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54 Results

Tracking Canadian Trend Productivity: A Dynamic Factor Model with Markov Switching

Staff Discussion Paper 2007-12 Michael Dolega
The author attempts to track Canadian labour productivity over the past four decades using a multivariate dynamic factor model that, in addition to the labour productivity series, includes aggregate compensation and consumption information. Productivity is assumed to switch between two regimes (the high-growth state and the low-growth state) with different trend growth rates according to […]
Content Type(s): Staff research, Staff discussion papers Topic(s): Productivity JEL Code(s): C, C3, C32, O, O4, O5, O51

Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation

Staff Working Paper 2007-8 Frédérick Demers, Calista Cheung
This paper evaluates the performance of static and dynamic factor models for forecasting Canadian real output growth and core inflation on a quarterly basis. We extract the common component from a large number of macroeconomic indicators, and use the estimates to compute out-of-sample forecasts under a recursive and a rolling scheme with different window sizes.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C3, C32, E, E3, E37

Canadian City Housing Prices and Urban Market Segmentation

Staff Working Paper 2006-49 Jason Allen, Robert Amano, David Byrne, Allan Gregory
The authors provide a detailed empirical analysis of Canadian city housing prices. They examine the long-run relationship between city house prices in Canada from 1981 to 2005 as well as idiosyncratic relations between city prices and city-specific variables.
Content Type(s): Staff research, Staff working papers Topic(s): Regional economic developments JEL Code(s): C, C2, C22, C3, C32, R, R2

Y a-t-il eu surinvestissement au Canada durant la seconde moitié des années 1990?

Staff Working Paper 2005-5 Sylvain Martel
This study on overinvestment differs from the existing literature in that investment in machinery and equipment is modelled as a structural vector autoregression with identification achieved by imposing long-run restrictions, as in Blanchard and Quah (1989).
Content Type(s): Staff research, Staff working papers Topic(s): Domestic demand and components JEL Code(s): C, C3, C32, E, E3, E37, F, F4, F47
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