Comparar métodos

	Regressão por Descontinuidade Difusa com Dados em Painel	Delineamento de Regressão com Descontinuidade Fuzzy
Área	Inferência causal	Inferência causal
Família	Regression model	Regression model
Ano de origem	2001 (fuzzy RDD); panel extension circa 2011	2001
Autor original	Hahn, Todd & Van der Klaauw; extended to panel settings by Papay, Willett & Murnane and others	Hahn, Todd & van der Klaauw
Tipo	Quasi-experimental causal inference	Quasi-experimental causal inference
Fonte seminal	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.
Outros nomes	Panel Fuzzy RDD, Panel FRD, Fuzzy RD with Panel Data, Panel Fuzzy RD	Fuzzy RD, Fuzzy RDD, Fuzzy RD Design, Imperfect RDD
Relacionados	5	5
Resumo	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.