Forecasting GDP at the regional level with many predictors

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a unique data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a "data-poor environment" at the sub-national level by including more than 300 international, national and regional indicators. We calculate single-indicator, multi-indicator and pooled forecasts. Our results show that we can significantly increase forecast accuracy compared to an autoregressive benchmark model, both for short- and long-term predictions. Furthermore, our best leading indicators describe the specific regional economic structure better than other indicators. -- leading indicators ; regional forecasting ; forecast evaluation ; forecast combination ; data rich environment