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The Influence of Spatially Correlated Heteroskedasticity on Tests for Spatial Correlation

In: Advances in Spatial Econometrics

Author

Listed:
  • Harry H. Kelejian

    (University of Maryland)

  • Dennis P. Robinson

    (University of Arkansas at Little Rock)

Abstract

In cross sectional regression models the possibility of spill-overs between neighboring units is increasingly being recognized in both the theoretical and applied literature.1 Within a regression framework, typically recognized forms of such spill-overs relate to the model’s dependent and independent variables, as well as to the error terms. General issues relating to spill-overs suggest that the model's error terms may be spatially correlated. Because the statistical properties of the regression parameter estimators depend upon whether or not the error terms are indeed spatially correlated, tests for such correlation are frequently considered.2

Suggested Citation

  • Harry H. Kelejian & Dennis P. Robinson, 2004. "The Influence of Spatially Correlated Heteroskedasticity on Tests for Spatial Correlation," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 4, pages 79-97, Springer.
    • Handle: RePEc:spr:adspcp:978-3-662-05617-2_4
    DOI: 10.1007/978-3-662-05617-2_4
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    Citations

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    Cited by:

    1. Benjamin Born & Jörg Breitung, 2011. "Simple regression‐based tests for spatial dependence," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 330-342, July.
    2. Robert Sörensson, 2012. "Population and employment location in Swedish municipalities 1994–2004," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 743-762, June.
    3. Shanaka Herath & Johanna Choumert & Gunther Maier, 2015. "The value of the greenbelt in Vienna: a spatial hedonic analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 349-374, March.
    4. Peter Robinson, 2007. "Correlation testing in time series, spatial and cross-sectional data," CeMMAP working papers CWP01/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Julie Le Gallo & Fernando A. López & Coro Chasco, 2020. "Testing for spatial group-wise heteroskedasticity in spatial autocorrelation regression models: Lagrange multiplier scan tests," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 287-312, April.
    6. Robinson, P.M., 2008. "Correlation testing in time series, spatial and cross-sectional data," Journal of Econometrics, Elsevier, vol. 147(1), pages 5-16, November.

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