C - Mathematical and Quantitative Methods - Bank of Canada
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Bank of Canada RSS Feedsen2024-03-28T16:53:36+00:00Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis
https://www.bankofcanada.ca/2007/02/working-paper-2007-13/
The stochastic simulation model suggested by Bolder (2003) for the analysis of the federal government's debt-management strategy provides a wide variety of useful information. It does not, however, assist in determining an optimal debt-management strategy for the government in its current form.2007-02-13T12:52:37+00:00enOptimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis2007-02-13Debt managementEconometric and statistical methodsFinancial marketsFiscal policyWorking Paper 2007-13 https://www.bankofcanada.ca/wp-content/uploads/2010/03/wp07-13.pdfOptimization in a Simulation Setting: Use of Function Approximation in Debt Strategy AnalysisDavid BolderTiago RubinFebruary 2007CC0C1C14C15C5C51C52C6C61C65EE6GG1HH6H63Evaluating 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 2007CC3C32EE3E37Monetary Policy Committees in Action: Is There Room for Improvement?
https://www.bankofcanada.ca/2007/02/working-paper-2007-6/
More than 80 central banks use a committee to take monetary policy decisions. The composition of the committee and the structure of the meeting can affect the quality of the decision making.2007-02-06T14:27:09+00:00enMonetary Policy Committees in Action: Is There Room for Improvement?2007-02-06Central bank researchMonetary policy frameworkWorking Paper 2007-6 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp07-6.pdfMonetary Policy Committees in Action: Is There Room for Improvement?Philipp MaierFebruary 2007CC9C92DD7D70EE5E58Time-Consistent Control in Non-Linear Models
https://www.bankofcanada.ca/2007/02/working-paper-2007-3/
We show how to use optimal control theory to derive optimal time-consistent Markov-perfect government policies in nonlinear dynamic general equilibrium models, extending the result of Cohen and Michel (1988) for models with quadratic objective functions and linear dynamics. We replace private agents' costates by flexible functions of current states in the government's maximization problem.2007-02-03T10:42:23+00:00enTime-Consistent Control in Non-Linear Models2007-02-03Fiscal policyMonetary policy frameworkWorking Paper 2007-3 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp07-3.pdfTime-Consistent Control in Non-Linear ModelsSteve AmblerFlorian PelgrinFebruary 2007CC6C63EE6E61E62Housing Market Cycles and Duration Dependence in the United States and Canada
https://www.bankofcanada.ca/2007/02/working-paper-2007-2/
Housing wealth is a large component of total wealth and plays an important role in aggregate business cycles. In this paper, we explore data on real house price cycles at the aggregate level and city level for the United States and Canada.2007-02-02T10:28:41+00:00enHousing Market Cycles and Duration Dependence in the United States and Canada2007-02-02Business fluctuations and cyclesEconometric and statistical methodsWorking Paper 2007-2 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp07-2.pdfHousing Market Cycles and Duration Dependence in the United States and CanadaRose CunninghamIlan KoletFebruary 2007CC4C41EE3E32RR2R21How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables
https://www.bankofcanada.ca/2007/02/working-paper-2007-1/
For stationary transformations of variables, there exists a maximum horizon beyond which forecasts can provide no more information about the variable than is present in the unconditional mean. Meteorological forecasts, typically excepting only experimental or exploratory situations, are not reported beyond this horizon; by contrast, little generally accepted information about such maximum horizons is available for economic variables.2007-02-01T10:00:59+00:00enHow Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables2007-02-01Business fluctuations and cyclesEconometric and statistical methodsWorking Paper 2007-1 https://www.bankofcanada.ca/wp-content/uploads/2010/02/wp07-1.pdfHow Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic VariablesJohn GalbraithGreg TkaczFebruary 2007CC5C53