Minimal T for global identification relative to Ledermann bound

Ascertain whether global identification of the parameters in the dynamic panel data model with interactive effects (y_{it} = α y_{it−1} + δ_t + λ_i' f_t + ε_{it}) can be achieved under weaker time-dimension conditions than T ≥ 2( r + 1 ), specifically when T satisfies the Ledermann bound plus one, thereby reducing the required number of periods for identification in the dynamic setting.

Background

The paper proves global identification for dynamic panel models with interactive effects when the time dimension satisfies T ≥ 2( r + 1 ). This threshold exceeds the classical Ledermann bound from static factor models due to the inclusion of the autoregressive parameter α, which adds complexity to identification.

Determining whether global identification can be obtained under weaker T, such as the Ledermann bound plus one, would clarify the minimal data requirements for reliable estimation in dynamic panels and align the dynamic case more closely with established static results.