Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Autocorrelación Espacial en Datos de Panel× | Autocorrelación espacial× | |
|---|---|---|
| Campo | Análisis espacial | Análisis espacial |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1988–2003 | 1950 |
| Autor original≠ | Anselin, L.; Elhorst, J. P. | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Tipo≠ | Diagnostic test / exploratory statistic | Spatial statistic / exploratory spatial data analysis |
| Fuente seminal≠ | Anselin, L. (2013). Spatial Econometrics: Methods and Models. Springer Netherlands. (Originally published 1988.) ISBN: 978-9401577991 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Alias | spatial autocorrelation in panel data, panel spatial dependence, spatio-temporal autocorrelation, cross-sectional dependence in panels | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Relacionados | 5 | 5 |
| Resumen≠ | Panel Spatial Autocorrelation measures whether observations that are geographically close also tend to have similar values across repeated time periods. It extends classic cross-sectional spatial autocorrelation statistics such as Moran's I to panel data, enabling researchers to detect spatial dependence consistently over time and to diagnose whether a panel regression model requires a spatial component. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGateConjunto de datos ↗ |
|
|