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Pooling‐Based Data Interpolation and Backdating
Authors:Massimiliano Marcellino
Abstract:Abstract. 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.
Keywords:Pooling  interpolation  factor model  Kalman filter  spline  C32  C43  C82
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