A NOTE ON FORECASTING WITH ECONOMETRIC MODELS

Forecasts made by econometricians are typically conditioned on actual values of explanatory variables, even when at the time of the forecast, such variables might not be available. As a first step, one might test the adequacy of econometric specification by comparing conditional post sample forecasts with those of a univariate ARIMA model. Second, when explanatory variables must themselves be forecast, those for which this can be done only badly, should be omitted from the final model. A better forecast will result. An example of screening out badly forecasted explanatory variables is presented.