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3541 Results

The Government of Canada Debt Securities Data Set

We present the daily time series of the outstanding amounts of all Government of Canada marketable debt securities from July 2001 to June 2017.
February 8, 2018

At the Crossroads: Innovation and Inclusive Growth

Remarks Carolyn A. Wilkins G7 Symposium on Innovation and Inclusive Growth Montebello, Quebec
Senior Deputy Governor Carolyn A. Wilkins discusses technological progress and how policy-makers can harness it for economic growth that benefits everyone.
April 29, 2026

Monetary Policy Report—April 2026—Overview

Before the outbreak of the war in the Middle East, the Canadian economy was evolving as expected. Since the war began, oil prices have risen, pushing inflation up, and the outlook has become more uncertain.
June 2, 2022

Navigating high inflation

Speech summary Paul Beaudry Gatineau Chamber of Commerce Gatineau, Quebec
On June 1, the Bank of Canada decided to increase its policy interest rate by half a percentage point. Speaking the next day, Deputy Governor Paul Beaudry explains why inflation has been higher than expected and what we are doing to get it back to our 2% target.

Non-homothetic Preferences and the Demand Channel of Inflation

Staff working paper 2025-30 Stephen Murchison
An alternative to the standard CES aggregator, based on non-homothetic household preferences, is proposed. Specifically, the elasticity of substitution between goods declines during periods of strong per-capita consumption and vice versa, giving firms an incentive to adjust their desired markup in response to the state of demand. Empirical evidence favouring a direct role for per-capita consumption demand in inflation determination for Canada is presented.

Differentiable, Filter Free Bayesian Estimation of DSGE Models Using Mixture Density Networks

Staff working paper 2025-3 Chris Naubert
I develop a method for Bayesian estimation of globally solved, non-linear macroeconomic models. The method uses a mixture density network to approximate the initial state distribution. The mixture density network results in more reliable posterior inference compared with the case when the initial states are set to their steady-state values.
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