Forecasting Macroeconomic Variables for the New Member States of the European Union

By Anindya Banerjee, Massimiliano Marcellino, Igor Masten. 2005

49 citations recorded by the source corpus.

The accession of ten countries into the European Union makes the forecasting of their key macroeconomic indicators an exercise of some importance. Because of the transition period, only short spans of reliable time series are available, suggesting the adoption of simple time series models as forecasting tools. However, despite this constraint on the span of data, a large number of macroeconomic variables (for a given time span) are available, making the class of dynamic factor models a reasonable alternative forecasting tool. The relative performance of these two forecasting approaches is compared by using data for five new Member States. The role of Euro-area information for forecasting and the usefulness of robustifying techniques such as intercept corrections are also evaluated. We find that factor models work well in general, although with marked differences across countries. Robustifying techniques are useful in a few cases, while Euro-area information is virtually irrelevant.

Subfields: Economics and Econometrics, Finance

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Citations in the corpus

Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change (2008, methodology): “This section, which is based on Banerjee et al. (2005, 2006), reviews the competing forecasting approaches we consider both in the Monte Carlo analysis in Section 3 below and, more particularly, in the empirical analysis discussed in Section 4.”