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We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets.

We consider ways central banks could adapt in the event of an increased risk of a dash for cash from asset managers. We explore ideas such as new facilities that ease asset managers’ ability to convert existing assets to cash or new assets with liquidity that central banks would guarantee.

During the COVID-19 financial market crisis, central banks introduced programs to support liquidity in important core funding markets. As well as acting as a backstop to market prices, these programs produce useful trading data on prevailing market conditions. When summary information from this data is shared publicly, it can help market participants understand current conditions and aid the recovery of market functioning.

We examine how demographic factors influence potential output, focusing on how the age distribution of the working-age population and the old-age dependency ratio affect aggregate productivity. Following Feyrer (2007), we emphasize that the contribution to aggregate productivity varies by age group, with middle-aged individuals (aged 40 to 49) being the most productive.

Changes in the term premium can reflect uncertainty about inflation, growth and monetary policy. Understanding the key factors that influence the term premium is important when central banks make decisions about monetary policy. In this paper, we derive the real term premium from the nominal term premium in Canada.

Changes in domestic interest rates affect the value of the Canadian dollar less than changes in the risk premium do. These variations often occur when a broad shift in risk sentiment occurs in global markets. Ultimately, the value of the currency reflects long-term, slow-moving features of the economies.

This paper provides an extensive evaluation of the performance of quantile vector autoregression (QVAR) to forecast macroeconomic risk. Generally, QVAR outperforms standard benchmark models. Moreover, QVAR and QVAR augmented with factors perform equally well. Both are adequate for modeling macroeconomic risks.

We model non-bank entry into fixed-income markets and state-dependent liquidity. Non-bank financial institutions improve liquidity more during normal times than in stress. Banks may become less reliable to marginal clients, exacerbating the difference in liquidity between normal and stressed times. Central bank lending during stress may limit this harmful division.

In 2023, the share of Canadian banks’ foreign assets and liabilities amounted to around 50%. While Canadian banks engage domestically mostly with households and non-financial corporations, their most common counterparties abroad are non-bank financial institutions.

We draw on the Canadian experience to examine how monetary and macroprudential policies interact and possibly complement each other in achieving their respective price and financial stability objectives.