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We analyze micro-level data from the Canadian Survey of Consumer Expectations through the lens of a heterogeneous-expectations model to study how inflation expectations form over the business cycle. We provide new insights into how households form expectations, documenting that forecasting behaviours, attention and noise in beliefs vary across socio-demographic groups and correlate with views about monetary policy.

This report provides a detailed technical description of the updated MacroFinancial Risk Assessment Framework (MFRAF), which replaces the version described in Gauthier, Souissi and Liu (2014) as the Bank of Canada’s stress-testing model for banks with a focus on domestic systemically important banks (D-SIBs).

This paper studies how the outcome of Bayesian persuasion depends on a sender’s information. I study a game in which, prior to the sender’s information disclosure, the designer can restrict the most informative signal that the sender can generate.

Commodity prices are once again making headlines. Some commodity prices, such as those for copper and cattle, have reached record highs; others are rising quickly and approaching previous peaks.

We explore properties of asymmetric generalized autoregressive conditional heteroscedasticity (GARCH) models in the threshold GARCH (GTARCH) family and propose a more general Spline-GTARCH model, which captures high-frequency return volatility, low-frequency macroeconomic volatility as well as an asymmetric response to past negative news in both autoregressive conditional heteroscedasticity (ARCH) and GARCH terms.

We propose a macroeconomic model with a nonlinear Phillips curve that has a flat slope when inflationary pressures are subdued and steepens when inflationary pressures are elevated. Our model can generate more sizable inflation surges due to cost-push and demand shocks than a standard linearized model when inflation is high.

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.

In recent years, the Bank has put renewed emphasis on analyzing monetary variables and on developing models that incorporate money as an active part of the transmission mechanism. In this article, Dinah Maclean describes how the monetary aggregates are used in the formulation of monetary policy analysis at the Bank, outlining the key tools and models used. The most important money-based model currently in use is the M1-VECM. In this model, deviations in the money supply from the long-term demand for money cause changes in inflation. The author briefly describes the "active-money" paradigm underlying this model and explains the key equations within it. Other simpler empirical models are also outlined, including single-equation indicator models for output based on the narrow aggregates, a neural network, and a model based on the broader aggregate M2++. A detailed technical annex provides details on model equations and coefficient values.

The TSX index rose by 9.5 percent in November 2020, adding large gains to an already sharp V-shaped recovery. The economic outlook improved at that time as well. We ask whether the stock market gains since last autumn are due to improving forecasts of firms’ earnings.

Following the recent financial crisis, major central banks have introduced several types of unconventional monetary policy measures, including liquidity and credit facilities, asset purchases and forward guidance. To date, these measures appear to have been successful. They restored market functioning, facilitated the transmission of monetary policy and supported economic activity. They have potential costs, however, including challenges related to the greatly expanded balance sheets of central banks and the eventual exit from these measures, as well as the vulnerabilities that can arise from prolonged monetary accommodation.