Power Properties of Invariant Tests for Spatial Autocorrelation in Linear Regression
AbstractThis paper derives some exact power properties of tests for spatial autocorrelation in the context of a linear regression model. In particular, we characterize the circumstances in which the power vanishes as the autocorrelation increases, thus extending the work of Krämer (2005, Journal of Statistical Planning and Inference 128, 489-496). More generally, the analysis in the paper sheds new light on how the power of tests for spatial autocorrelation is affected by the matrix of regressors and by the spatial structure. We mainly focus on the problem of residual spatial autocorrelation, in which case it is appropriate to restrict attention to the class of invariant tests, but we also consider the case when the autocorrelation is due to the presence of a spatially lagged dependent variable among the regressors. A numerical study aimed at assessing the practical relevance of the theoretical results is included.
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 University Library of Munich, Germany in its series MPRA Paper with number 7255.
Date of creation: 29 Jan 2008
Date of revision:
Cliff-Ord test; invariant tests; linear regression model; point optimal tests; power; similar tests; spatial autocorrelation;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-02-23 (All new papers)
- NEP-ECM-2008-02-23 (Econometrics)
- NEP-GEO-2008-02-23 (Economic Geography)
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.:
- Kadiyala, Koteswara Rao, 1970. "Testing for the Independence of Regression Disturbances," Econometrica, Econometric Society, vol. 38(1), pages 97-117, January.
- Kramer, W., 1985. "The power of the Durbin-Watson test for regressions without an intercept," Journal of Econometrics, Elsevier, vol. 28(3), pages 363-370, June.
- Tillman, John A, 1975. "The Power of the Durbin-Watson Test," Econometrica, Econometric Society, vol. 43(5-6), pages 959-74, Sept.-Nov.
- Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(02), pages 252-277, April.
- Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-65, July.
- Hillier, Grant H., 1987. "Classes of Similar Regions and Their Power Properties for Some Econometric Testing Problems," Econometric Theory, Cambridge University Press, vol. 3(01), pages 1-44, February.
- Baltagi, Badi H., 2006.
"Random Effects And Spatial Autocorrelation With Equal Weights,"
Cambridge University Press, vol. 22(05), pages 973-984, October.
- Badi H. Baltagi, 2006. "Random effects and Spatial Autocorrelations with Equal Weights," Center for Policy Research Working Papers 89, Center for Policy Research, Maxwell School, Syracuse University.
- Durbin, J, 1970. "An Alternative to the Bounds Test for Testing for Serial Correlation in Least-Squares Regression," Econometrica, Econometric Society, vol. 38(3), pages 422-29, May.
- Paulauskas, Vygantas, 2007. "On unit roots for spatial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 209-226, January.
- D. P. Kennedy, 1994. "The Term Structure Of Interest Rates As A Gaussian Random Field," Mathematical Finance, Wiley Blackwell, vol. 4(3), pages 247-258.
- Rahman, Shahidur & King, Maxwell L., 1997. "Marginal-likelihood score-based tests of regression disturbances in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 82(1), pages 81-106.
- Prof. Dr. Walter Krämer & Christian Kleiber, .
"Finite-Sample Power of the Durbin-Watson Test Against Fractionally Integrated Disturbances,"
10, Business and Social Statistics Department, Technische Universität Dortmund.
- Christian Kleiber & Walter Kr�mer, 2005. "Finite-sample power of the Durbin--Watson test against fractionally integrated disturbances," Econometrics Journal, Royal Economic Society, vol. 8(3), pages 406-417, December.
- Kariya, Takeaki, 1988. "The Class of Models for which the Durbin-Watson Test is Locally Optimal," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(1), pages 167-75, February.
- A. F. Militino & M. D. Ugarte & L. García-Reinaldos, 2004. "Alternative Models for Describing Spatial Dependence among Dwelling Selling Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 29(2), pages 193-209, 09.
- Pinkse, Joris & Slade, Margaret E., 1998. "Contracting in space: An application of spatial statistics to discrete-choice models," Journal of Econometrics, Elsevier, vol. 85(1), pages 125-154, July.
- Bartels, Robert, 1992. "On the power function of the Durbin-Watson test," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 101-112.
- Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
- Oksanen, E.H., 1993. "Efficiency as Correlation," Econometric Theory, Cambridge University Press, vol. 9(01), pages 146-146, January.
- Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
- Goldstein, Robert S, 2000. "The Term Structure of Interest Rates as a Random Field," Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 365-84.
- 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.
- Martellosio, Federico, 2008. "Testing for spatial autocorrelation: the regressors that make the power disappear," MPRA Paper 10542, University Library of Munich, Germany.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ekkehart Schlicht).
If references are entirely missing, you can add them using this form.