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A Non-Parametric Approach to Spatial Causality

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  • Herrera Gómez, Marcos
  • Ruiz Marín, Manuel
  • Mur Lacambra, Jesús
  • Paelinck, Jean

Abstract

The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. The good performance of the new test in detecting spatial causality and causal weighting matrix is notable and gives rise to an expectation that it may form a adequate tool for constructive specification searches.

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File URL: http://mpra.ub.uni-muenchen.de/36768/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 36768.

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Date of creation: 2010
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Handle: RePEc:pra:mprapa:36768

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Related research

Keywords: Causality; Spatial Dependence; Spatial Weight Matrices;

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  1. Harry Joe, 1989. "Estimation of entropy and other functionals of a multivariate density," Annals of the Institute of Statistical Mathematics, Springer, Springer, vol. 41(4), pages 683-697, December.
  2. 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, Elsevier, vol. 40(2-3), pages 106-115, May.
  3. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 30(9-10), pages 1647-1669.
  4. G�ran Therborn & K.C. Ho, 2009. "Introduction," City, Taylor & Francis Journals, Taylor & Francis Journals, vol. 13(1), pages 53-62, March.
  5. Yongmiao Hong & Halbert White, 2005. "Asymptotic Distribution Theory for Nonparametric Entropy Measures of Serial Dependence," Econometrica, Econometric Society, Econometric Society, vol. 73(3), pages 837-901, 05.
  6. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, Elsevier, vol. 144(1), pages 139-155, May.
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