Dynamic specification tests for static factor models

Abstract

We derive score tests of serial correlation in the levels and squares of common and idiosyncratic factors in static factor models. The implicit orthogonality conditions resemble the orthogonality conditions of models with observed factors but the weighting matrices reflect their unobservability. We robustify our tests against fat-tails, and derive more powerful versions when the conditional distribution is elliptically symmetric, which can be either parametrically or semipametrically specified. We conduct Monte Carlo exercises to study the finite sample reliability and power of our proposed tests. Finally, we illustrate our methods with an empirical application to monthly US stock returns".

Keywords

JEL codes