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Freedman and Engert focus on the changing pattern of lending and borrowing in Canada in the past thirty to forty years, including the types of financial instruments used and the relative roles of financial institutions and financial markets. They examine how borrowing mechanisms have changed over time and consider the challenges facing the Canadian financial sector, including whether our financial markets are in danger of disappearing because of the size and pre-eminence of U.S. financial markets. Some of the trends examined here include syndicated lending, securitization, and credit derivatives, a form of financial engineering that has become increasingly important in the last few years. They also study bond and equity markets to determine whether Canadian capital markets have been hollowed out or abandoned by Canadian firms and conclude that the data do not provide much support for that view.

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.

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.

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.

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.

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.

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.

We investigate the risks and opportunities to the mandates of central banks arising from fintech developments.