Standardized LM Tests for Spatial Error Dependence in Linear or Panel Regressions
The robustness of the LM tests for spatial error dependence of Burridge (1980) for the linear regression model and Anselin (1988) for the panel regression model are examined. While both tests are asymptotically robust against distributional misspecification, their finite sample behavior can be sensitive to the spatial layout. To overcome this shortcoming, standardized LM tests are suggested. Monte Carlo results show that the new tests possess good finite sample properties. An important observation made throughout this study is that the LM tests for spatial dependence need to be both mean and variance-adjusted for good finite sample performance to be achieved. The former is, however, often neglected in the literature.
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