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Inference on factor structures in heterogeneous panels

Castagnetti, Carolina; Rossi, Eduardo; Trapani, Lorenzo

Authors

Carolina Castagnetti

Eduardo Rossi



Abstract

This paper develops an estimation and testing framework for a stationary large panel model with observable regressors and unobservable common factors. We allow for slope heterogeneity and for correlation between the common factors and the regressors. We propose a two stage estimation procedure for the unobservable common factors and their loadings, based on Common Correlated Effects estimator and the Principal Component estimator. We also develop two tests for the null of no factor structure: one for the null that loadings are cross sectionally homogeneous, and one for the null that common factors are homogeneous over time. Our tests are based on using extremes of the estimated loadings and common factors. The test statistics have an asymptotic Gumbel distribution under the null, and have power versus alternatives where only one loading or common factor differs from the others. Monte Carlo evidence shows that the tests have the correct size and good power.

Journal Article Type Article
Publication Date Jan 1, 2015
Journal Journal of Econometrics
Print ISSN 0304-4076
Electronic ISSN 0304-4076
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 184
Issue 1
APA6 Citation Castagnetti, C., Rossi, E., & Trapani, L. (2015). Inference on factor structures in heterogeneous panels. Journal of Econometrics, 184(1), https://doi.org/10.1016/j.jeconom.2014.08.004
DOI https://doi.org/10.1016/j.jeconom.2014.08.004
Keywords Large panels; CCE estimator; Principal Component estimator; Testing for factor structure; Extreme Value distribution
Publisher URL http://www.sciencedirect.com/science/article/pii/S0304407614001808
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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