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On the Asymptotic Distribution of the Moran I Test Statistic with Applications

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Author Info

  • Harry H. Kelejian

    ()
    (Department of Economics, University of Maryland)

  • Ingmar R. Prucha

    ()
    (Department of Economics, University of Maryland)

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    Abstract

    By far, the most popular test for spatial correlation is the one based on Moran's (1950) I test statistic. Despite this, the available results in the literature concerning the large sample distribution of this statistic are limited and have been derived under assumptions that do not cover many applications of interest. In this paper we first give a general result concerning the large sample distribution of Moran I type test statistic. We then apply this result to derive the large sample distribution of the Moran I test statistic for a variety of important models for which general spatial correlation testing procedures are not available. In order to establish these results we also give a new central limit theorem for linear-quadratic forms.

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    File URL: http://www.econweb.umd.edu/papers/prucha2.pdf
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    Bibliographic Info

    Paper provided by University of Maryland, Department of Economics in its series Electronic Working Papers with number 99-002.

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    Date of creation: Feb 1999
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    Handle: RePEc:umd:umdeco:99-002

    Contact details of provider:
    Postal: Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
    Web page: http://www.econ.umd.edu/

    Order Information:
    Postal: Ms. Elizabeth Martinez, Department of Economics, University of Maryland, Tydings Hall, College Park, MD 20742
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    Related research

    Keywords: Moran I Test; Spatial Autocorrelation; Asymptotic Distribution; Central Limit Theorem;

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    References

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    1. J. Bradford De Long & Lawrence H. Summers, . "Equipment Investment and Economic Growth," J. Bradford De Long's Working Papers _122, University of California at Berkeley, Economics Department.
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    7. 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.
    8. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
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    12. 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.
    13. Dubin, Robin A, 1988. "Estimation of Regression Coefficients in the Presence of Spatially Autocorrelated Error Terms," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 466-74, August.
    14. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-40, June.
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    Cited by:
    1. 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.

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