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.