文章基本信息

标题：Forecasting fiscal time series using mixed frequency data
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作者：Stylianos Asimakopoulos ; Joan Paredes ; Thomas Warmedinger 等
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：2013
出版社：European Central Bank
摘要：Given the increased importance of scal monitoring, this study amends the existing literature in the eld of intra-annual scal data in two main dimen- sions. First, we use quarterly scal data to forecast a very disaggregated set of scal series at annual frequency. This makes the analysis useful in the typical forecasting environment of large institutions, which employ a "bottom-up" or disaggregated framework. Aside from this practical type of consideration, we nd that forecasts for total revenues and expenditures via their subcomponents can actually result more accurate than a direct fore- cast of the aggregate. Second, we employ a Mixed Data Sampling (MiDaS) approach to analyze mixed frequency scal data, which is a methodological novelty. It is shown that MiDaS is the best approach for the analysis of mixed frequency scal data compared to two alternative approaches. The results regarding the information content of quarterly scal data conrm previous work that such data should be taken into account as it becomes available throughout the year for improving the end-year forecast. For instance, once data for the third quarter is incorporated, the annual forecast becomes very accurate (very close to actual data). We also benchmark against the Euro- pean Commissions forecast and nd the results fare favorably, particularly when considering that they stem from a simple univariate framework.
关键词：Fiscal policy; Mixed frequency data; Short-term forecasting;Aggregated vs. disaggregated forecast.