The uncertainty of forecasting: models with structural change versus those without changing parameters

Abstract

The Bayesian predictive density is found for future observations of the unknown dependent variables for a multivariate linear model with a single shift in the regression matrix.

A numerical example shows that it is dangerous to predict future observations with an unchanging parameter model when the appropriate model should include structural change.

Keywords:

• multivariate linear model
• Bayesian predictive density
• Single shift in the regressin matrix