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Linganisha mbinu

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Vigezo vya Ala za Ndege za Angani (Spatial IV / Spatial 2SLS)×Muundo wa Usambazaji wa Regression wa Kijiografia (Spatial RDD)×
NyanjaUhitimisho wa KisababishiUhitimisho wa Kisababishi
FamiliaRegression modelRegression model
Mwaka wa asili1988-19982010s
MwanzilishiKelejian & Prucha (generalized spatial 2SLS); Anselin (spatial econometrics framework)Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015)
AinaQuasi-experimental causal inference with spatial dependenceQuasi-experimental causal inference
Chanzo asiliaKelejian, 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 ↗Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903. DOI ↗
Majina mbadalaSpatial IV, Spatial 2SLS, Spatial Two-Stage Least Squares, S-IVSpatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Design
Zinazohusiana64
MuhtasariSpatial 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.Spatial Regression Discontinuity Design uses a geographic or administrative boundary as the threshold that assigns units to treatment. Observations just inside one side of the boundary are compared with those just outside it, exploiting the near-random variation in treatment status near the cutoff to recover a local causal effect. The approach is widely used in economics, political science, and public health when policies or institutions change sharply at a border.
ScholarGateSeti ya data
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  2. 2 Vyanzo
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  1. v1
  2. 2 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Spatial Instrumental Variables · Spatial Regression Discontinuity Design. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare