Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In a recent study, Bai (2013) proposes a new factor analytical (FA) method for estimation of stationary dynamic panel data models with fixed effects. Our interest in this method originates with the fact it does not require explicit demeaning of the data, a practice that is known to cause problems of bias and low power in near unit root panels. The purpose is to study the properties of FA when applied to such panels when the common component admits to a interactive effects representation, which is more general than fixed effects. It is shown that the estimator of the autoregressive parameter is consistent with a well centered asymptotic normal distribution, leading to unit root tests with maximal achievable power. In fact, FA is consistent and asymptotically normal regardless of whether the data are near unit root non-stationary or stationary. It is therefore very general and hence widely applicable.