Short-Term GDP Forecasting With a Mixed-Frequency Dynamic Factor Model With Stochastic Volatility
开发了一个混频动态因子模型，其中共同因子和异质性成分的扰动均具有时变随机波动性，用于欧元区商业周期分析，发现引入随机波动能提升点预测和密度预测的准确性。
In this article, we develop a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time-varying stochastic volatilities. We use the model to investigate business cycle dynamics in the euro area and present three sets of empirical results. First, we evaluate the impact of macroeconomic releases on point and density forecast accuracy and on the width of forecast intervals. Second, we show how our setup allows to make a probabilistic assessment of the contribution of releases to forecast revisions. Third, we examine point and density out of sample forecast accuracy. We find that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy. Supplementary materials for this article are available online.