Exploiting information from singletons in panel data analysis: A GMM approach

Randolph Luca Bruno, Laura Magazzini*, Marco Stampini

*Autore corrispondente per questo lavoro

Risultato della ricerca: Contributo in rivistaArticolo in rivista


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 unobserved time-invariant characteristics. We assess its properties by means of Monte Carlo simulations, and apply it to a traditional Total Factor Productivity regression, showing efficiency gains of approximately 8–9 percent.
Lingua originaleEnglish
pagine (da-a)108519-108522
Numero di pagine4
RivistaEconomics Letters
Stato di pubblicazionePubblicato - 2020


  • Efficient estimation
  • GMM
  • Panel data
  • Singletons
  • Unobserved heterogeneity


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