Inference in Weak Factor Models

Material type: 文書・図像類

Author: Uematsu, Yoshimasaほか

Publisher: The Institute of Social and Economic Research, Osaka University

Publication date: 2020-03

Material Format: Paper

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Note (General)：: In this paper, we consider statistical inference for high-dimensional approximate factor models. We posit a weak factor structure, in which the factor...

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Paper

Material Type: 文書・図像類
Title: Inference in Weak Factor Models
Author/Editor: Uematsu, Yoshimasa
Yamagata, Takashi
Author Heading: Uematsu, Yoshimasa
https://nrid.nii.ac.jp/nrid/1000040835279
Yamagata, Takashi
https://nrid.nii.ac.jp/nrid/1000020813231
Publication, Distribution, etc.: The Institute of Social and Economic Research, Osaka University
Publication Date: 2020-03
Publication Date (W3CDTF): 2020-03
Periodical title: Institute of Social and Economic Research Discussion Papers
No. or year of volume/issue: 1080
Volume: 1080
Pages: 1-42
ISSN (Periodical Title): PISSN : 0473453X
EISSN : 24350982
Text Language Code: eng
Subject Heading: Approximate factor models
Debiased SOFAR estimator
Multiple testing
FDR and Power
Re-sparsification
Target Audience: 一般
Note (General): In this paper, we consider statistical inference for high-dimensional approximate factor models. We posit a weak factor structure, in which the factor loading matrix can be sparse and the signal eigenvalues may diverge more slowly than the cross-sectional dimension, N. We propose a novel inferential procedure to decide whether each component of the factor loadings is zero or not, and prove that this controls the false discovery rate (FDR) below a pre-assigned level, while the power tends to unity. This "factor selection" procedure is primarily based on a de-sparsified (or debiased) version of the WF-SOFAR estimator of Uematsu and Yamagata (2020), but is also applicable to the principal component (PC) estimator. After the factor selection, the re-sparsified WFSOFAR and sparsified PC estimators are proposed and their consistency is established. Finite sample evidence supports the theoretical results. We apply our procedure to the FRED-MD macroeconomic and financial data, consisting of 128 series from June 1999 to May 2019. The results strongly suggest the existence of sparse factor loadings and exhibit a clear association of each of the extracted factors with a group of macroeconomic variables. In particular, we find a price factor, housing factor, output and income factor, and a money, credit and stock market factor.
References (URI): http://www.iser.osaka-u.ac.jp/library/dp/2020/DP1080.pdf
URI
http://www.iser.osaka-u.ac.jp/library/dp/2020/DP1080.pdf
Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
https://irdb.nii.ac.jp
Original Data Provider (Database): 大阪大学 : 大阪大学学術情報庫　桜華