Optimal Bandwidth Choice for the Regression Discontinuity Estimator
Autor: | Guido W. Imbens, Karthik Kalyanaraman |
---|---|
Rok vydání: | 2011 |
Předmět: |
Polynomial regression
Economics and Econometrics Mathematical optimization 050208 finance 05 social sciences Bandwidth (signal processing) Local regression Estimator jel:C14 Regression 0506 political science optimal bandwidth selection local linear regression regression discontinuity designs 0502 economics and business 050602 political science & public administration Regression discontinuity design Choice rule 050207 economics Smoothing Mathematics |
Zdroj: | The Review of Economic Studies. 79:933-959 |
ISSN: | 1467-937X 0034-6527 |
DOI: | 10.1093/restud/rdr043 |
Popis: | We investigate the choice of the bandwidth for the regression discontinuity estimator. We focus on estimation by local linear regression, which was shown to have attractive properties (Porter, J. 2003, "Estimation in the Regression Discontinuity Model" (unpublished, Department of Economics, University of Wisconsin, Madison)). We derive the asymptotically optimal bandwidth under squared error loss. This optimal bandwidth depends on unknown functionals of the distribution of the data and we propose simple and consistent estimators for these functionals to obtain a fully data-driven bandwidth algorithm. We show that this bandwidth estimator is optimal according to the criterion of Li (1987, "Asymptotic Optimality for C p , C L , Cross-validation and Generalized Cross-validation: Discrete Index Set", Annals of Statistics, 15, 958--975), although it is not unique in the sense that alternative consistent estimators for the unknown functionals would lead to bandwidth estimators with the same optimality properties. We illustrate the proposed bandwidth, and the sensitivity to the choices made in our algorithm, by applying the methods to a data set previously analysed by Lee (2008, "Randomized Experiments from Non-random Selection in U.S. House Elections", Journal of Econometrics, 142, 675--697) as well as by conducting a small simulation study. Copyright , Oxford University Press. |
Databáze: | OpenAIRE |
Externí odkaz: |