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Exploiting Information from Singletons in Panel Data Analysis: a GMM Approach

Bruno, R; Magazzini, L; Stampini, M; (2020) Exploiting Information from Singletons in Panel Data Analysis: a GMM Approach. Economics Letters , 186 , Article 108519. 10.1016/j.econlet.2019.07.004. Green open access

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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.

Type: Article
Title: Exploiting Information from Singletons in Panel Data Analysis: a GMM Approach
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.econlet.2019.07.004
Publisher version: https://doi.org/10.1016/j.econlet.2019.07.004
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Singleton, Panel data, Efficient estimation, Unobserved heterogeneity, GMM
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > SSEES
URI: https://discovery.ucl.ac.uk/id/eprint/10077461
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