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| Panel Local Indicators of Spatial Association (패널 LISA)× | 패널 공간 자기상관× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1995 (LISA); panel extension 2000s–2010s | 1988–2003 |
| 창시자≠ | Anselin (1995), panel extension developed through spatial econometrics literature | Anselin, L.; Elhorst, J. P. |
| 유형≠ | Local spatial autocorrelation statistic | Diagnostic test / exploratory statistic |
| 원전≠ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Anselin, L. (2013). Spatial Econometrics: Methods and Models. Springer Netherlands. (Originally published 1988.) ISBN: 978-9401577991 |
| 별칭 | Panel LISA, spatiotemporal LISA, panel local spatial autocorrelation, LISA panel extension | spatial autocorrelation in panel data, panel spatial dependence, spatio-temporal autocorrelation, cross-sectional dependence in panels |
| 관련≠ | 4 | 5 |
| 요약≠ | Panel Local Indicators of Spatial Association extends Anselin's LISA statistics — most commonly Local Moran's I — to panel datasets, identifying spatial clusters and outliers at each location across multiple time periods. By applying local autocorrelation measures repeatedly over time, researchers can detect whether spatial concentration patterns emerge, persist, or dissolve, giving a richer spatiotemporal picture than a single cross-section allows. | 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. |
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