Сравнение методов

	Пространственный тест-плацебо	Пространственный регрессионный разрывной дизайн (Spatial RDD)
Область	Причинно-следственный вывод	Причинно-следственный вывод
Семейство	Regression model	Regression model
Год появления	2000s–2010s	2010s
Автор метода	Developed organically in spatial econometrics and geographic RDD literature; prominent use in Dell (2010) and related work	Popularized by Dell (2010); formalized for geographic boundaries by Keele & Titiunik (2015)
Тип	Falsification / robustness check	Quasi-experimental causal inference
Основополагающий источник	Buonanno, P., Montolio, D., & Vanin, P. (2009). Does Social Capital Reduce Crime? Journal of Law and Economics, 52(1), 145-170.	Dell, M. (2010). The Persistent Effects of Peru's Mining Mita. Econometrica, 78(6), 1863-1903.
Другие названия	geographic placebo test, spatial falsification test, spatial robustness check, geographic spillover test	Spatial RDD, Geographic RDD, Border RD Design, Geographic Discontinuity Design
Связанные	4	4
Сводка	A spatial placebo test is a falsification check used in geographic or spatial causal-inference studies. The analyst applies the same estimation procedure to spatial units, boundaries, or zones where no treatment effect should exist — fake borders, shifted cutoffs, or buffer areas beyond spillover range — and checks whether a spurious effect emerges. A non-significant result in the placebo region supports the credibility of the main causal estimate.	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.