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Standardized LM Tests for Spatial Error Dependence in Linear or Panel Regressions

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Abstract

The robustness of the LM tests for spatial error dependence of Burridge (1980) and Born and Breitung (2011) for the linear regression model, and Anselin (1988) and Debarsy and Ertur (2010) for the panel regression model with random or fixed effects are examined. While all tests are asymptotically robust against distributional misspecification, their finite sample behavior may 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. Key Words: Bootstrap; Distributional misspecification; Group interaction; LM test; Moran’s I Test; Robustness; Spatial layout; Spatial panel models JEL No. C21, C23, C5

Suggested Citation

  • Badi H. Baltagi & Zhenlin Yang, 2012. "Standardized LM Tests for Spatial Error Dependence in Linear or Panel Regressions," Center for Policy Research Working Papers 142, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:142
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    1. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
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    5. Benjamin Born & Jörg Breitung, 2011. "Simple regression‐based tests for spatial dependence," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 330-342, July.
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    More about this item

    Keywords

    bootstrap; distributional misspecification; group interaction; lm test; moran’s i test; robustness; spatial layout; spatial panel models jel no. c21; c23; c5;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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