Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels

SERIES Working papers N. 02/2019

44 Pages Posted: 18 Jun 2019

See all articles by George Kapetanios

George Kapetanios

King's College, London

Laura Serlenga

Università degli Studi di Bari “Aldo Moro” (UNIBA) - Dipartimento di Economia e Finanza

Yongcheol Shin

Independent

Date Written: June 2019

Abstract

A large strand of the literature on panel data models has focused on explicitly modelling the cross-section dependence between panel units. Factor augmented approaches have been proposed to deal with this issue. Under a mild restriction on the correlation of the factor loadings, we show that factor augmented panel data models can be encompassed by a standard two-way fixed effect model. This highlights the importance of verifying whether the factor loadings are correlated, which, we argue, is an important hypothesis to be tested, in practice. As a main contribution, we propose a Hausman-type test that determines the presence of correlated factor loadings in panels with interactive effects. Furthermore, we develop two nonparametric variance estimators that are robust to the presence of heteroscedasticity, autocorrelation as well as slope heterogeneity. Via Monte Carlo simulations, we demonstrate desirable size and power performance of the proposed test, even in small samples. Finally, we provide extensive empirical evidence in favour of uncorrelated factor loadings in panels with interactive effects.

Keywords: Panel Data Models, Cross-sectional Error Dependence, Unobserved Heterogeneous Factors, Factor Correlated Loadings

JEL Classification: C13, C33

Suggested Citation

Kapetanios, George and Serlenga, Laura and Shin, Yongcheol, Testing for Correlated Factor Loadings in Cross Sectionally Dependent Panels (June 2019). SERIES Working papers N. 02/2019, Available at SSRN: https://ssrn.com/abstract=3401745 or http://dx.doi.org/10.2139/ssrn.3401745

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

Laura Serlenga (Contact Author)

Università degli Studi di Bari “Aldo Moro” (UNIBA) - Dipartimento di Economia e Finanza ( email )

Piazza Umberto I
Bari, 70121
Italy

Yongcheol Shin

Independent

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