A method for evaluating the rank condition for CCE estimators

Ignace De Vos, Gerdie Everaert and Vasilis Sarafidis

MPRA Paper from University Library of Munich, Germany

Abstract: This paper proposes a binary classifier to evaluate the rank condition (RC) that is required for consistency of the Common Correlated Effects (CCE) estimator. The RC postulates that the number of unobserved factors, m, is not larger than the rank of the unobserved matrix of average factor loadings, \rho. The key insight in this paper is that \rho can be consistently estimated with existing techniques through the matrix of cross-sectional averages of the data. Similarly, m can be estimated consistently from the data using existing methods. A binary classifier, constructed by comparing estimates of m and \rho, correctly determines whether the RC is satisfied or not as (N,T) -> infinity. We illustrate the practical relevance of testing the RC by studying the effect of the Dodd-Frank Act on bank profitability.

Keywords: Common Factors; Common Correlated Effects approach; rank condition (search for similar items in EconPapers)
JEL-codes: C13 C23 C52 G21 (search for similar items in EconPapers)
Date: 2021-04-01, Revised 2022-03-09
New Economics Papers: this item is included in nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/112305/1/MPRA_paper_112305.pdf original version (application/pdf)

Related works:
Working Paper: A method for evaluating the rank condition for CCE estimators (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:112305

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().