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Large-Sample Inference on SpatialDependence

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  • Peter M Robinson

Abstract

We consider cross-sectional data that exhibit no spatial correla-tion, but are feared to be spatially dependent. We demonstrate that a spatialversion of the stochastic volatility model of financial econometrics, entailing aform of spatial autoregression, can explain such behaviour. The parameters areestimated by pseudo Gaussian maximum likelihood based on log-transformedsquares, and consistency and asymptotic normality are established. Asymptotically valid tests for spatial independence are developed.

Suggested Citation

  • Peter M Robinson, 2009. "Large-Sample Inference on SpatialDependence," STICERD - Econometrics Paper Series 533, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    • Handle: RePEc:cep:stiecm:533
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    File URL: https://sticerd.lse.ac.uk/dps/em/em533.pdf
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    References listed on IDEAS

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    1. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    2. Peter Robinson, 2007. "Correlation testing in time series, spatial and cross-sectional data," CeMMAP working papers CWP01/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Craig Brett & Joris Pinkse, 1997. "Those Taxes are all over the Map! A Test for Spatial Independence of Municipal Tax Rates in British Columbia," International Regional Science Review, , vol. 20(1-2), pages 131-151, April.
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    Cited by:

    1. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar & Wolfgang Schmid & Anil K. Bera, 2023. "Spatial and Spatiotemporal Volatility Models: A Review," Papers 2308.13061, arXiv.org.
    2. Takaki Sato & Yasumasa Matsuda, 2016. "Spatial Autoregressive Conditional Heteroscedasticity Model and Its Application," TERG Discussion Papers 348, Graduate School of Economics and Management, Tohoku University.
    3. Joris Pinkse & Margaret E. Slade, 2010. "The Future Of Spatial Econometrics," Journal of Regional Science, Wiley Blackwell, vol. 50(1), pages 103-117, February.
    4. Osman Dou{g}an & Raffaele Mattera & Philipp Otto & Suleyman Tac{s}p{i}nar, 2024. "A Dynamic Spatiotemporal and Network ARCH Model with Common Factors," Papers 2410.16526, arXiv.org.
    5. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar, 2022. "Dynamic Spatiotemporal ARCH Models," Papers 2202.13856, arXiv.org.
    6. Philipp Otto & Osman Dou{g}an & Suleyman Tac{s}p{i}nar, 2023. "Dynamic Spatiotemporal ARCH Models: Small and Large Sample Results," Papers 2312.05898, arXiv.org.
    7. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    8. Philipp Otto, 2022. "A Multivariate Spatial and Spatiotemporal ARCH Model," Papers 2204.12472, arXiv.org.
    9. Fernando López & Mariano Matilla-García & Jesús Mur & Manuel Ruiz Marín, 2021. "Statistical Tests of Symbolic Dynamics," Mathematics, MDPI, vol. 9(8), pages 1-21, April.

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