In this study, we assess the accuracy of macroeconomic forecasts at the regional level using a large 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 complementing various regional indicators with more than 200 national and international indicators. We calculate single-indicator, multi-indicator, pooled and factor forecasts in a ‘pseudo-real-time’ setting. Our results show that we can significantly increase forecast accuracy compared with an autoregressive benchmark model, both for short- and long-term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP.