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 discusses the implications of these conditions for empirical analyses. We also propose a computationally attractive IV estimator that is consistent under essentially the same conditions as existing estimators. While a Monte Carlo study indicates that this estimator may work well under relatively weak conditions, these conditions are not trivially satisfied in applied work. Accordingly, a key conclusion of the paper is that these estimators cannot be implemented under general conditions.

cohorts, individual dynamics, instrumental variables, pseudo-panel data, repeated cross-sections
Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions (jel C21), Models with Panel Data (jel C23), Methodology for Collecting, Estimating, and Organizing Microeconomic Data (jel C81),
Journal of Econometrics
Erasmus Research Institute of Management

Verbeek, M.J.C.M, & Vella, F. (2005). Estimating Dynamic Models from Repeated Cross-Sections. Journal of Econometrics, 127(1), 83–102. doi:10.1016/j.jeconom.2004.06.004