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Staff projections provided for the Bank of Canada's monetary policy decision process take into account the integration of Canada's very open economy within the global economy, as well as its close real and financial linkages with the United States. To provide inputs for this projection, the Bank has developed several models, including MUSE, NEUQ (the New European Quarterly Model), and BoC-GEM (Bank of Canada Global Economy Model), to analyze and forecast economic developments in the rest of the world. The authors focus on MUSE, the model currently used to describe interaction among the principal U.S. economic variables, including gross domestic product, inflation, interest rates, and the exchange rate. Brief descriptions are also provided of NEUQ and BoC-GEM.

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.

Many important economic variables are subject to revision. This article explains how, when, and why such revisions occur; how revisions to Canadian gross domestic product (GDP) compare with GDP revisions in some other countries; which GDP components are subject to the largest revisions; and how data revisions can affect policy decisions. The author finds that revisions to Canadian GDP tend to be smaller, on average, than those of some other countries, and that among the GDP components, exports and imports are most heavily revised.

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

The existence of downward nominal wage rigidity (DNWR) has often been used to justify a positive inflation target. It is traditionally assumed that positive inflation could “grease the wheels” of the labour market by putting downward pressure on real wages, easing labour market adjustments during a recession.

Worst-case analysis is used among financial regulators in the wake of the recent financial crisis to gauge the tail risk. We provide insight into worst-case analysis and provide guidance on how to estimate it. We derive the bias for the non-parametric heavy-tailed order statistics and contrast it with the semi-parametric extreme value theory (EVT) approach.

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.

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.

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.