Search

An important channel in the transmission of monetary policy is the relationship between the short-term policy rate and long-term interest rates. Using a new term-structure model, the authors show that the variation in long-term interest rates over time consists of two components: one representing investor expectations of future policy rates, and another reflecting a term-structure risk premium that compensates investors for holding a risky asset. The time variation in the term-structure risk premium is countercyclical and largely determined by global macroeconomic conditions. As a result, long-term rates are pushed up during recessions and down during times of expansion. This is an important phenomenon that central banks need to take into account when using short-term rates as a policy tool.

We compare the determinants of consumer inflation expectations in the US and Canada by analyzing two current surveys. We find that Canadian consumers rely more on professional forecasts and the history of actual inflation when forming their expectations, while US consumers rely more on their own lagged expectations.

This paper develops a model of firm heterogeneity, technological adoption, and urbanization. In the model, welfare is measured by household real income, and urbanization is measured by population density. I use the model to derive statistics that measure the effect of a new technology on productivity, welfare, and urbanization.

This paper considers an economy where central-bank-issued fiat money competes with privately issued e-money. We study a policy-setting game between the central bank and the e-money issuer and find (1) the optimal monetary policy of the central bank depends on the policy of the private issuer and may deviate from the Friedman rule; (2) multiple equilibria may exist; (3) when the economy approaches a cashless state, the central bank’s optimal policy improves the market power of the e-money issuer and can lead to a discrete decrease in welfare and a discrete increase in inflation; and (4) first best cannot be achieved.

Dynamic general-equilibrium models (DGEMs) are being increasingly used in macroeconomic research. In this article, the author describes the main features of these models and outlines their contribution to economic research performed at the Bank of Canada. He notes that the basic principle of DGEMs is that the modelling of economic activity, even on a scale as large as the economy of a country, should start with a series of microeconomic problems (at the scale of individuals), which, once resolved, are aggregated to represent the macroeconomic reality described by the model.

Staff projections provided for the Bank of Canada's monetary policy decision process take into account the integration of Canada's very open economy within the global economy, as well as its close real and financial linkages with the United States. To provide inputs for this projection, the Bank has developed several models, including MUSE, NEUQ (the New European Quarterly Model), and BoC-GEM (Bank of Canada Global Economy Model), to analyze and forecast economic developments in the rest of the world. The authors focus on MUSE, the model currently used to describe interaction among the principal U.S. economic variables, including gross domestic product, inflation, interest rates, and the exchange rate. Brief descriptions are also provided of NEUQ and BoC-GEM.

How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy.

Annual research grants for a term of up to two years.

Deposit insurance protects depositors from failing banks, thus making insured deposits risk-free. When a deposit insurance limit is increased, some deposits that previously were uninsured become insured, thereby increasing the share of risk-free assets in households’ portfolios. This increase cannot simply be undone by households, because to invest in uninsured deposits, a household must first invest in insured deposits up to the limit. This basic insight is the starting point of the analysis in this paper.

We propose a tool that decomposes TFP growth into sectoral contributions. The analysis incorporates three structural factors—digitalization, aging and climate change policies—and measures their contributions. Overall, we expect that aggregate TFP growth will slow down in the 2020s below both its historical average and the average from the 2010s.