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A non-parametric spatial independence test using symbolic entropy

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  • López, Fernando
  • Matilla-García, Mariano
  • Mur, Jesús
  • Marín, Manuel Ruiz

Abstract

In the present paper, we construct a new, simple, consistent and powerful test for spatial independence, called the SG test, by using the new concept of symbolic entropy as a measure of spatial dependence. The standard asymptotic distribution of the test is an affine transformation of the symbolic entropy under the null hypothesis. The test statistic, with the proposed symbolization procedure, and its standard limit distribution have appealing theoretical properties that guarantee the general applicability of the test. An important aspect is that the test does not require specification of the W matrix and is free of a priori assumptions. We include a Monte Carlo study of our test, in comparison with the well-known Moran's I, the SBDS (de Graaff et al., 2001) and [tau] test (Brett and Pinkse, 1997) that are two non-parametric tests, to better appreciate the properties and the behaviour of the new test. Apart from being competitive compared to other tests, results underline the outstanding power of the new test for non-linear dependent spatial processes.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:regeco:v:40:y:2010:i:2-3:p:106-115
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    Cited by:

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    12. Elsinger, Helmut, 2013. "Comment on: A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 838-840.
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    15. Luc Anselin & Xun Li, 2019. "Operational local join count statistics for cluster detection," Journal of Geographical Systems, Springer, vol. 21(2), pages 189-210, June.
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    17. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    18. Herrera Gómez, Marcos & Mur Lacambra, Jesús & Ruiz Marín, Manuel, 2012. "Selecting the Most Adequate Spatial Weighting Matrix:A Study on Criteria," MPRA Paper 73700, University Library of Munich, Germany.
    19. Herrera Gómez, Marcos & Ruiz Marín, Manuel & Mur Lacambra, Jesús & Paelinck, Jean, 2010. "A Non-Parametric Approach to Spatial Causality," MPRA Paper 36768, University Library of Munich, Germany.
    20. López-Hernández , Fernando A. & Artal-Tur, Andrés & Maté-Sánchez-Val, M. Luz, 2011. "Identifying nonlinear spatial dependence patterns by using non-parametric tests: Evidence for the European Union," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 19-36.
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