A multilevel factor model: Identification, asymptotic theory and applications
A multilevel factor model: Identification, asymptotic theory and applications
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多级因子模型：辨识、渐近理论和应用
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Noh
中科院分区：
文献类型：
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作者：
In Choi;Dukpa Kim;Yun;Noh
本文研究了具有全球和国家因素的多层次因素模型。全球因素影响所有个人，而国家因素仅影响每个特定国家/地区内的个人。提出了分别识别全球和国家因素的顺序程序。在第一步中，通过典型相关分析来估计全局因素。使用该初始估计量，构建全球和国家因素的主成分估计量 (PCE)。结果表明，PCE 对全球和国家因素空间的估计是一致的，并且在极限内呈正态分布。提出了几种可以估计国家因素数量的信息标准。假设全局因子的数量是已知的。大量的模拟结果表明，顺序过程和信息标准在有限样本中运行良好。本文的方法被应用于25个OECD国家来识别国际经济周期。据报道，该方法可以很好地提取全局因子。
This paper studies a multilevel factor model with global and country factors. The global factors affect all individuals while the country factors affect only those within each specific country. A sequential procedure to identify the global and country factors separately is proposed. In the initial step, the global factors are estimated by canonical correlation analysis. Using this initial estimator, the principal component estimators (PCEs) of the global and country factors are constructed. It is shown that the PCEs estimate the spaces of the global and country factors consistently and are normally distributed in the limit. Several information criteria that can estimate the numbers of the country factors are proposed. The number of the global factors is assumed to be known. Extensive simulation results demonstrate that the sequential procedure and the information criteria work well in finite samples. The method of this paper is applied to 25 OECD countries to identify international business cycle. It is reported that the method extracts a global factor reasonably well.