Freedom of Choice in Macroeconomic Forecasting*

Different studies provide a surprisingly large variety of controversial conclusions about the forecasting power of an indicator, even when it is supposed to forecast the same time series. In this study, we aim to provide a thorough overview of linear forecasting techniques and draw conclusions useful for the identification of the predictive relationship between leading indicators and time series. In a case study for Germany, we forecast two possible representations of industrial production. Further on we consider a large variety of time-varying specifications. In a horse race with nine leading indicators plus an AR benchmark model, we demonstrate the variance of assessment across target variables and forecasting settings (50 per horizon). We show that it is nearly always possible to find situations in which one indicator proved to have better predicting power compared with another. Nevertheless, the freedom of choice can be useful to identify robust leading indicators. (JEL codes: C52, C53, E37).