TY - JOUR
T1 - Testing AR(1) against MA(1) disturbances in an error component model
AU - Baltagi, Badi H.
AU - Li, Qi
N1 - Funding Information:
The authors would like to thank Richard Blundell and two anonymous referees for their helpful comments and suggestions. Baltagi was funded by the Advanced Research Progam, Texas Higher Education Board, while Li was funded by the Social Sciences of Humanities Research Council of Canada.
PY - 1995/7
Y1 - 1995/7
N2 - This paper derives three LM statistics for an error component model with first-order serially correlated errors. The first LM statistic jointly tests for zero first-order serial correlation and random individual effects, the second LM statistic tests for zero first-order serial correlation assuming fixed individual effects, and the third LM statistic tests for zero first-order serial correlation assuming random individual effects. In all three cases, the corresponding LM statistic is the same whether the alternative is AR(1) or MA(1). This paper also derives two extensions of the Burke, Godfrey, and Termayne (1990) test from the time-series to the panel data literature. The first tests the null of AR(1) disturbances against MA(1) disturbances, and the second tests the null of MA(1) disturbances against AR(1) disturbances in an error component model. These tests are computationally simple requiring only OLS or within residuals. The small sample performance of these tests are studied using Monte Carlo experiments.
AB - This paper derives three LM statistics for an error component model with first-order serially correlated errors. The first LM statistic jointly tests for zero first-order serial correlation and random individual effects, the second LM statistic tests for zero first-order serial correlation assuming fixed individual effects, and the third LM statistic tests for zero first-order serial correlation assuming random individual effects. In all three cases, the corresponding LM statistic is the same whether the alternative is AR(1) or MA(1). This paper also derives two extensions of the Burke, Godfrey, and Termayne (1990) test from the time-series to the panel data literature. The first tests the null of AR(1) disturbances against MA(1) disturbances, and the second tests the null of MA(1) disturbances against AR(1) disturbances in an error component model. These tests are computationally simple requiring only OLS or within residuals. The small sample performance of these tests are studied using Monte Carlo experiments.
KW - Error components
KW - Lagrange multiplier
KW - Random and fixed effects
KW - Serial correlation
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U2 - 10.1016/0304-4076(94)01646-H
DO - 10.1016/0304-4076(94)01646-H
M3 - Article
AN - SCOPUS:33846668200
SN - 0304-4076
VL - 68
SP - 133
EP - 151
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 1
ER -