Several factor-based models are estimated to investigate the role of country-specific trade and survey data in forecasting euro area manufacturing production. Following Boivin and Ng (2006), the emphasis is put on the choice of the dataset chosen to estimate the factors. Four datasets are built and common factors are estimated separately on each of them following two methodologies, Stock and Watson (2002a, 2002b) and Forni et al. (2005). Then, a rolling out of sample forecast comparison exercise is carried out on nine models to compare the forecast performance of the models and the datasets. Compared to univariate benchmarks, our results are supportive of factor-based models up to two quarters. They show that incorporating survey and external trade information improves the forecast of manufacturing production. They also confirm the findings of Marcellino, Stock and Watson (2003) that, using country information, it is possible to improve forecasts for the euro area. Interestingly, the medium-sized highly opened economies provide valuable information to monitor area wide developments, beyond their weight in the aggregate. Conversely, the large countries do not add much to the monitoring of the aggregate, when considered separately.