IDEAS home Printed from https://ideas.repec.org/a/eee/regeco/v33y2003i5p595-618.html
   My bibliography  Save this article

Properties of tests for spatial error components

Author

Listed:
  • Anselin, Luc
  • Moreno, Rosina

Abstract

In spatial econometrics, the typical alternative of spatial autocorrelation is expressed in the form of a spatial autorregressive process. While the bulk of the literature is devoted to specification tests and estimation methods for these models, alternatives have been suggested as well. In this paper, we consider alternatives that take the form of the spatial error components formulation proposed by Kelejian and Robinson. We consider a number of specification tests against this alternative, based on both a maximum likelihood framework as well as on a general method of moments estimation approach. We compare the performance of these tests in a series of Monte Carlo simulation experiments against a wide range of alternatives of spatial autocorrelation, under a number of different error distributions.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Anselin, Luc & Moreno, Rosina, 2003. "Properties of tests for spatial error components," Regional Science and Urban Economics, Elsevier, vol. 33(5), pages 595-618, September.
    • Handle: RePEc:eee:regeco:v:33:y:2003:i:5:p:595-618
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0166-0462(03)00008-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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 509-533, May.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    3. Luc Anselin & Raymond J. G. M. Florax, 1995. "Small Sample Properties of Tests for Spatial Dependence in Regression Models: Some Further Results," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 2, pages 21-74, Springer.
    4. Harry H. Kelejian & Dennis P. Robinson, 1993. "A Suggested Method Of Estimation For Spatial Interdependent Models With Autocorrelated Errors, And An Application To A County Expenditure Model," Papers in Regional Science, Wiley Blackwell, vol. 72(3), pages 297-312, July.
    5. Harry H. Kelejian & Dennis P. Robinson, 1997. "Infrastructure Productivity Estimation And Its Underlying Econometric Specifications: A Sensitivity Analysis," Papers in Regional Science, Wiley Blackwell, vol. 76(1), pages 115-131, January.
    6. 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.
    7. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
    8. Harry H. Kelejian & Dennis P. Robinson, 1995. "Spatial Correlation: A Suggested Alternative to the Autoregressive Model," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 3, pages 75-95, Springer.
    9. Kelejian, Harry H. & Robinson, Dennis P., 1992. "Spatial autocorrelation : A new computationally simple test with an application to per capita county police expenditures," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 317-331, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raymond J. G. M. Florax & Arno J. Van der Vlist, 2003. "Spatial Econometric Data Analysis: Moving Beyond Traditional Models," International Regional Science Review, , vol. 26(3), pages 223-243, July.
    2. LE GALLO, Julie, 2000. "Econométrie spatiale 1 -Autocorrélation spatiale," LATEC - Document de travail - Economie (1991-2003) 2000-05, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    3. Egger, Peter & Larch, Mario & Pfaffermayr, Michael & Walde, Janette, 2009. "Small sample properties of maximum likelihood versus generalized method of moments based tests for spatially autocorrelated errors," Regional Science and Urban Economics, Elsevier, vol. 39(6), pages 670-678, November.
    4. López, Fernando & Matilla-García, Mariano & Mur, Jesús & Marín, Manuel Ruiz, 2010. "A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 40(2-3), pages 106-115, May.
    5. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    6. Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
    7. Julie Le Gallo, 2002. "Économétrie spatiale : l'autocorrélation spatiale dans les modèles de régression linéaire," Economie & Prévision, La Documentation Française, vol. 155(4), pages 139-157.
    8. Julie Le Gallo, 2000. "Spatial econometrics (1, Spatial autocorrelation) [Econométrie spatiale (1, Autocorrélation spatiale)]," Working Papers hal-01527290, HAL.
    9. Fang, Ying & Park, Sung Y. & Zhang, Jinfeng, 2014. "A simple spatial dependence test robust to local and distributional misspecifications," Economics Letters, Elsevier, vol. 124(2), pages 203-206.
    10. Zhou, Bin (Brenda) & Kockelman, Kara M., 2009. "Predicting the distribution of households and employment: a seemingly unrelated regression model with two spatial processes," Journal of Transport Geography, Elsevier, vol. 17(5), pages 369-376.
    11. Saavedra, Luz A., 2003. "Tests for spatial lag dependence based on method of moments estimation," Regional Science and Urban Economics, Elsevier, vol. 33(1), pages 27-58, January.
    12. Wang, Li & Ready, Richard C., 2005. "Spatial Econometric Approaches to Estimating Hedonic Property Value Models," 2005 Annual meeting, July 24-27, Providence, RI 19174, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. repec:asg:wpaper:1013 is not listed on IDEAS
    14. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    15. Jin, Fei & Lee, Lung-fei, 2013. "Cox-type tests for competing spatial autoregressive models with spatial autoregressive disturbances," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 590-616.
    16. Quentin Frère & Matthieu Leprince & Sonia Paty, 2014. "The Impact of Intermunicipal Cooperation on Local Public Spending," Urban Studies, Urban Studies Journal Limited, vol. 51(8), pages 1741-1760, June.
    17. repec:asg:wpaper:1006 is not listed on IDEAS
    18. Chen, Yang & Regis, Paulo José, 2014. "Strategic interactions in corporate tax between Chinese local governments," RIEI Working Papers 2014-01, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration, revised 27 Oct 2015.
    19. Revelli, Federico, 2006. "Performance rating and yardstick competition in social service provision," Journal of Public Economics, Elsevier, vol. 90(3), pages 459-475, February.
    20. 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.
    21. 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 509-533, May.
    22. Piras, Gianfranco & Prucha, Ingmar R., 2014. "On the finite sample properties of pre-test estimators of spatial models," Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 103-115.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:regeco:v:33:y:2003:i:5:p:595-618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/regec .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.