A quasi-differencing approach to dynamic modelling from a time series of independent cross-sections

We motivate and describe a GMM method of estimating linear dynamic models from a time series of independent cross-sections. This involves subjecting the model to a quasi-differencing transformation across pairs of individuals that belong to the same group. Desirable features of the model include the fact that: (i) no aggregation is involved, (ii) dynamic response parameters can vary across groups, (iii) the presence of unobserved individual specific heterogeneity is explicitly allowed for, and (iv) the GMM estimators are derived by realistically assuming group size asymptotics. The Monte Carlo experiments conducted to assess the finite sample performances of the proposed estimators provide us with encouragement.