방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 전역 공간 패널 모형× | 공간 시차 모형 (SAR / 공간 자기회귀)× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2003-2010 | 1988 |
| 창시자≠ | Elhorst, J. P.; Lee, L. F. & Yu, J. | Anselin (textbook formalisation); LeSage & Pace |
| 유형≠ | Spatial panel regression | Spatial autoregressive regression |
| 원전≠ | Elhorst, J. P. (2014). Spatial Econometrics: From Cross-Sectional Data to Spatial Panels. Springer. ISBN: 978-3642403408 | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| 별칭 | spatial panel model with global weights, global spatial panel regression, spatial panel data model, GSPM | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| 관련≠ | 4 | 5 |
| 요약≠ | The Global Spatial Panel Model extends panel data regression by incorporating a global spatial weights matrix that links every location to every other location simultaneously. It jointly accounts for cross-sectional spatial dependence, time-series dynamics, and individual fixed or random effects, making it the standard workhorse for panel data when spatial spillovers operate across the full study region. | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
| ScholarGate데이터셋 ↗ |
|
|