Determining the number of factors in approximate factor models by twice K-fold cross validation

DOI10.1016/j.econlet.2020.109149zbMath1443.62163OpenAlexW3015301926WikidataQ112880962 ScholiaQ112880962MaRDI QIDQ777679

Hui Chen, Jie Wei

Publication date: 7 July 2020

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.econlet.2020.109149

zbMATH Keywords

consistencyapproximate factor modelsfinite sample performanceK-fold cross validation

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Causal inference from observational studies (62D20)

Related Items (3)

Estimation of high dimensional factor model with multiple threshold-type regime shifts ⋮ Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion ⋮ Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components

Cites Work

• Cross-validation for selecting a model selection procedure
• Consistency of cross validation for comparing regression procedures
• Estimation in semiparametric spatial regression
• Eigenvalue Ratio Test for the Number of Factors
• Stability Selection
• Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series
• Linear Model Selection by Cross-Validation
• Determining the Number of Factors in the General Dynamic Factor Model
• A Testing Procedure for Determining the Number of Factors in Approximate Factor Models With Large Datasets
• Determining the Number of Factors in Approximate Factor Models

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