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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.

Similar to those of other forecasters, the Bank of Canada’s forecasts of global GDP growth have shown persistent negative errors over the past five years. This is in contrast to the pre-crisis period, when errors were consistently positive as global GDP surprised to the upside. All major regions have contributed to the forecast errors observed since 2011, although the United States has been the most persistent source of notable errors.

How much capital do banks need as a buffer to absorb severe shocks? By using historical stock market data, market-based stress tests help estimate the magnitude of capital buffers necessary to absorb severe but plausible shocks.

A low level of the neutral rate of interest increases the likelihood that a central bank’s policy rate will reach its effective lower bound (ELB) in future economic downturns. In a low neutral rate environment, using an extended monetary policy toolkit including forward guidance helps address the ELB challenge. Using the Bank’s Terms-of-Trade Economic Model, we assess the benefits and limitations of a state-contingent forward guidance implemented within a flexible inflation targeting framework.

We analyze the dynamic and heterogeneous responses of small-business loan performance to a monetary-policy shock using loan-level data in Canada. We find evidence of monetary policy transmission through the cash-flow channel and the aggregate demand channel as well as some, though limited, impact of collateral to discipline loan repayment.

Today the Bank of Canada launched a digital database with more than 30 years of past staff economic projections of the Canadian economy.

The break-even inflation rate (BEIR) is calculated by comparing the yields on conventional and Real Return Bonds. Defined as the average rate of inflation that equates the expected returns on these two bonds, the BEIR has the potential to contain useful information about long-run inflation expectations. Yet the BEIR has been higher, on average, and more variable than survey measures of inflation expectations, which may be explained by the effects of premiums and distortions embedded in the BEIR. Because of the difficulty in accounting for these distortions, the BEIR should not be given a large weight as a measure of long-run inflation expectations at this time. However, as the Real Return Bond market continues to develop, the BEIR should become a more useful indicator of inflation expectations. At present, it demonstrates no clear advantage over survey measures and even past inflation rates in forecasting near-term inflation.

I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors.

Bank of Canada Deputy Governor Sharon Kozicki discusses how differences among households affect economic outcomes, how shocks can have important uneven effects across households, and why these things matter for monetary policy.

This paper introduces a new methodology to date systemic financial stress events in a transparent, objective and reproducible way. The financial cycle is captured by a monthly country-specific financial stress index.