期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2003
出版社：European Central Bank
摘要：Existing methods for data interpolation or backdating are either uni- variate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowa- days large datasets are readily available, and models with hundreds of parameters are fastly estimated. We model these large datasets with a factor model, and develop an interpolation method that exploits the estimated factors as an efficient summary of all the available infor- mation. The method is compared with existing standard approaches from a theoretical point of view, by means of Monte Carlo simula- tions, and also when applied to actual macroeconomic series. The results indicate that our method is more robust to model misspeciÞ- cation, although traditional multivariate methods also work well while univariate approaches are systematically outperformed. When interpo- lated series are subsequently used in econometric analyses, biases can emerge, depending on the type of interpolation but again be reduced with multivariate approaches, including factor-based ones.
