The sharp depreciation of the Canadian dollar and the successful launch of the euro have spawned an animated debate in Canada concerning the potential benefits of formally adopting the U.S. dollar as our national currency.
Mankiw and Reis (2001a) have proposed a "sticky-information"-based Phillips curve (SIPC) to address some of the concerns with the "sticky-price"-based new Keynesian Phillips curve.
This paper examines the predictive power of credit spreads from the corporate bond market. The high-yield bond spread and investment-grade spread can explain 68 per cent and 42 per cent of output variations one year ahead, while the term spread based on government debts can explain only 12 per cent of them.
In this paper, we measure, with Canadian data, the scope of the revisions to real-time estimates of the output gap generated with several univariate and multivariate techniques. We also make an empirical evaluation of the usefulness of the output gap estimates for predicting inflation.
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.
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.
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.
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.