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Pooling-Based Data Interpolation and Backdating

Number: 299
Year: 2005
Author(s): Massimiliano Marcellino

Pooling forecasts obtained from different procedures typically reduces
the mean square forecast error and more generally improves 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 also in this context.

Keywords: Pooling, Interpolation, Factor Model, Kalman Filter, Spline
JEL codes: C32, C43, C82