Estimating Dynamic Models from Repeated Cross-Sections

Posted: 3 Jan 2006

See all articles by Marno Verbeek

Marno Verbeek

Erasmus University - Rotterdam School of Management; Erasmus Research Institute of Management (ERIM); Netspar

Francis Vella

Georgetown University; IZA Institute of Labor Economics

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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.

Keywords: repeated cross-sections, pseudo panel data, cohort data, instrumental variables

JEL Classification: C21, C23, C81

Suggested Citation

Verbeek, Marno and Vella, Francis, Estimating Dynamic Models from Repeated Cross-Sections. Journal of Econometrics, Vol. 127, No. 1, pp. 83-102, July 2005, Available at SSRN:

Marno Verbeek

Erasmus University - Rotterdam School of Management ( email )

P.O. Box 1738
Room T09-53
3000 DR Rotterdam
+31 10 408 2790 (Phone)


Erasmus Research Institute of Management (ERIM)

P.O. Box 1738
3000 DR Rotterdam


P.O. Box 90153
Tilburg, 5000 LE

Francis Vella (Contact Author)

Georgetown University ( email )

Washington, DC 20057
United States
202-687-5573 (Phone)


IZA Institute of Labor Economics

Schaumburg-Lippe-Str. 7 / 9
Bonn, D-53072

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