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The objective of this paper is twofold. First, we assess whether financial education might be a suitable tool to promote the financial inclusion opportunities that big techs provide. Second, we study how this potential financial inclusion could impact financial stability.

Using data on bank branch locations across Canada from 2008 to 2018, we explore an interesting aspect of bank branch competition—geographic concentration. We find that bank branch density does not correlate with geographic and market concentration; however, we do find strong correlation with postal-code demographics.

The financial crisis of 2007-09 and the subsequent extended period of historically low real interest rates have revived the question of whether economic agents are willing to take on more risk when interest rates remain low for a prolonged time period. This increased appetite for risk, which causes economic agents to search for investment assets and strategies that generate higher investment returns, has been called the risk-taking channel of monetary policy. Recent academic research on banks suggests that lending policies in times of low interest rates can be consistent with the existence of a risk-taking channel of monetary policy in Europe, South America, the United States and Canada. Specifically, studies find that the terms of loans to risky borrowers become less stringent in periods of low interest rates. This risk-taking channel may amplify the effects of traditional transmission mechanisms, resulting in the creation of excessive credit.

We are experiencing a commodity super cycle. Throughout the current boom, the scale of price increases has been higher, and the range of affected commodities broader, than in previous upturns. Since 2002, grain and oilseed prices have more than doubled, base metals prices have tripled, and oil prices have quadrupled.

Should monetary policy lean against housing market booms? We approach this question using a small-scale, regime-switching New Keynesian model, where housing market crashes arrive with a logit probability that depends on the level of household debt.

This paper surveys and summarizes the literature on how fiscal policy and monetary policy can complement each other in stabilizing economic activity.

This article examines another strategy in the Bank's approach to dealing with an uncertain world: the use of carefully articulated models to produce economic forecasts and to examine the implications of the various risks to those forecasts. Economic models are deliberate simplifications of a complex world that allow economists to make predictions that are reasonably accurate and that can be easily understood and communicated. By using several models, based on competing paradigms, the Bank minimizes policy errors that could result from relying on one view of the world and one philosophy of model design. The authors review some of the models currently used at the Bank, as well as the role of judgment in the projection process.

We explain how the Bank of Canada’s policy models capture the trade-off between output and inflation in Canada. We provide new estimates of the trade-off and contrast them with those in the Bank’s macroeconomic models.

In its role as fiscal agent to the government, the Bank of Canada provides analysis and advice on decisions about the government's domestic debt portfolio. Debt-management decisions depend on assumptions about future interest rates, macroeconomic outcomes, and fiscal policy, yet when a debt-strategy decision is taken, none of these factors can be known with certainty. Moreover, the government has various financing options (i.e., treasury bills, nominal bonds, and inflation-linked bonds) to meet its objectives of minimizing debt-service charges while simultaneously ensuring a prudent risk profile and well-functioning government securities markets. Bank of Canada staff have therefore developed a mathematical model to assist in the decision-making process. This article describes the key aspects of the debt manager's challenge and the principal assumptions incorporated in the debt-strategy model, illustrated with specific results.