Optimal bandwidth selection for differences of nonparametric estimators with an application to the sharp regression discontinuity design

Arbeitspapier

We consider the problem of choosing two bandwidths simultaneously for estimating the difference of two functions at given points. When the asymptotic approximation of the mean squared error (AMSE) criterion is used, we show that minimisation problem is not well-defined when the sign of the product of the second derivatives of the underlying functions at the estimated points is positive. To address this problem, we theoretically define and construct estimators of the asymptotically first-order optimal (AFO) bandwidths which are well-defined regardless of the sign. They are based on objective functions which incorporate a second-order bias term. Our approach is general enough to cover estimation problems related to densities and regression functions at interior and boundary points. We provide a detailed treatment of the sharp regression discontinuity design.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: cemmap working paper ; No. CWP27/13

Classification and Topics

• Classification: Wirtschaft
• Subject: Bandwidth selection ; kernel density estimation ; local linear regression ; regression discontinuity design

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Arai, Yoichi ; Ichimura, Hidehiko
• Event: Veröffentlichung
• (who): Centre for Microdata Methods and Practice (cemmap)
• (where): London
• (when): 2013

Further information

• DOI: doi:10.1920/wp.cem.2013.2713
• Handle: http://hdl.handle.net/10419/79528
• Last update: 10.03.2025, 11:44 AM CET