Inference on Factor Structures in Heterogeneous Panels

Carolina Castagnetti, Eduardo Rossi and Lorenzo Trapani ()

No 2, DEM Working Papers Series from University of Pavia, Department of Economics and Management

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 applying Pesaran’s (2006) CCE 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.

Keywords: Large Panels; CCE Estimator; Principal Component Estimator; Testing for Factor Structure; Extreme Value Distribution. (search for similar items in EconPapers)
JEL-codes: C12 C33 (search for similar items in EconPapers)
Pages: 61 pages
Date: 2012-09
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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http://dem-web.unipv.it/web/docs/dipeco/quad/ps/RePEc/pav/demwpp/DEMWP0002.pdf (application/pdf)

Related works:
Journal Article: Inference on factor structures in heterogeneous panels (2015)
Working Paper: Inference on Factor Structures in Heterogeneous Panels (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:pav:demwpp:demwp0002

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