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Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm

Matteo Barigozzi, Matteo Luciani

arXiv 9 Oct 2019 · Mathematics — Statistics Theory · publishedFinance and Economics Discussion Series (2024) · 12 citations (OpenAlex)

arXiv:1910.03821 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study estimation of large Dynamic Factor models implemented through the Expectation Maximization (EM) algorithm, jointly with the Kalman smoother. We prove that as both the cross-sectional dimension, $n$, and the sample size, $T$, diverge to infinity: (i) the estimated loadings are $\sqrt T$-consistent, asymptotically normal and equivalent to their Quasi Maximum Likelihood estimates; (ii) the estimated factors are $\sqrt n$-consistent, asymptotically normal and equivalent to their Weighted Least Squares estimates. Moreover, the estimated loadings are asymptotically as efficient as those obtained by Principal Components analysis, while the estimated factors are more efficient if the idiosyncratic covariance is sparse enough.

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140
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576
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315
distinct cited
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Bai, J. and K. Li (2016) Maximum likelihood estimation and inference for approximate factor models of high dimension1.000278100%
2Bai, J (2003) Inferential theory for factor models of large dimensions1.000217100%
3Barigozzi, M (2023) Asymptotic equivalence of principal component and quasi maximum likelihood estimators in large approximate factor models self1.000198100%
4Merikoski, J. K. and R. Kumar (2004) Inequalities for spreads of matrix sums and products1.000196100%
5Doz, C., D. Giannone, and L. Reichlin (2012) A quasi maximum likelihood approach for large approximate dynamic factor models1.000147100%
6Bai, J. and K. Li (2012) Statistical analysis of factor models of high dimension1.00095100%
7Hamilton, J. D (1994) Time Series Analysis1.00064100%
8Fan, J., Y. Liao, and M. Mincheva (2013) Large covariance estimation by thresholding principal orthogonal complements1.00063100%
9Wu, J. C. F (1983) On the convergence properties of the EM algorithm1.00063100%
10Doz, C., D. Giannone, and L. Reichlin (2011) A two-step estimator for large approximate dynamic factor models based on Kalman filtering0.92843100%

Showing the top 10 of 315 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Quasi Maximum Likelihood Estimation of Non-Stationary Large Approximate Dynamic Factor Models1.000154
2Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review1.000114
3Probabilistic Targeted Factor Analysis0.73733
4Measuring the Euro Area Output Gap$^$0.73732
5Deep Dynamic Factor Models0.64422
6The Dynamic, the Static, and the Weak factor models and the analysis of high-dimensional time series0.64422
7Heterogeneous economic growth vulnerability across Euro Area countries under stressed scenarios0.64422
8Estimation of impulse-response functions with dynamic factor models: a new parametrization0.51121
9Modelling Large Dimensional Datasets with Markov Switching Factor Models0.51121
10Estimation of large approximate dynamic matrix factor models based on the EM algorithm and Kalman filtering0.43782