Dynamic panel GMM using R

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dc.contributor.author Phillips, Peter en
dc.contributor.author Han, C en
dc.date.accessioned 2020-04-21T01:40:20Z en
dc.date.issued 2019-01-01 en
dc.identifier.isbn 9780444643117 en
dc.identifier.uri http://hdl.handle.net/2292/50443 en
dc.description.abstract © 2019 Elsevier B.V. GMM methods for estimating dynamic panel regression models are heavily used in applied work in many areas of economics and more widely in the social and business sciences. Software packages in STATA and GAUSS are commonly used in these applications. We provide a new R program for difference GMM, system GMM, and within-group estimation for simulation with the model we consider that is based on a standard first-order dynamic panel regression with individual- and time-specific effects. The program lacks the generality of a full package but provides a foundation for further development and is optimized for speed, making it particularly useful for large panels and simulation purposes. The program is illustrated in simulations that include both stationary and nonstationary cases. Particular attention in the simulations is given to analyzing the impact of fixed effect heterogeneity on bias in system GMM estimation compared with the other methods. en
dc.relation.ispartof Handbook of Statistics en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Dynamic panel GMM using R en
dc.type Book Item en
dc.identifier.doi 10.1016/bs.host.2019.01.002 en
pubs.begin-page 119 en
pubs.volume 41 en
dc.rights.holder Copyright: The author en
pubs.end-page 144 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.elements-id 764076 en
pubs.org-id Business and Economics en
pubs.org-id Economics en

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