP growth from financial conditions.

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging – so as to explicitly reflect the objective of forecasting a discrete outcome.