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| Spatial Conflict Analysis× | 공간 회귀분석 (공간 시차 및 공간 오차 모형)× | |
|---|---|---|
| 분야≠ | International Relations | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2002 | 1988 |
| 창시자≠ | Spatial-analysis-of-conflict literature (e.g., Michael Ward & Kristian Skrede Gleditsch) | Luc Anselin |
| 유형≠ | Spatial regression / spatial-statistical modeling of conflict | Spatial regression (cross-sectional) |
| 원전≠ | Ward, M. D., & Gleditsch, K. S. (2002). Location, location, location: An MCMC approach to modeling the spatial context of war and peace. Political Analysis, 10(3), 244–260. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗ |
| 별칭≠ | Spatial Analysis of War and Peace, Geographic Conflict Modeling, Spatial Econometrics of Conflict, Georeferenced Conflict Analysis | spatial econometrics, spatial lag model, spatial error model, SAR / SEM |
| 관련≠ | 3 | 5 |
| 요약≠ | Spatial conflict analysis models armed conflict while taking geography seriously: conflict is not randomly scattered but clusters in space, and a place's risk depends on its neighbors. Building on georeferenced data and spatial-statistical methods — as in Ward and Gleditsch's (2002) MCMC approach to the spatial context of war and peace — it uses spatial weights, tests for spatial autocorrelation, and fits spatial regression models so that conflict, peace, and their predictors are analyzed as interdependent across locations rather than as isolated observations. | Spatial regression is a family of regression models that build geographic neighbourhood relationships directly into the model, introduced by Luc Anselin in his 1988 treatment of spatial econometrics. It splits into a spatial lag model, where spatial dependence sits in the dependent variable, and a spatial error model, where the dependence sits in the error term. |
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