The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Statistical analysis of factor models of high dimension
Open accessAbstract
This paper considers the maximum likelihood estimation of factor models of high dimension, where the number of variables (N) is comparable with or even greater than the number of observations (T). An inferential theory is developed. We establish not only consistency but also the rate of convergence and the limiting distributions. Five different sets of identification conditions are considered. We show that the distributions of the MLE estimators depend on the identification restrictions. Unlike the principal components approach, the maximum likelihood estimator explicitly allows heteroskedasticities, which are jointly estimated with other parameters. Efficiency of MLE relative to the principal components method is also considered.
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Cites
An Introduction to Multivariate Statistical Analysis
Muirhead, R. J., & Anderson, T. W. (1986) · Journal of Business & Economic Statistics · doi:10.2307/1391399 · Cited by 9,082
The arbitrage theory of capital asset pricing
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The Econometrics of Financial Markets
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2012) · Princeton University Press eBooks · doi:10.2307/j.ctt7skm5 · Cited by 5,875
The Econometrics of Financial Markets
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Determining the Number of Factors in Approximate Factor Models
Bai, J., & Ng, S. (2002) · Econometrica · doi:10.1111/1468-0262.00273 · Cited by 4,099
Self-citationOn the Convergence Properties of the EM Algorithm
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Forecasting Using Principal Components From a Large Number of Predictors
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Macroeconomic Forecasting Using Diffusion Indexes
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Cited by
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, J., Liao, Y., & Mincheva, M. (2013) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/rssb.12016 · Cited by 909
Item Response Theory: A Statistical Framework for Educational and Psychological Measurement
Chen, Y., Li, X., Liu, J., & Ying, Z. (2025) · Statistical Science · doi:10.1214/23-sts896 · Cited by 30
Metadata
- Authors
- Bai, J., & Li, K.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 2012-02-01
- Volume
- 40
- Issue
- 1
- Pages
- 436-465
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W2074609004
- Cited by
- 310
- References
- 27
- FWCI
- 11.39
- Type
- journal article
- Language
- en
- Open access
- bronze
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