Сравнение методов

	Нечёткий регрессионный разрывный дизайн для панельных данных	Нечеткий регрессионный разрывный дизайн
Область	Причинно-следственный вывод	Причинно-следственный вывод
Семейство	Regression model	Regression model
Год появления	2001 (fuzzy RDD); panel extension circa 2011	2001
Автор метода	Hahn, Todd & Van der Klaauw; extended to panel settings by Papay, Willett & Murnane and others	Hahn, Todd & van der Klaauw
Тип	Quasi-experimental causal inference	Quasi-experimental causal inference
Основополагающий источник	Hahn, J., Todd, P., & Van der Klaauw, W. (2001). Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Review of Economic Studies, 68(1), 201-209.	Hahn, J., Todd, P., & van der Klaauw, W. (2001). Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design. Review of Economic Studies, 68(1), 201-209.
Другие названия	Panel Fuzzy RDD, Panel FRD, Fuzzy RD with Panel Data, Panel Fuzzy RD	Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Связанные	5	5
Сводка	Panel Data Fuzzy Regression Discontinuity Design (Panel FRD) extends the fuzzy RDD framework to settings where multiple observations per unit are available over time. It exploits a probabilistic — rather than deterministic — threshold-crossing rule to identify a local average treatment effect (LATE) while controlling for unit-level and time-level fixed effects, sharpening identification in repeated-measures contexts.	Fuzzy Regression Discontinuity Design (Fuzzy RDD) estimates causal effects when eligibility for a treatment is determined by a threshold on a running variable but actual take-up of that treatment is imperfect — some eligible units do not receive treatment and some ineligible units do. The cutoff acts as an instrument, and the estimand is a Local Average Treatment Effect (LATE) for compliers near the threshold.