Estimating dynamic models from repeated cross-sections

An important feature of panel data is that it allows the estimation of parameters characterizing dynamics from individual level data. Several authors argue that such parameters can also be identified from repeated cross-section data and present estimators to do so. This paper reviews the identification conditions underlying these estimators. As grouping data to obtain a pseudo-panel is an application of instrumental variables (IV), identification requires that standard IV conditions are met. This paper explicitly discuss the implications of these conditions for empirical analyses. We also propose a computationally attractive instrumental variables estimator that is consistent under a relatively weak set of conditions. A Monte Carlo study indicates that this estimator may work well in practice.