A method for evaluating the rank condition for CCE estimators

De Vos, Ignace and Everaert, Gerdie and Sarafidis, Vasilis (2021): A method for evaluating the rank condition for CCE estimators.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Common Factors, Common Correlated Effects approach, rank condition
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C23 - Panel Data Models ; Spatio-temporal Models; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection; G - Financial Economics > G2 - Financial Institutions and Services > G21 - Banks ; Depository Institutions ; Micro Finance Institutions ; Mortgages

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