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Simple regression‐based tests for spatial dependence

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Author Info

  • Benjamin Born
  • Jörg Breitung

Abstract

We propose two simple diagnostic tests for spatial error autocorrelation and spatial lag dependence. The idea is to reformulate the testing problem such that the test statistics are asymptotically equivalent to the familiar LM test statistics. Speci cally, our version of the test is based on a simple auxiliary regression and an ordinary regression t-statistic can be used to test for spatial autocorrelation and lag dependence. We also propose a variant of the test that is robust to heteroskedasticity. This approach gives practitioners an easy to implement and robust alternative to existing tests. Monte Carlo studies show that our variants of the spatial LM tests possess comparable size and power properties even in small samples.

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Bibliographic Info

Article provided by Royal Economic Society in its journal Econometrics Journal.

Volume (Year): 14 (2011)
Issue (Month): 2 (07)
Pages: 330-342

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Handle: RePEc:ect:emjrnl:v:14:y:2011:i:2:p:330-342

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References

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  1. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
  2. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
  3. Russell Davidson & James G. MacKinnon, 1999. "Artificial Regressions," Working Papers 978, Queen's University, Department of Economics.
  4. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
  5. Russell Davidson & James G. MacKinnon, 1981. "Model Specification Tests Based on Artificial Linear Regressions," Working Papers 426, Queen's University, Department of Economics.
  6. Anselin, Luc, 2007. "Spatial econometrics in RSUE: Retrospect and prospect," Regional Science and Urban Economics, Elsevier, vol. 37(4), pages 450-456, July.
  7. Badi Baltagi & Dong Li, 2001. "Double Length Artificial Regressions For Testing Spatial Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 20(1), pages 31-40.
  8. Kelejian, Harry H. & Robinson, Dennis P., 1998. "A suggested test for spatial autocorrelation and/or heteroskedasticity and corresponding Monte Carlo results," Regional Science and Urban Economics, Elsevier, vol. 28(4), pages 389-417, July.
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Citations

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Cited by:
  1. Zhenlin Yang, 2013. "LM Tests of Spatial Dependence Based on Bootstrap Critical Values," Working Papers 03-2013, Singapore Management University, School of Economics.
  2. Badi H. Baltagi & Zhenlin Yang, 2013. "Standardized LM tests for spatial error dependence in linear or panel regressions," Econometrics Journal, Royal Economic Society, vol. 16(1), pages 103-134, 02.
  3. Bhattacharjee, Arnab & de Castro, Eduardo Anselmo & Marques, João Lourenço, 2011. "Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal," SIRE Discussion Papers 2011-45, Scottish Institute for Research in Economics (SIRE).
  4. Baltagi, Badi H. & Yang, Zhenlin, 2013. "Heteroskedasticity and non-normality robust LM tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 725-739.
  5. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2011. "Estimation of the Spatial Weights Matrix under Structural Constraints," SIRE Discussion Papers 2011-48, Scottish Institute for Research in Economics (SIRE).
  6. Bhattacharjee, Arnab & Jensen-Butler, Chris, 2013. "Estimation of the spatial weights matrix under structural constraints," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 617-634.

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