Research
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An Estimated Canadian DSGE Model with Nominal and Real Rigidities
This paper develops a dynamic, stochastic, general-equilibrium (DGSE) model for the Canadian economy and evaluates the real effects of monetary policy shocks. To generate high and persistent real effects, the model combines nominal frictions in the form of costly price adjustment with real rigidities modelled as convex costs of adjusting capital and employment. -
New Phillips Curve with Alternative Marginal Cost Measures for Canada, the United States, and the Euro Area
Recent research on the new Phillips curve (NPC) (e.g., Galí, Gertler, and López-Salido 2001a) gives marginal cost an important role in capturing pressures on inflation. In this paper we assess the case for using alternative measures of marginal cost to improve the empirical fit of the NPC. -
Price-Level versus Inflation Targeting in a Small Open Economy
This paper compares two types of monetary policy: price-level targeting and inflation targeting. It reviews recent arguments that favour price-level targeting, and examines how certain factors, such as the nature of the shocks affecting the economy and the degree to which agents are forward-looking, bear upon the arguments. -
Modelling Mortgage Rate Changes with a Smooth Transition Error-Correction Model
This paper uses a smooth transition error-correction model (STECM) to model the one-year and five-year mortgage rate changes. The model allows for a non-linear adjustment process of mortgage rates towards their long-run equilibrium. -
On Inflation and the Persistence of Shocks to Output
This paper empirically investigates the possibility that the effects of shocks to output depend on the level of inflation. The analysis extends Elwood's (1998) framework by incorporating in the model an inflation-threshold process that can potentially influence the stochastic properties of output. -
A Consistent Bootstrap Test for Conditional Density Functions with Time-Dependent Data
This paper describes a new test for evaluating conditional density functions that remains valid when the data are time-dependent and that is therefore applicable to forecasting problems. We show that the test statistic is asymptotically distributed standard normal under the null hypothesis, and diverges to infinity when the null hypothesis is false.