Pooling forecasts obtained from different procedures typically reduces the mean square forecast error and more generally improve the quality of the forecast. In this paper, we evaluate whether pooling-interpolated or-backdated time series obtained from different procedures can also improve the quality of the generated data. Both simulation results and empirical analyses with macroeconomic time series indicate that pooling plays a positive and important role in this context also. Copyright 2007 The Author Journal compilation 2007 Blackwell Publishing Ltd.
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David F. Hendry & Michael P. Clements, 2004.
"Pooling of forecasts,"
Econometrics Journal,
Royal Economic Society, vol. 7(1), pages 1-31, 06.
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David Hendry & Michael P. Clements, 2001.
"Pooling of Forecasts,"
Economics Papers
2002-W9, Economics Group, Nuffield College, University of Oxford.
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