Testing for cross-sectional dependence in a panel factor model using the wild bootstrap <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$F$$</EquationSource> </InlineEquation> test

This paper considers testing for cross-sectional dependence in a panel factor model. Based on the model considered by Bai (Econometrica 71: 135–171, <CitationRef CitationID="CR3">2003</CitationRef>), we investigate the use of a simple <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$F$$</EquationSource> </InlineEquation> test for testing for cross-sectional dependence when the factor may be known or unknown. The limiting distributions of these <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$F$$</EquationSource> </InlineEquation> test statistics are derived when the cross-sectional dimension and the time-series dimension are both large. The main contribution of this paper is to propose a wild bootstrap <InlineEquation ID="IEq5"> <EquationSource Format="TEX">$$F$$</EquationSource> </InlineEquation> test which is shown to be consistent and which performs well in Monte Carlo simulations especially when the factor is unknown. Copyright Springer-Verlag Berlin Heidelberg 2013