Double Length Artificial Regressions For Testing Spatial Dependence
AbstractThis paper derives two simple artificial Double Length Regressions (DLR) to test for spatial dependence. The first DLR tests for spatial lag dependence while the second DLR tests for spatial error dependence. Both artificial regressions utilize only least squares residuals of the restricted model and are therefore easy to compute. These tests are illustrated using two simple examples. In addition, Monte Carlo experiments are performed to study the small sample performance of these tests. As expected, these DLR tests have similar performance to their corresponding LM counterparts.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 20 (2001)
Issue (Month): 1 ()
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- JEL - Labor and Demographic Economics - - - - -
- Cla - Mathematical and Quantitative Methods - - - - -
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
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