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Nowcasting Irish GDP

By Antonello D'Agostino, Kieran McQuinn and Derry O'Brien


In this paper we present a dynamic factor model that produces nowcasts and backcasts of Irish quarterly GDP using timely data from a panel dataset of 35 indicators. We apply a recently developed methodology, whereby numerous potentially useful indicator series for Irish GDP can be availed of in a parsimonious manner and the unsynchronized nature of the release calendar for a wide range of higher frequency indicators can be handled. The nowcasts in this paper are generated by using dynamic factor analysis to extract common factors from the panel dataset. Bridge equations are then used to relate these factors to quarterly GDP estimates. We conduct an out-of-sample forecasting simulation exercise, where the performance of the factor model is compared with that of a standard benchmark model.

Topics: C53 - Forecasting and Prediction Methods; Simulation Methods, E52 - Monetary Policy, C33 - Models with Panel Data; Longitudinal Data; Spatial Time Series
Year: 2011
DOI identifier: 10.1787/jbcma-2012-5k92n2pwccwb
OAI identifier: oai:mpra.ub.uni-muenchen.de:32941

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