On the Role of the Rank Condition in CCE Estimation of Factor-Augmented Panel Regressions
Research output: Contribution to journal › Article
A popular approach to factor-augmented panel regressions is the common correlatedeffects (CCE) estimator of Pesaran (Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74, 967–1012, 2006). This paper points to a problem with the CCE approach that appears in the empirically relevant case when the number of factors is strictly less than the number of observables used in their estimation. Specifically, the use of too many observables causes the second moment matrix of the estimated factors to become asymptotically singular, an issue that has not yet been appropriately accounted for. The purpose of the present paper is to fill this gap in the literature.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Number of pages||5|
|Journal||Journal of Econometrics|
|Early online date||2016 Oct 28|
|Publication status||Published - 2017 Mar|
Related research output
Simon Reese, 2017 Mar 2, Lund: Lund University (Media-Tryck). 227 p.
Research output: Thesis › Doctoral Thesis (compilation)