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Testing the assumption of independence between variables is a crucial aspect of spatial data analysis. However, the literature is limited and somewhat confusing. To our knowledge, we can mention only the bivariate generalization of Moran’s statistic. This test suffers from several...
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Testing for the assumption of independence between spatial variables is an important first step in spatial conometrics. Usually the researchers use the bivariate generalization of the Moran’s statistic, specifying a spatial matrix a priori. This test is applicable only to detect linear...
Persistent link: https://www.econbiz.de/10011260236
The paper shows a new non-parametric test, based on symbolic entropy, which permits detect spatial causality in cross-section data. The test is robust to the functional form of the relation and has a good behaviour in samples of medium to large size. We illustrate the use of test with the case...
Persistent link: https://www.econbiz.de/10011108455
In spatial econometrics, it is customary to specify a weighting matrix, the so-called W matrix. The decision is important because the choice of W matrix determines the rest of the analysis. However, the procedure is not well defined and, usually, reflects the priors of the user. In the paper, we...
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In spatial econometrics, it is customary to specify a weighting matrix, the so-called W matrix, just choosing one matrix from the different types of matrices a user is considering (Anselin, 2002). In general, this selection is made a priori, depending on the user's judgment. This decision is...
Persistent link: https://www.econbiz.de/10011538215
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