arXiv 1 Aug 2020 · Econometrics · 3 citations (OpenAlex)
arXiv:2008.00254 · PDF · DOI · OpenAlex · Extracted main text
Estimates of the approximate factor model are increasingly used in empirical work. Their theoretical properties, studied some twenty years ago, also laid the ground work for analysis on large dimensional panel data models with cross-section dependence. This paper presents simplified proofs for the estimates by using alternative rotation matrices, exploiting properties of low rank matrices, as well as the singular value decomposition of the data in addition to its covariance structure. These simplifications facilitate interpretation of results and provide a more friendly introduction to researchers new to the field. New results are provided to allow linear restrictions to be imposed on factor models.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Bai and Ng (2002) Determining the Number of Factors in Approximate Factor Models, Econometrica 70:1, 191–221 | 1.000 | 8 | 4 | 100% |
| 2 | Bai (2003) Inferential Theory for Factor Models of Large Dimensions, Econometrica 71:1, 135–172 self | 0.928 | 4 | 4 | 100% |
| 3 | Bai and Ng (2019) Regularized Estimation of Approximate Factor Models, Journal of Econometrics 78-96, 212:1 | 0.843 | 3 | 3 | 100% |
| 4 | Anderson and Rubin (1956) Statistical Inference in Factor Analysis, in J. Neyman (ed.), Proceedings of the Third Berkeley Symposium on Mathematical Statis… | 0.737 | 3 | 2 | 100% |
| 5 | Chamberlain and Rothschild (1983) Arbitrage, Factor Structure and Mean-Variance Analysis in Large Asset Markets, Econometrica 51, 1281–2304 | 0.644 | 2 | 2 | 100% |
| 6 | Stock and Watson (1998) Diffusion Indexes, NBER Working Paper 6702 | 0.644 | 2 | 2 | 100% |
| 7 | Stock and Watson (2002) Forecasting Using Principle Components from a Large Number of Predictors, Journal of American Statistical Association 97(460), 1… | 0.644 | 2 | 2 | 100% |
| 8 | Cattell (1966) The Scree Test for the Number of Factors, Multivariate Behavioral Research 1, 245–276 | 0.511 | 2 | 1 | 100% |
| 9 | Ahn and Horenstein (2013) Eigenvalue Ratio Test for the Number of Factors, Econometrica 81:3, 1203–1227 | 0.405 | 1 | 1 | 100% |
| 10 | Bai and Wang (2014) Identification Theory for High Dimensional Static and Dynamic Factor Models, Journal of Econometrics 178(2), 794–804 | 0.405 | 1 | 1 | 100% |
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