A Look into the Factor Model Black Box: Publication Lags and the Role of Hard and Soft Data in Forecasting GDP

36 Pages Posted: 31 May 2007

See all articles by Marta Banbura

Marta Banbura

European Central Bank

Gerhard Rünstler

European Central Bank

Date Written: May 2007

Abstract

We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information beyond the monthly real activity measures for the GDP forecasts. However, this is discovered only, if their more timely publication is properly taken into account. Differences in publication lags play a very important role and should be considered in forecast evaluation.

Keywords: dynamic factor models, forecasting, filter weights

JEL Classification: E37, C53

Suggested Citation

Banbura, Marta and Rünstler, Gerhard, A Look into the Factor Model Black Box: Publication Lags and the Role of Hard and Soft Data in Forecasting GDP (May 2007). ECB Working Paper No. 751. Available at SSRN: https://ssrn.com/abstract=984265

Marta Banbura (Contact Author)

European Central Bank ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Gerhard Rünstler

European Central Bank ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

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