Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Regressão Espacial (Modelos de Lag Espacial e Erro Espacial)× | Regressões Aparentemente Não Relacionadas (SUR)× | |
|---|---|---|
| Área | Econometria | Econometria |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1988 | 1962 |
| Autor original≠ | Luc Anselin | Arnold Zellner |
| Tipo≠ | Spatial regression (cross-sectional) | System regression (multi-equation) |
| Fonte seminal≠ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic Publishers. DOI ↗ | Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368. DOI ↗ |
| Outros nomes≠ | spatial econometrics, spatial lag model, spatial error model, SAR / SEM | SUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR) |
| Relacionados | 5 | 5 |
| Resumo≠ | 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. | Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS. |
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