Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper deals with the estimation of monthly indicators of economic activity for the Euro area and its largest member countries that possess the following attributes: relevance, representativeness and timeliness. Relevance is determined by comparing our monthly indicators to the gross domestic product at chained volumes, as the most important measure of the level of economic activity. Representativeness is achieved by considering a very large number of (timely) time series of monthly indicators relating to the level of economic activity, providing a more or less complete coverage. The indicators are modelled using a large-scale parametric factor model. We discuss its specification and provide details of the statistical treatment. Computational efficiency is crucial for the estimation of large-scale parametric factor models of the dimension used in our application (considering about 170 series). To achieve it, we apply state-of-the-art state space methods that can handle temporal aggregation, and any pattern of missing values.