Econometric and statistical methods

• Optimization in a Simulation Setting: Use of Function Approximation in Debt Strategy Analysis

  Staff Working Paper 2007-13 David Bolder, Tiago Rubin

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Debt management, Econometric and statistical methods, Financial markets, Fiscal policy JEL Code(s): C, C0, C1, C14, C15, C5, C51, C52, C6, C61, C65, E, E6, G, G1, H, H6, H63

• 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

• Housing Market Cycles and Duration Dependence in the United States and Canada

  Staff Working Paper 2007-2 Rose Cunningham, Ilan Kolet

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C4, C41, E, E3, E32, R, R2, R21

• How Far Can Forecasting Models Forecast? Forecast Content Horizons for Some Important Macroeconomic Variables

  Staff Working Paper 2007-1 John Galbraith, Greg Tkacz

  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.

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C5, C53