On GMM estimation of linear dynamic panel data models
Markus Fritsch
No B-36-19, Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe from University of Passau, Faculty of Business and Economics
Abstract:
The linear dynamic panel data model provides a possible avenue to deal with unobservable individual-specific heterogeneity and dynamic relationships in panel data. The model structure renders standard estimation techniques inconsistent. Estimation and inference can, however, be carried out with the generalized method of moments (GMM) by suitably aggregating population orthogonality conditions directly deduced from the underlying modeling assumptions. Different variations of these assumptions are proposed in the literature - often lacking a thorough discussion of the implications for estimation and inference. This paper aims to enhance the understanding of the assumptions and their interplay by connecting the assumptions and the conditions required to establish identification and consistency, derive the asymptotic properties, and carry out inference for the GMM estimator.
Keywords: GMM; linear dynamic panel data model; identi cation; large sample properties; inference (search for similar items in EconPapers)
JEL-codes: C10 C23 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:upadbr:b3619
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