This paper stresses the links that exist between concepts that are used in the theory of model reduction and concepts that arise in the missing data literature. This connection motivates the extension of the missing at random (MAR) and the missing completely at random (MCAR) concepts from a static setting, as introduced by Rubin (1976), to the case of dynamic panel data models. Using this exten...

Lancaster (2002) proposes an estimator for the dynamic panel data model with homoskedastic errors and zero initial conditions. In this paper, we show is invariant to orthogonal transformations, but inefficient because it ignores additional information available in data. The condition trivially satisfied by subtracting observations from We that differencing out further erodes efficiency compared...