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

Randolph Bruno, Laura Magazzini and Marco Stampini

Economics Letters, 2020, vol. 186, issue C

Abstract: 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.

Keywords: Singletons; Panel data; Efficient estimation; Unobserved heterogeneity; GMM (search for similar items in EconPapers)
JEL-codes: C23 C33 C51 (search for similar items in EconPapers)
Date: 2020
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Working Paper: Exploiting Information from Singletons in Panel Data Analysis: A GMM Approach (2019) Downloads
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DOI: 10.1016/j.econlet.2019.07.004

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