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We propose a new strength measure of the global financial cycle by estimating a regime-switching factor model on cross-border equity flows for 61 countries. We then assess how the strength of the global financial cycle affects monetary policy independence, which is defined as the response of central banks' policy interest rates to exogenous changes in inflation.

We create a theoretical model of central bank asset purchases. The model helps explain how, in a crisis, these purchases ease pressures on investment dealers.

We provide an analysis of cash trends in Canada before and during the COVID-19 pandemic. We also consider the potential two scenarios for issuance of a central bank digital currency in Canada: the emergence of a cashless society or the widespread use of an alternative digital currency in Canada. Finally, we discuss the Canadian experience in maintaining cash as an efficient and accessible method of payment and store of value.

What are the main drivers behind the monetary policy reaction function of the People’s Bank of China?

Modeling and estimating persistent discrete data can be challenging. In this paper, we use an autoregressive panel probit model where the autocorrelation in the discrete variable is driven by the autocorrelation in the latent variable. In such a non-linear model, the autocorrelation in an unobserved variable results in an intractable likelihood containing high-dimensional integrals.

We examine the macro implications of commodity price shocks in a model with multiple production sectors that are interconnected within a commodity-exporting small open economy.

Text of major 1995 lecture by Bank Governor Gordon Thiessen, plus articles from Bank of Canada Review and other sources

Many derivatives markets use collateral requirements calculated with industry-standard but dated methods that are not designed with systemic risk in mind. This paper explores whether the conservative nature of conventional collateral requirements outweighs their lack of consideration of systemic risk.

We measure soft information contained in the congressional testimonies of U.S. Federal Reserve Chairs and analyze its effect on financial markets. Increases in the Chair’s text-, voice-, or face-emotion indices during these testimonies generally raise stock prices and lower their volatility.

We estimate the effects of economic uncertainty on time use and discuss its macroeconomic implications. We develop a model to demonstrate that substitution between market and non-market work provides an additional insurance margin to households, weakening precautionary savings and labour supply and lowering aggregate demand, ultimately amplifying the contractionary effects of uncertainty.