We propose a drifting-coefficient model to empirically study the effect of money on output growth in Canada and to examine the role of prevailing financial conditions for that relationship. We show that such a time-varying approach can be a useful way of modelling the impact of money on growth, and can partly reconcile the lack of concensus in the literature on the question of whether money affects growth.
We propose alternative single-equation semi-structural models for forecasting inflation in Canada, whereby structural New Keynesian models are combined with time-series features in the data. Several marginal cost measures are used, including one that in addition to unit labour cost also integrates relative price shocks known to play an important role in open-economies.
Inflation-targeting central banks around the world often state their inflation objectives with regard to the consumer price index (CPI). Yet the literature on optimal monetary policy based on models with nominal rigidities and more than one sector suggests that CPI inflation is not always the best choice from a social welfare perspective.
Real wage rigidities have recently been proposed as a way of building intrinsic persistence in inflation within the context of New Keynesian Phillips Curves. Using two recent illustrative structural models, we evaluate empirically the importance of real wage rigidities in the data and the extent to which such models provide useful information regarding price stickiness.
Weak identification is likely to be prevalent in multi-equation macroeconomic models such as in dynamic stochastic general equilibrium setups. Identification difficulties cause the breakdown of standard asymptotic procedures, making inference unreliable.