This paper explores how cross-sectional data can be exploited jointly with longitudinal data, in order to increase estimation efficiency while properly tackling the potential bias due to unobserved individual characteristics. We propose an innovative procedure and we show its implementation by...

We propose a novel procedure, built within a Generalized Method of Moments framework, which exploits unpaired observations (singletons) to increase the efficiency of longitudinal fixed effect estimates. The approach allows increasing estimation efficiency, while properly tackling the bias due to...

We propose a novel procedure, built within a Generalized Method of Moments framework, which exploits unpaired observations (singletons) to increase the efficiency of longitudinal fixed effect estimates. The approach allows increasing estimation efficiency, while properly tackling the bias due to...