Measuring intervention Effects on Multiple Time Series Subjected to Linear Restrictions: A Banking Example
研究如何估计受线性约束的时间序列向量的干预效应，提供了两种情形下的最小方差线性无偏估计量，并用银行业示例说明。
We 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 constraint, previous to the multivariate analysis, and the results of both analyses are required to be made compatible with each other. A banking example that motivated this work illustrates our solutions.