2008
DOI: 10.1111/j.1368-423x.2007.00227.x
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A bias-adjusted LM test of error cross-section independence

Abstract: This paper proposes a bias-adjusted version of Breusch and Pagan (1980) Lagrange multiplier (LM) test statistic of error cross-section independence, in the case of panel models with strictly exogenous regressors and normal errors. The exact mean and variance of the test indicator of the LM test statistic are provided for the purpose of the bias-adjustments. It is shown that the centring of the LM statistic is correct for fixed T and N. Importantly, the proposed bias-adjusted LM test is consistent even when the… Show more

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Cited by 1,552 publications
(731 citation statements)
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“…It is important to note that the LM test is valid only for relatively small N and sufficiently large T -as we have in this study. 7 However, the Cross sectional Dependence (CD) test is subject to decreasing power in situations that the population average pair-wise correlations are zero, although the underlying individual population pair-wise correlations are non-zero [23]. Furthermore, in stationary dynamic panel data models the CD test fails to reject the null hypothesis when the factor loadings have zero mean in the cross-sectional dimension.…”
Section: Testing Cross-section Dependencementioning
confidence: 99%
See 1 more Smart Citation
“…It is important to note that the LM test is valid only for relatively small N and sufficiently large T -as we have in this study. 7 However, the Cross sectional Dependence (CD) test is subject to decreasing power in situations that the population average pair-wise correlations are zero, although the underlying individual population pair-wise correlations are non-zero [23]. Furthermore, in stationary dynamic panel data models the CD test fails to reject the null hypothesis when the factor loadings have zero mean in the cross-sectional dimension.…”
Section: Testing Cross-section Dependencementioning
confidence: 99%
“…Furthermore, in stationary dynamic panel data models the CD test fails to reject the null hypothesis when the factor loadings have zero mean in the cross-sectional dimension. In order to deal with these problems, Pesaran et al [23] propose a bias-adjusted test, which is a modified version of the LM test, by using the exact mean and variance of the LM statistic. The bias-adjusted LM test is: …”
Section: Testing Cross-section Dependencementioning
confidence: 99%
“…Regarding the countryspecific heterogeneity assumption, the slope homogeneity tests ( Δ andΔ − adj ) of Pesaran and Yamagata (2008) are used (Appendix 3 provides more information about these tests). The Kónya's (2006) approach considers both issues, based on SUR systems estimation and identification of Wald tests with country-specific bootstrap critical values.…”
Section: Empirical Framework Data and Methodologymentioning
confidence: 99%
“…A set of three tests is constructed in order to check the cross-sectional dependence assumption: the Breusch and Pagan (1980) cross-sectional dependence (CD BP ) test, the Pesaran (2004) cross-sectional dependence (CD P ) test, and the Pesaran et al (2008) bias-adjusted LM test (LM adj ). Regarding the countryspecific heterogeneity assumption, the slope homogeneity tests ( Δ andΔ − adj ) of Pesaran and Yamagata (2008) are used (Appendix 3 provides more information about these tests).…”
Section: Empirical Framework Data and Methodologymentioning
confidence: 99%
“…Pesaran et al (2008) also suggest an improved interpretation of this test in order to account for the cases where both cross sectional and time dimension is fixed. This test is referred ad (LM adj ) and estimated as below (Pesaran et al, 2008):…”
Section: Foreign Direct Investment International Trade and Financialmentioning
confidence: 99%