পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| স্থানিক ইন্সট্রুমেন্টাল ভ্যারিয়েবল (Spatial IV / Spatial 2SLS)× | কারণগত অনুমানের জন্য ইনস্ট্রুমেন্টাল ভ্যারিয়েবলস (IV) পদ্ধতি× | |
|---|---|---|
| ক্ষেত্র≠ | কার্যকারণ অনুমান | স্বাস্থ্য অর্থনীতি |
| পরিবার≠ | Regression model | Process / pipeline |
| উদ্ভবের বছর≠ | 1988-1998 | 1990s (modern applications) |
| প্রবর্তক≠ | Kelejian & Prucha (generalized spatial 2SLS); Anselin (spatial econometrics framework) | Angrist & Pischke (applied econometrics); rooted in econometric theory |
| ধরন≠ | Quasi-experimental causal inference with spatial dependence | Method |
| মৌলিক উৎস≠ | 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 ↗ |
| অপর নাম | Spatial IV, Spatial 2SLS, Spatial Two-Stage Least Squares, S-IV | IV, two-stage least squares, TSLS, causal estimation |
| সম্পর্কিত≠ | 6 | 3 |
| সারসংক্ষেপ≠ | 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. |
| ScholarGateডেটাসেট ↗ |
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