A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP

Marta Banbura and Gerhard Rünstler ()

International Journal of Forecasting, 2011, vol. 27, issue 2, 333-346

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

Keywords: Dynamic; factor; models; Filter; weights; GDP; Publication; lags (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (103)

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Related works:
Journal Article: A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP (2011)
Working Paper: A look into the factor model black box: publication lags and the role of hard and soft data in forecasting GDP (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:27:y::i:2:p:333-346

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