Panels with non-stationary multifactor error structures

The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently, work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference in the case of stationary panel regressions with a multifa...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of econometrics Jg. 160; H. 2; S. 326 - 348
Hauptverfasser:	Kapetanios, G., Pesaran, M. Hashem, Yamagata, T.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.02.2011 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	Journal of Econometrics
Schlagworte:	Applications Asymptotic methods Bias Common correlated effects Correlation analysis Cross-section dependence Cross-section dependence Large panels Unit roots Principal components Common correlated effects Data analysis Distribution Distribution theory Econometrics Estimating techniques Estimation Exact sciences and technology Inference Insurance, economics, finance Large panels Linear inference, regression Logic and foundations Mathematical logic, foundations, set theory Mathematics Model theory Monte Carlo method Monte Carlo simulation Panel data Principal components Probability and statistics Sciences and techniques of general use Statistics Stochastic processes Studies Unit root Unit roots C33 C13 Cross-section dependence C12 Unit roots Common correlated effects Large panels Principal components Statistical distribution Error estimation Non parametric estimation Multivariate analysis Stochastic method Unit root Correspondence analysis Panel data Cross sectional study Approximation theory Monte Carlo method Data analysis Factor analysis Asymptotic behavior Average Statistical estimation Mean estimation Statistical method Statistical regression Numerical analysis Correlation analysis Small sample Econometrics Principal component analysis Biased estimation
ISSN:	0304-4076, 1872-6895
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!