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2139 Results

Core inflation over the COVID-19 pandemic

Staff analytical note 2022-17 Mikael Khan, Elyse Sullivan
We assess the usefulness of various measures of core inflation over the COVID-19 pandemic. We find that Cpi-trim and CPI-median provided the best signal of underlying inflation. The favourable performance of these measures stems from their lack of reliance on historical experience, an especially valuable feature in unprecedented times.
March 30, 1995

Uncertainty and the Transmission of Monetary Policy in Canada

Lecture Gordon Thiessen York University, Glendon College Toronto, Ontario
Just over seven years ago, my predecessor, John Crow, delivered the Hanson Memorial Lecture at the University of Alberta. In it, he discussed a number of issues relating to the conduct of Canadian monetary policy, including the goal of monetary policy, the transmission mechanism, the use of monetary aggregates as policy guides, financial market uncertainty, and the role of the exchange rate
August 6, 2010

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November 14, 2013

Fragmentation in Canadian Equity Markets

Changes in technology and regulation have resulted in an increasing number of trading venues in equity markets in Canada. New trading platforms have intensified price competition and have encouraged innovation, and they do not appear to have segmented trade. But the increasingly complex market structure has necessitated investments in expensive technology and has introduced new operational risks. Regulatory responses should be carefully adapted to retain the competition and innovation associated with this market fragmentation.
Content Type(s): Publications, Bank of Canada Review articles JEL Code(s): G, G2, L, L1, L13, N, N2, N22

Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models

Staff discussion paper 2022-19 James Younker
This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models.
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