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| Пространствен дизайн на събитийно проучване× | Пространствен дизайн на регресионно прекъсване (Spatial RDD)× | |
|---|---|---|
| Област | Причинно-следствено заключение | Причинно-следствено заключение |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000s–2010s | 2010s |
| Създател≠ | Developed across applied spatial economics literature; canonical applications in Autor, Dorn & Hanson (2013) and related regional economics studies | Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015) |
| Тип≠ | Quasi-experimental causal inference with spatial structure | Quasi-experimental causal inference |
| Основополагащ източник≠ | Autor, D. H., Dorn, D., & Hanson, G. H. (2013). The China Syndrome: Local Labor Market Effects of Import Competition in the United States. American Economic Review, 103(6), 2121-2168. DOI ↗ | Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903. DOI ↗ |
| Други названия | spatial event study, geographic event study, spatial dynamic DiD, place-based event study | Spatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Design |
| Свързани≠ | 5 | 4 |
| Резюме≠ | Spatial event study design estimates the dynamic causal effects of a geographically concentrated shock or policy by plotting how outcomes in affected locations evolve relative to unaffected locations across time periods, while explicitly accounting for spatial spillovers and autocorrelation across geographic units. It is widely used in regional and urban economics to evaluate place-based policies, trade shocks, and local labour market interventions. | 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. |
| ScholarGateНабор от данни ↗ |
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