An Automatic Leading Indicator of Economic Activity: Forecasting GDP Growth for European Countries

In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large, and selection of a subset must be carried out. In this paper we propose an `Automatic Leading Indicator' model. Rather than preselection, we use a dynamic factor model to summarise the information content of a pool of variables. Results show that the forecasting performance of our `Automatic Leading Indicator' model is significantly better than that of traditional model selection criteria with VAR models. This study is carried out using quaterly data for France, Germany, Italy and the United Kingdom.