Heteroskedasticity and Non-normality Robust LM Tests for Spatial Dependence
AbstractThe standard LM tests for spatial dependence in linear and panel regressions are derived under the normality and homoskedasticity assumptions of the regression disturbances. Hence, they may not be robust against non-normality or heteroskedasticity of the disturbances. Following Born and Breitung (2011), we introduce general methods to modify the standard LM tests so that they become robust against heteroskedasticity and non-normality. The idea behind the robustification is to decompose the concentrated score function into a sum of uncorrelated terms so that the outer product of gradient (OPG) can be used to estimate its variance. We also provide methods for improving the finite sample performance of the proposed tests. These methods are then applied to several popular spatial models. Monte Carlo results show that they work well in finite sample. Key Words: Centering; Heteroskedasticity; Non-Normality; LM Tests; Panel Model; Spatial Dependence JEL No. C21, C23, C5
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 156.
Length: 30 pages
Date of creation: May 2013
Date of revision:
Contact details of provider:
Postal: 426 Eggers Hall, Syracuse, New York USA 13244-1020
Phone: (315) 443-3114
Fax: (315) 443-1081
Web page: http://www.maxwell.syr.edu/cpr.aspx
More information through EDIRC
Other versions of this item:
- 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.
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Yang, Zhenlin, 2010.
"A robust LM test for spatial error components,"
Regional Science and Urban Economics,
Elsevier, vol. 40(5), pages 299-310, September.
- 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.
- Nicolas Debarsy & Cem Ertur, 2009. "Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model," Post-Print halshs-00414133, HAL.
- Edward E. Glaeser & Bruce Sacerdote & Jose A. Scheinkman, 1995.
"Crime and Social Interactions,"
Harvard Institute of Economic Research Working Papers
1738, Harvard - Institute of Economic Research.
- Badi H. Baltagi & Zhenlin Yang, 2013.
"Standardized LM tests for spatial error dependence in linear or panel regressions,"
Royal Economic Society, vol. 16(1), pages 103-134, 02.
- Badi H. Baltagi & Zhenlin Yang, 2010. "Standardized LM Tests for Spatial Error Dependence in Linear or Panel Regressions," Working Papers 11-2010, Singapore Management University, School of Economics.
- 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.
- Russell Davidson & James G. MacKinnon, 1985.
"Heteroskedasticity-Robust Tests in Regression Directions,"
616, Queen's University, Department of Economics.
- DAVIDSON, Russel & MACKINNON, James G., . "Heteroskedastcity-robust tests in regressions directions," CORE Discussion Papers RP -678, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Benjamin Born & Jörg Breitung, 2011.
"Simple regression‐based tests for spatial dependence,"
Royal Economic Society, vol. 14(2), pages 330-342, 07.
- Benjamin Born & Jörg Breitung, 2009. "Simple Regression Based Tests for Spatial Dependence," Bonn Econ Discussion Papers bgse23_2009, University of Bonn, Germany.
- White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
- Badi H. Baltagi & Seuck Heun Song & Won Koh, 2002.
"Testing Panel Data Regression Models with Spatial Error Correlation,"
10th International Conference on Panel Data, Berlin, July 5-6, 2002
B6-4, International Conferences on Panel Data.
- Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
- 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.
- Lin, Xu & Lee, Lung-fei, 2010. "GMM estimation of spatial autoregressive models with unknown heteroskedasticity," Journal of Econometrics, Elsevier, vol. 157(1), pages 34-52, July.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kelly Bogart) or (Katrina Wingle).
If references are entirely missing, you can add them using this form.