Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming nondifferential measurement error, we propose a consistent nonparametric estimator of the LATE when the discrepancy between the true running variable and its noisy measure is observed in an auxiliary sample of treated individuals, and when there are treated individuals at any value of the true running variable - two-sided fuzzy designs. We apply our method to estimate the effect of receiving unemployment benefits. The Journal of Econometrics is the top-field journal in econometrics.
Regression discontinuity design with continuous measurement error in the running variable
Le Barbanchon, Thomas
2017
Abstract
Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming nondifferential measurement error, we propose a consistent nonparametric estimator of the LATE when the discrepancy between the true running variable and its noisy measure is observed in an auxiliary sample of treated individuals, and when there are treated individuals at any value of the true running variable - two-sided fuzzy designs. We apply our method to estimate the effect of receiving unemployment benefits. The Journal of Econometrics is the top-field journal in econometrics.File | Dimensione | Formato | |
---|---|---|---|
Davezies_LeBarbanchon-main.pdf
non disponibili
Descrizione: Articolo principale
Tipologia:
Pdf editoriale (Publisher's layout)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
1.18 MB
Formato
Adobe PDF
|
1.18 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.