Large factor models and large random matrices

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.

For more information, contact Frank Schorfheide.