Small Area Estimation with State Space Common Factor Models for Rotating Panels
本文扩展了多变量结构时间序列模型，利用其他领域或强相关辅助序列的样本信息，提高旋转面板数据的小区域估计精度，已被荷兰统计局用于官方月度劳动力数据生产。
Summary Macroeconomic indicators about the labour force, published by national statistical institutes, are predominantly based on rotating panels. Sample sizes of most labour force surveys in combination with the design-based or model-assisted mode of inference obstruct the publication of such indicators on a monthly frequency. Previous research proposed a multivariate structural time series model to obtain more precise model-based estimates by taking advantage of sample information observed in previous periods. In the paper this model is extended to use sample information from other domains or strongly correlated auxiliary series. A relatively parsimonious version of these models is currently used by Statistics Netherlands to produce official monthly figures about the labour force.