Asymptotics of the principal components estimator of large factor models with weak factors and i.i.d. Gaussian noise.
Cambridge Working Papers in Economics
MetadataShow full item record
Onatski, A. (2018). Asymptotics of the principal components estimator of large factor models with weak factors and i.i.d. Gaussian noise.. https://doi.org/10.17863/CAM.21783
We consider large factor models where factors' explanatory power does not strongly dominate the explanatory power of the idiosyncratic terms asymptotically. We find the first and second order asymptotics of the principal components estimator of such a weak factors as the dimensionality of the data and the number of observations tend to infinity proportionally. The principal components estimator is inconsistent but asymptotically normal.
Large factor models, principal components, phase transition, weak factors, inconsistency, asymptotic distribution, Marčenko-Pastur law.
This record's DOI: https://doi.org/10.17863/CAM.21783
This record's URL: https://www.repository.cam.ac.uk/handle/1810/274650
All Rights Reserved
Licence URL: https://www.rioxx.net/licenses/all-rights-reserved/