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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.

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.

In an era when the primary policy instrument is the level of the short-term interest rate, a comparison of that rate with some equilibrium rate can be a useful guide for policy and a convenient method to measure the stance of monetary policy.

The recent financial crisis and global economic slowdown have renewed interest in monetary policy options when the policy interest rate is at or near zero.

In this paper two shocks are analysed using Canadian data: a money-supply shock ("M-shock") and an interest-rate shock ("R-shock"). Money-supply shocks are derived using long-run restrictions based on long-run propositions of monetary theory. Thus, an M-shock is represented by an orthogonalized innovation in the trend shared by money and prices.

The authors examine whether simple measures of Canadian equity and housing price misalignments contain leading information about output growth and inflation.

This article by the Bank's Web master details the development of the Bank's Web site and highlights some of its special features. It includes a description of dataBANK, a custom-built interface to the Bank's economic databases that gives visitors access to 220 data series. It also provides a mini tour of monetary policy material "on site," as well as a taste of things to come. Above all, this article invites you to come and visit our site.

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.

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.

As the Government of Canada’s fiscal agent, the Bank of Canada provides strategic policy advice on the management of the government’s debt, in addition to being responsible for conducting debt-management operations. In this article, the authors review the evolution of the debt strategy over the past 20 years and outline the complex process of developing a sound strategy that balances various cost and risk considerations. This includes an examination of the tools and practices used to develop the new medium-term debt-management strategy, such as the modelling approach involved, market consultations and various debt-management metrics.