Asymptotics of the principal components estimator of large factor models with weak factors and i.i.d. Gaussian noise.

Thursday 25th January 2018
CINET:
1823
Onatski, A.
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.
Keywords
Large factor models
principal components
phase transition
weak factors
inconsistency
asymptotic distribution
Marčenko-Pastur law
C13
C33
Themes
empirical