Show simple item record

dc.contributor.authorBarbosa, José Diogo Valadares Moreira
dc.contributor.authorMoreira, Marcelo J.
dc.date.accessioned2017-10-03T17:32:17Z
dc.date.available2017-10-03T17:32:17Z
dc.date.issued2017-10
dc.identifier.issn0104-8910
dc.identifier.urihttp://hdl.handle.net/10438/18902
dc.description.abstractLancaster (2002) proposes an estimator for the dynamic panel data model with homoskedastic errors and zero initial conditions. In this paper, we show this estimator is invariant to orthogonal transformations, but is ine cient because it ignores additional information available in the data. The zero initial condition is trivially satis ed by subtracting initial observations from the data. We show that di erencing out the data further erodes e ciency compared to drawing inference conditional on the rst observations. Finally, we compare the conditional method with standard random e ects approaches for unobserved data. Standard approaches implicitly rely on normal approximations, which may not be reliable when unobserved data is very skewed with some mass at zero values. For example, panel data on rms naturally depend on the rst period in which the rm enters on a new state. It seems unreasonable then to assume that the process determining unobserved data is known or stationary. We can instead make inference on structural parameters by conditioning on the initial observations.eng
dc.language.isoeng
dc.publisherEscola de Pós-Graduação em Economia da FGVpor
dc.relation.ispartofseriesEnsaios Econômicos;788por
dc.subjectAutoregressiveeng
dc.subjectPanel dataeng
dc.subjectInvarianceeng
dc.subjectEficiencyeng
dc.titleLikelihood inference and the role of initial conditions for the dynamic panel data modeleng
dc.typeWorking Papereng
dc.subject.areaEconomiapor
dc.contributor.unidadefgvEscolas::EPGEpor
dc.subject.bibliodataModelagem de dadospor
dc.subject.bibliodataAnálise de variânciapor
dc.contributor.affiliationFGV


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record