Predictor selection in forecasting macro-economic variables

This paper evaluates the forecasting power of different methods of sub-set selection on U.S. macroeconomic time series. A data set containing 126 variables and spanning 50 years is used in several targeted manners to employ only the variables essential to the forecast at that particular time. Also an attempt is made at incorporating the squared values of the variables in order to allow for non-linearity in the data. Using the normal data set the benchmark is often beaten. The data set including the squared variables is very inconsistent.