পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| স্থানিক প্রবণতা স্কোর ম্যাচিং× | স্থানিক ইন্সট্রুমেন্টাল ভ্যারিয়েবল (Spatial IV / Spatial 2SLS)× | |
|---|---|---|
| ক্ষেত্র | কার্যকারণ অনুমান | কার্যকারণ অনুমান |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2000s | 1988-1998 |
| প্রবর্তক≠ | Extension of Rosenbaum & Rubin (1983) PSM to spatial settings; spatial adaptation developed in applied econometrics and epidemiology literature from the 2000s onward | Kelejian & Prucha (generalized spatial 2SLS); Anselin (spatial econometrics framework) |
| ধরন≠ | Quasi-experimental matching estimator | Quasi-experimental causal inference with spatial dependence |
| মৌলিক উৎস≠ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. DOI ↗ | 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 ↗ |
| অপর নাম | Spatial PSM, Geospatial PSM, Spatially-adjusted propensity score matching, Geographic propensity score matching | Spatial IV, Spatial 2SLS, Spatial Two-Stage Least Squares, S-IV |
| সম্পর্কিত | 6 | 6 |
| সারসংক্ষেপ≠ | Spatial Propensity Score Matching (Spatial PSM) extends the classic propensity score matching framework to settings where units are embedded in geographic space and treatment assignment or outcomes may be spatially correlated. By incorporating spatial covariates and adjacency structure into the propensity model and matching procedure, it produces causal estimates that account for geographic confounding and spillover effects. | 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. |
| ScholarGateডেটাসেট ↗ |
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