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The third strategy employed by the Bank when dealing with uncertainty is the consideration of appropriate simple reaction functions or "rules" for the setting of the policy interest rate. Since John Taylor's presentation of his much-discussed rule, research on simple policy rules has exploded. Simple rules have several advantages. In particular, they are easy to construct and communicate and are believed by some to be robust, in the sense of generating good results in a variety of economic models. This article provides an overview of the recent research regarding the usefulness and robustness of simple monetary policy rules, particularly in models of the Canadian economy. It also describes and explains the role of simple rules in the conduct of monetary policy in Canada.

To what extent does a central bank digital currency (CBDC) compete with bank deposits? To answer this question, we develop and estimate a structural model where each household chooses which financial institution to deposit their digital money with.

This article by the Bank's visiting economist examines the role of money in the transmission of monetary policy. Professor Laidler argues against the view of money as a passive variable that reacts to changes in prices, output, and interest rates but has no direct causative effect on them. He maintains that the empirical evidence supports the view of money playing an active role in the transmission mechanism. While he agrees that individual monetary aggregates can be difficult to read because of instabilities in the demand-for-money function, he argues that monetary aggregates, particularly those relating to transactions money, should have a more significant place in the hierarchy of policy variables that the Bank considers when formulating monetary policy.

Can artificial intelligence (AI) think and act like a cash manager? In this paper we explore how generative AI agents can help manage liquidity, prioritize payments and optimize efficiency in real-time gross settlement systems.

We analyze the evolution of macroeconomic uncertainty in the United States, based on the forecast errors of consensus survey forecasts of different economic indicators. Comprehensive information contained in the survey forecasts enables us to capture a real-time subjective measure of uncertainty in a simple framework.