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A wald Test for Spatial Nonstationarity

Author

Listed:
  • LAURIDSEN, J.

    () (Corresponding author: Associate Professor. The Econometric Group, Department of Economics, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark. Fax: 45 6595 7766)

  • KOSFELD, R.

    () (Professor, Department of Economics, University of Kassel, D-34109 Kassel, Germany.)

Abstract

A test strategy consisting of a two-step Lagrange multiplier test was recently suggested as a device to reveal spatial nonstationarity, spurious spatial regression and presence of a spatial cointegrating relationship between two variables. Due to the well known radicality of such pre-tests in finite samples, the present paper suggests a Wald post-test, based on maximum likelihood estimation. The finite-sample distribution of the test under nonstationarity is derived using Monte Carlo simulation and applied to an empirical example. Se ha propuesto recientemente una estrategia de contraste basada en el Multiplicador de Lagrange en dos etapas para analizar no estacionariedad espacial, regresión espacial espurea y la presencia de relaciones de cointegración en el caso bivariante. Como es conocido, estos métodos condicionados tienen problemas en muestras finitas por lo que en el trabajo se presenta un contraste de Wald, basado en la estimación de máxima verosimilitud. En el trabajo se obtiene la distribución en muestra finita del contraste bajo la hipótesis de no estacionariedad mediante simulaciones de Monte Carlo, y se aplica a un ejemplo concreto. La distribución obtenida para el contraste de Wald parece tener unas colas más densas que la distribución tradicional, chi-cuadrado con un grado de libertad.

Suggested Citation

  • Lauridsen, J. & Kosfeld, R., 2004. "A wald Test for Spatial Nonstationarity," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 22, pages 1-12, Diciembre.
  • Handle: RePEc:lrk:eeaart:22_3_5
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    References listed on IDEAS

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    1. John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Chapters,in: NBER Macroeconomics Annual 1991, Volume 6, pages 141-220 National Bureau of Economic Research, Inc.
    2. Jørgen Lauridsen, 2006. "Spatial autoregressively distributed lag models: equivalent forms, estimation, and an illustrative commuting model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 40(2), pages 297-311, June.
    3. Kosfeld, Reinhold & Lauridsen, Jorgen, 2004. "Dynamic Spatial Modelling of Regional Convergence Processes," Discussion Paper Series 26211, Hamburg Institute of International Economics.
    4. Sergio Rey & Brett Montouri, 1999. "US Regional Income Convergence: A Spatial Econometric Perspective," Regional Studies, Taylor & Francis Journals, vol. 33(2), pages 143-156.
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    7. Reinhold Kosfeld & Jorgen Lauridsen, 2004. "Dynamic spatial modelling of regional convergence processes," Empirical Economics, Springer, vol. 29(4), pages 705-722, December.
    8. Francis X. Diebold & Marc Nerlove, 1988. "Unit roots in economic time series: a selective survey," Finance and Economics Discussion Series 49, Board of Governors of the Federal Reserve System (US).
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    Citations

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    Cited by:

    1. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    2. Jørgen Lauridsen & Reinhold Kosfeld, 2007. "Spatial cointegration and heteroscedasticity," Journal of Geographical Systems, Springer, vol. 9(3), pages 253-265, September.
    3. Andrea Vaona, 2010. "Spatial autocorrelation and the sensitivity of RESET: a simulation study," Journal of Geographical Systems, Springer, vol. 12(1), pages 89-103, March.

    More about this item

    Keywords

    Spatial nonstationarity; spurious regression; Wald tests; Lagrange multiplier tests.;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

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