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cwp421515.pdf
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A new bandwidth selection rule that uses different bandwidths for the local linear regression estimators on the left and the right of the cut-off point is proposed for the sharp regression discontinuity estimator of the mean program impact at the cut-off point. The asymptotic mean squared error of the estimator using the proposed bandwidth selection rule is shown to be smaller than other bandwidth selection rules proposed in the literature. An extensive simulation study shows that the proposed method's performances for the samples sizes 500, 2000, and 5000 closely match the theoretical predictions.
Supplementary material for this paper is available here.
Authors
![Hidehiko Ichimura](/sites/default/files/styles/square_desktop/public/2022-07/Hidechiko%20Ichimura.jpg?itok=qozO-upv)
Research Associate University of Arizona, University of Tokyo
Hidehiko is a Professor of Economics at the Eller College of Management, University of Arizona and a Research Associate at the IFS.
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
Yoichi Arai
Working Paper details
- DOI
- 10.1920/wp.cem.2015.4215
- Publisher
- Institute for Fiscal Studies
Suggested citation
Arai, Y and Ichimura, H. (2015). Simultaneous selection of optimal bandwidths for the sharp regression discontinuity estimator. London: Institute for Fiscal Studies. Available at: https://ifs.org.uk/publications/simultaneous-selection-optimal-bandwidths-sharp-regression-discontinuity-estimator (accessed: 2 July 2024).
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