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从多项经济指标中提取非线性信号AI 解读

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one-step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two-step approach). Second, we…

Factor models have been applied extensively for forecasting when high-dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial…

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线性约束下多元时间序列干预效应的测量：银行业实例AI 解读

The authors consider the problem of estimating the effects of an intervention on a time-series vector subjected to a linear constraint. Minimum variance linear and unbiased estimators are provided for two different formulations of the problem--(1) when a multivariate intervention analysis is carried out and an adjustment is needed to fulfill the restriction and (2) when a univariate intervention analysis was performed on the aggregate series obtained from the linear…