权衡(T)篮子:欧元区的总体和基于组成部分的通胀预测

Andrej Sokol, M. Porqueddu, Jakub Chalmovianský
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引用次数: 1

摘要

我们比较了欧元区和五个成员国对HICP和排除能源和食品的HICP的直接预测,以及对其主要组成部分的汇总预测,这些主要组成部分来自具有一组共享预测因子的大型贝叶斯var。我们专注于条件点和密度预测,与许多政策机构的预测实践一致。我们的主要发现是,点预测在使用两种方法时表现相似,而直接预测总指数往往会产生更好的密度预测。在金融危机之后,相对的预测表现通常只受到暂时的影响。欧元体系/欧洲央行工作人员所做的通胀预测与我们对欧元区的模型所做的预测相似或略好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weigh(T)Ing the Basket: Aggregate and Component-Based Inflation Forecasts for the Euro Area
We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with forecasting practices at many policy institutions. Our main findings are that point forecasts perform similarly using both approaches, whereas directly forecasting aggregate indices tends to yield better density forecasts. In the aftermath of the Great Financial Crisis, relative forecasting performance was typically only affected temporarily. Inflation forecasts made by Eurosystem/ECB staff perform similarly or slightly better than those from our models for the euro area.
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