Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/64641 
Year of Publication: 
2010
Series/Report no.: 
cemmap working paper No. CWP05/10
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to be rate optimal (Porter, 2003). We derive the optimal bandwidth. This optimal bandwidth depends on unknown functionals of the distribution of the data and we propose specific, consistent, estimators for these functionals to obtain a fully data-driven bandwidth choice that has the asymptotic no-regret property. We illustrate our proposed bandwidth, and the sensitivity to the choices made in this bandwidth proposal, using a data set previously analyzed by Lee (2008), as well as a small simulation study based on the Lee data set. The simulations suggest that the proposed rule performs well.
Subjects: 
Optimal Bandwidth Selection
Local Linear Regression
Regression Discontinuity Designs
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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