Simple diagnostic tests for spatial dependence

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Abstract

In this paper we propose simple diagnostic tests, based on ordinary least-squares (OLS) residuals, for spatial error autocorrelation in the presence of a spatially lagged dependent variable and for spatial lag dependence in the presence of spatial error autocorrelation, applying the modified Lagrange multiplier (LM) test developed by Bera and Yoon (Econometric Theory, 1993, 9, 649–658). Our new tests may be viewed as computationally simple and robust alternatives to some existing procedures in spatial econometrics. We provide empirical illustrations to demonstrate the usefulness of the proposed tests. The finite sample size and power performance of the tests are also investigated through a Monte Carlo study. The results indicate that the adjusted LM tests have good finite sample properties. In addition, they prove to be more suitable for the identification of the source of dependence (lag or error) than their unadjusted counterparts.

References (28)

  • L. Anselin

    Spatial dependence and spatial heterogeneity: Model specification issues in the spatial expansion paradigm

  • L. Anselin

    SpaceStat: A program for the analysis of spatial data

  • L. Anselin

    SpaceStat version 1.50: Revision notes

  • L. Anselin et al.

    Small sample properties fo tests for spatial dependence in regression models: Some further results

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