多维动态因子模型
Multidimensional dynamic factor models
摘要：
本文推广了多维相依数据的动态因子模型。在这样做的过程中，它开发了一种可解释的技术，以研究复杂的信息来源，从对不同数量的答卷人进行的重复调查到卫星图像小组。我们专门研究我们的结果，以模拟美国家庭的微观经济数据与宏观经济总量。这导致了一个强大的工具，能够生成本地化的预测，反事实和脉冲响应函数为个别家庭，占传统的时间序列的复杂性描述的状态空间文献。该模型还与决策者日益关注的实时经济分析相兼容，因为它能够在线处理观察结果，同时处理缺失值和异步数据发布。
英文摘要：
This paper generalises dynamic factor models for multidimensional dependent data. In doing so, it develops an interpretable technique to study complex information sources ranging from repeated surveys with a varying number of respondents to panels of satellite images. We specialise our results to model microeconomic data on US households jointly with macroeconomic aggregates. This results in a powerful tool able to generate localised predictions, counterfactuals and impulse response functions for individual households, accounting for traditional time-series complexities depicted in the state-space literature. The model is also compatible with the growing focus of policymakers for real-time economic analysis as it is able to process observations online, while handling missing values and asynchronous data releases.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
