Projektleitung: Philipp Piribauer
Modeling European regional output dynamics using a dynamic multi-level factor model
Abgeschlossene Forschungsprojekte
Mit finanzieller Unterstützung von: Jubiläumsfonds der Oesterreichischen Nationalbank
Studie von: Österreichisches Institut für Wirtschaftsforschung
Abgeschlossen: 2018
In this project we aim to develop a flexible dynamic factor model for European regions. Taking a regional stance allows us to gain deep insights on the relationship between individual regions and phenomena like country-specific or global business cycle fluctuations. Our proposed modelling approach allows answering a rich set of possible research questions. For instance, it could provide new insights on how business cycle shocks propagate through Europe. In addition, we aim to provide new evidence on the degree of business cycle synchronisation over time, employing a time-varying parameter framework. Finally, to assess how well our model fits the data we also plan to perform a forecasting exercise where we predict regional output growth in Europe.
Forschungsbereich:Regionalökonomie und räumliche Analyse
Sprache:Englisch

Verwandte Einträge

WIFO Working Papers, 2018, (560), 30 Seiten
Mit finanzieller Unterstützung von: Jubiläumsfonds der Oesterreichischen Nationalbank
Online seit: 13.03.2018 0:00
We develop a multivariate dynamic factor model that exploits euro area country-specific information on output and inflation for estimating an area-wide measure of the output gap. In the proposed multi-country framework we moreover allow for flexible stochastic volatility specifications for both the error variances and the innovations to the latent quantities in order to deal with potential changes in the commonalities of business cycle movements. By tracing the relative importance of the common euro area output gap component as a means to explaining movements in both output and inflation over time, the paper provides valuable insights in the evolution of the degree of synchronicity of the country-specific business cycles. In an out-of-sample forecasting exercise, the paper shows that the proposed approach performs well as compared to other well-known benchmark specifications.