Frédérick Demers - Latest - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-28T19:28:29+00:00The Canadian Business Cycle: A Comparison of Models
https://www.bankofcanada.ca/2007/07/working-paper-2007-38/
This paper examines the ability of linear and nonlinear models to replicate features of real Canadian GDP. We evaluate the models using various business-cycle metrics.2007-07-01T12:54:10+00:00enThe Canadian Business Cycle: A Comparison of Models2007-07-01Business fluctuations and cyclesEconometric and statistical methodsWorking Paper 2007-38 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp07-38.pdfThe Canadian Business Cycle: A Comparison of ModelsFrédérick DemersRyan MacdonaldJuly 2007CC3C32EE3E37Evaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation
https://www.bankofcanada.ca/2007/02/working-paper-2007-8/
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.2007-02-08T11:00:53+00:00enEvaluating Forecasts from Factor Models for Canadian GDP Growth and Core Inflation2007-02-08Econometric and statistical methodsWorking Paper 2007-8 https://www.bankofcanada.ca/wp-content/uploads/2010/03/wp07-8.pdfEvaluating Forecasts from Factor Models for Canadian GDP Growth and Core InflationFrédérick DemersCalista CheungFebruary 2007CC3C32EE3E37Forecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?
https://www.bankofcanada.ca/2005/12/working-paper-2005-44/
The authors investigate the behaviour of core inflation in Canada to analyze three key issues: (i) homogeneity in the response of various price indexes to demand or real exchange rate shocks relative to the response of aggregate core inflation; (ii) whether using disaggregate data helps to improve the forecast of core inflation; and (iii) whether using monthly data helps to improve quarterly forecasts.2005-12-03T11:32:19+00:00enForecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?2005-12-03Econometric and statistical methodsInflation and pricesWorking Paper 2005-44 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp05-44.pdfForecasting Core Inflation in Canada: Should We Forecast the Aggregate or the Components?Frédérick DemersAnnie De ChamplainDecember 2005CC5EE3E37Modelling and Forecasting Housing Investment: The Case of Canada
https://www.bankofcanada.ca/2005/12/working-paper-2005-41/
The author proposes and evaluates econometric models that try to explain and forecast real quarterly housing expenditures in Canada. Structural and leading-indicator models of the Canadian housing sector are described.2005-12-01T15:55:15+00:00enModelling and Forecasting Housing Investment: The Case of Canada2005-12-01Econometric and statistical methodsEconomic modelsWorking Paper 2005-41 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp05-41.pdfModelling and Forecasting Housing Investment: The Case of CanadaFrédérick DemersDecember 2005EE2E27RR2R21Forecasting Canadian GDP: Region-Specific versus Countrywide Information
https://www.bankofcanada.ca/2005/11/working-paper-2005-31/
The authors investigate whether the aggregation of region-specific forecasts improves upon the direct forecasting of Canadian GDP growth.2005-11-01T12:50:45+00:00enForecasting Canadian GDP: Region-Specific versus Countrywide Information2005-11-01Econometric and statistical methodsWorking Paper 2005-31 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp05-31.pdfForecasting Canadian GDP: Region-Specific versus Countrywide InformationFrédérick DemersDavid DupuisNovember 2005CC3C32C5C53EE1E17Prévision et analyse de la production manufacturière au Canada : comparaison de modèles linéaires et non linéaires
https://www.bankofcanada.ca/2004/10/working-paper-2004-40/
In this paper, the author describes reduced-form linear and non-linear econometric models developed to forecast and analyze quarterly data on output growth in the Canadian manufacturing sector from 1981 to 2003.2004-10-01T16:27:30+00:00frPrévision et analyse de la production manufacturière au Canada : comparaison de modèles linéaires et non linéaires2004-10-01Business fluctuations and cyclesEconometric and statistical methodsWorking Paper 2004-40https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp04-40.pdfPrévision et analyse de la production manufacturière au Canada : comparaison de modèles linéaires et non linéairesFrédérick DemersOctober 2004CC2C22C5C53The Canadian Phillips Curve and Regime Shifting
https://www.bankofcanada.ca/2003/10/working-paper-2003-32/
Phillips curves are generally estimated under the assumption of linearity and parameter constancy. Linear models of inflation, however, have recently been criticized for their poor forecasting performance.2003-10-03T14:06:57+00:00enThe Canadian Phillips Curve and Regime Shifting2003-10-03Econometric and statistical methodsInflation and pricesWorking Paper 2003-32 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp03-32.pdfThe Canadian Phillips Curve and Regime ShiftingFrédérick DemersOctober 2003CC5C52EE3E31Forecasting and Analyzing World Commodity Prices
https://www.bankofcanada.ca/2003/08/working-paper-2003-24/
The authors develop simple econometric models to analyze and forecast two components of the Bank of Canada commodity price index: the Bank of Canada non-energy (BCNE) commodity prices and the West Texas Intermediate crude oil price. They present different methodologies to identify transitory and permanent components of movements in these prices.2003-08-01T11:44:17+00:00enForecasting and Analyzing World Commodity Prices2003-08-01Econometric and statistical methodsWorking Paper 2003-24 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp03-24.pdfForecasting and Analyzing World Commodity PricesRené LalondeZhenhua ZhuFrédérick DemersAugust 2003CC5