השוואת שיטות

	Spatial Instrumental Variables	שיטת המשתנים המתערבים (IV) להסקה סיבתית
תחום	הסקה סיבתית	כלכלת בריאות
משפחה	Regression model	Process / pipeline
שנת המקור	1988-1998	1990s (modern applications)
הוגה השיטה	Kelejian & Prucha (generalized spatial 2SLS); Anselin (spatial econometrics framework)	Angrist & Pischke (applied econometrics); rooted in econometric theory
סוג	Quasi-experimental causal inference with spatial dependence	Method
מקור מכונן	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.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
כינויים	Spatial IV, Spatial 2SLS, Spatial Two-Stage Least Squares, S-IV	IV, two-stage least squares, TSLS, causal estimation
קשורות	6	3
תקציר	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.