So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Biến công cụ không gian (Spatial IV / Spatial 2SLS)× | Phương pháp Biến Công cụ (IV) cho Suy luận Nhân quả× | |
|---|---|---|
| Lĩnh vực≠ | Suy luận nhân quả | Kinh tế học y tế |
| Họ≠ | Regression model | Process / pipeline |
| Năm ra đời≠ | 1988-1998 | 1990s (modern applications) |
| Người khởi xướng≠ | Kelejian & Prucha (generalized spatial 2SLS); Anselin (spatial econometrics framework) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| Loại≠ | Quasi-experimental causal inference with spatial dependence | Method |
| Công trình gốc≠ | Kelejian, H. H., & Prucha, I. R. (1998). A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances. Journal of Real Estate Finance and Economics, 17(1), 99-121. DOI ↗ | Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press. link ↗ |
| Tên gọi khác | Spatial IV, Spatial 2SLS, Spatial Two-Stage Least Squares, S-IV | IV, two-stage least squares, TSLS, causal estimation |
| Liên quan≠ | 6 | 3 |
| Tóm tắt≠ | Spatial Instrumental Variables (Spatial IV) is a causal inference method for settings where units — regions, firms, neighborhoods — are spatially interdependent, creating endogeneity that standard IV approaches ignore. It constructs instruments from the spatially lagged values of exogenous characteristics of neighboring units, then applies two-stage least squares to recover unbiased causal estimates in the presence of both endogenous regressors and spatial autocorrelation. | Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes. |
| ScholarGateBộ dữ liệu ↗ |
|
|