Confidence intervals for linear combinations of forecasts from dynamic econometric models

Abstract

This paper derives the approximate distribution of a vector of forecast errors from a dynamic simultaneous equations econometric model. The system may include exogenous variables with known and/or unknown future values. For the latter set of exogenous variables, a stationery and invertible ARMAX process is assumed. Confidence regions are derived for vectors of linear combinations of forecasts. these confidence regions are particularly useful for designing tests of super exogeneity via tests of predictive failure. To illustrate the use of confidence intervals, forecasts are generated for an oil price and for a Venezuelan consumer price index.