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Debt strategy is defined as the manner in which a government finances an excess of government expenditures over revenues and any maturing debt issued in previous periods. The author gives a thorough qualitative description of the complexities of debt strategy analysis and then demonstrates that it is, in fact, a problem in stochastic optimal control.

In this report, the authors examine and compare twelve private and public sector models of the Canadian economy with respect to their paradigm, structure, and dynamic properties. These open-economy models can be grouped into two economic paradigms.

Postulating two different specifications for the Canadian Phillips curve (a purely backwardlooking model, and a partly backward-, partly forward-looking model), the authors test for structural breaks in the parameters of the equation. In each case, they account for the possibilities that: (i) breaks can be discrete, or continuous, and (ii) available data samples may be too small to justify using asymptotically valid structural-change tests.

Using interest rate yield spreads to explain changes in inflation, we investigate whether such relationships can be modelled using two-regime threshold models.

The effects of global energy-price shocks on retail energy prices in Canada are examined. More specifically, the author looks at the response of the consumer price indexes for gasoline, heating oil, natural gas, and electricity in Canada to movements in world crude oil prices.

This paper summarizes the results of recent research evaluating the Bank of Canada's Quarterly Projection Model (QPM).

An effective technique governments use to evaluate the desirability of different financing strategies involves stochastic simulation. This approach requires the postulation of the future dynamics of key macroeconomic variables and the use of those variables in the construction of a debt charge distribution for each individual financing strategy.

This paper examines asset allocation strategies in an extreme value at risk (VaR) framework in which the risk measure is the p-quantile from the extreme value distribution. The main focus is on the allocation problem faced by an extremely risk-averse institution, such as a central bank.

Affine models describe the stylized time-series properties of the term structure of interest rates in a reasonable manner, they generalize relatively easily to higher dimensions, and a vast academic literature exists relating to their implementation. This combination of characteristics makes the affine class a natural introductory point for modelling interest rate dynamics.

This paper evaluates linear and non-linear forecast-combination methods. Among the non-linear methods, we propose a nonparametric kernel-regression weighting approach that allows maximum flexibility of the weighting parameters.