Can Electoral Results Be Geographically Predicted? A Spatial Clusters and Outliers Analysis
The results of this study show that using spatial statistics in electoral geography can predict electoral results. The geographical concepts of spatial cluster and spatial outlier are applied, and a local spatial segregation measure used as the predictor variable. The statistical techniques employed...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2008 |
| País: | México |
| Institución: | EL COLEGIO DE MÉXICO |
| Repositorio: | Estudios Demográficos y Urbanos |
| Idioma: | español |
| OAI Identifier: | oai:oai.estudiosdemograficosyurbanos.colmex.mx:article/1322 |
| Acceso en línea: | https://estudiosdemograficosyurbanos.colmex.mx/index.php/edu/article/view/1322 |
| Access Level: | acceso abierto |
| Palabra clave: | electoral geography spatial analysis spatial segregation Mexico elecciones análisis espacial segregación espacial México |
| Sumario: | The results of this study show that using spatial statistics in electoral geography can predict electoral results. The geographical concepts of spatial cluster and spatial outlier are applied, and a local spatial segregation measure used as the predictor variable. The statistical techniques employed are Moran´s global and local spatial autocorrelation indexes, and linear regression. The analysis shows: 1) that Mexico City contains spatial clusters of electoral support and marginality, 2) spatial outliers of marginality, 3) political parties exclude each other geographically, and 4) electoral results to be significantly dependent on the levels of spatial segregation within the city. |
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