Show simple item record

dc.contributor.authorNorkutė, Milda
dc.contributor.authorSarafidis, Vasilis
dc.contributor.authorYamagata, Takashi
dc.contributor.authorCui, Guowei
dc.date.accessioned2023-09-26T08:39:14Z
dc.date.available2023-09-26T08:39:14Z
dc.date.created2020-06-30T18:08:55Z
dc.date.issued2021
dc.identifier.citationJournal of Econometrics. 2021, 220 (2), 416-446.en_US
dc.identifier.issn0304-4076
dc.identifier.urihttps://hdl.handle.net/11250/3091954
dc.description.abstractThis paper develops two instrumental variable (IV) estimators for dynamic panel data models with exogenous covariates and a multifactor error structure when both the cross-sectional and time series dimensions, and respectively, are large. The main idea is to project out the common factors from the exogenous covariates of the model, and to construct instruments based on defactored covariates. For models with homogeneous slope coefficients, we propose a two-step IV estimator. In the first step, the model is estimated consistently by employing defactored covariates as instruments. In the second step, the entire model is defactored based on estimated factors extracted from the residuals of the first-step estimation, after which an IV regression is implemented using the same instruments as in step one. For models with heterogeneous slope coefficients, we propose a mean-group-type estimator, which involves the averaging of first-step IV estimates of cross-section-specific slopes. The proposed estimators do not need to seek for instrumental variables outside the model. Furthermore, these estimators are linear, and therefore computationally robust and inexpensive. Notably, they require no bias correction. We investigate the finite sample performances of the proposed estimators and associated statistical tests, and the results show that the estimators and the tests perform well even for small N and T.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.titleInstrumental variable estimation of dynamic linear panel data models with defactored regressors and a multifactor error structureen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber416-446en_US
dc.source.volume220en_US
dc.source.journalJournal of Econometricsen_US
dc.source.issue2en_US
dc.identifier.doi10.1016/j.jeconom.2020.04.008
dc.identifier.cristin1817938
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal