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dc.contributor.authorPesaran, H.en
dc.contributor.authorChudik, A.en
dc.date.accessioned2016-04-22T15:01:24Z
dc.date.available2016-04-22T15:01:24Z
dc.date.issued2013-05-15en
dc.identifier.otherCWPE1317
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/255275
dc.description.abstractThis paper extends the Common Correlated Effects (CCE) approach developed by Pesaran (2006) to heterogeneous panel data models with lagged dependent variable and/or weakly exogenous regressors. We show that the CCE mean group estimator continues to be valid but the following two conditions must be satisfied to deal with the dynamics: a sufficient number of lags of cross section averages must be included in individual equations of the panel, and the number of cross section averages must be at least as large as the number of unobserved common factors. We establish consistency rates, derive the asymptotic distribution, suggest using co- variates to deal with the effects of multiple unobserved common factors, and consider jackknife and recursive de-meaning bias correction procedures to mitigate the small sample time series bias. Theoretical findings are accompanied by extensive Monte Carlo experiments, which show that the proposed estimators perform well so long as the time series dimension of the panel is sufficiently large.en
dc.publisherFaculty of Economics
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserveden
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/en
dc.subjectcross sectional dependenceen
dc.subjectcoefficient heterogeneityen
dc.subjectestimation and inferenceen
dc.subjectcommon correlated effectsen
dc.subjectunobserved common factors.en
dc.titleCommon Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressorsen
dc.typeWorking Paperen
dc.identifier.doi10.17863/CAM.5745


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