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

被引:91
作者
Banbura, Marta [1 ]
Ruenstler, Gerhard [2 ]
机构
[1] European Cent Bank, Frankfurt, Germany
[2] Austrian Inst Econ Res, Vienna, Austria
关键词
Dynamic factor models; Filter weights; GDP; Publication lags; EURO-AREA; INFLATION; NUMBER; HELP;
D O I
10.1016/j.ijforecast.2010.01.011
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2010 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:333 / 346
页数:14
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