Multivariate unobserved components (structural) time series models are fitted to annual post-war observations on real income per capita in countries in the euro zone. The aim is to establish stylized facts about convergence as it relates both to long-run income levels and to cycles.
Existing methods for data interpolation or backdating are either univariate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowadays large datasets are readily available, and models with hundreds of parameters are fastly estimated.
This Paper analyses the co-movement in activity, measured by GDP and industrial production, between the G7 countries for the period 1972-2002. For that purpose, a dynamic factor model is estimated using Kalman Filtering techniques.
