关于潜在群结构因子模型的注解

IF 2.1 4区经济学 Q2 ECONOMICS

Economics Letters Pub Date : 2025-05-02 DOI:10.1016/j.econlet.2025.112357

Yulin Bian, Liangjun Su

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引用次数: 0

摘要

本文研究了一个具有潜在群结构的因子模型。在初始PCA估计的基础上，我们提出应用顺序二值分割算法（SBSA）来估计组结构，并重新估计因子和负载。在群体数量未知的情况下，我们建议通过信息准则来估计群体数量。我们建立了所提估计量的渐近性质。仿真结果表明，在有限的样本中，我们提出的估计方法优于一些竞争方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A note on factor models with latent group structures

This paper studies a factor model with latent group structures. Given initial PCA estimates, we propose to apply the sequential binary segmentation algorithm (SBSA) to estimate the group structures and re-estimate the factors and loadings. In the case of unknown number of groups, we propose to estimate it via an information criterion. We establish the asymptotic properties of the proposed estimators. Simulations demonstrate that our proposed estimator outperforms some competitive approaches in finite samples.

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来源期刊

Economics Letters ECONOMICS-

CiteScore

3.20

自引率

5.00%

发文量

348

审稿时长

30 days

期刊介绍： Many economists today are concerned by the proliferation of journals and the concomitant labyrinth of research to be conquered in order to reach the specific information they require. To combat this tendency, Economics Letters has been conceived and designed outside the realm of the traditional economics journal. As a Letters Journal, it consists of concise communications (letters) that provide a means of rapid and efficient dissemination of new results, models and methods in all fields of economic research.